Small businesses are always trying to find new ways to compete and grow market share. Eric Ng Co-Founder and CEO Boutir, and Andy Chan Co-Founder and Chairman Qupital talk to Anthony Lacavera about how their companies are taking down competitive pressures and helping small businesses with ...

About Boutir

Boutir is a mobile app which help merchants to easily set up their online store and manage inventory.

Boutir - Crunchbase Company Profile & Funding

Information on valuation, funding, cap tables, investors, and executives for Boutir. Use the PitchBook Platform to explore the full profile.

Boutir Company Profile: Valuation & Investors | PitchBook

Boutir - Cloud-based software tool to create online stores.

Boutir - Company Profile - Tracxn

Boutir: We passionate about helping merchants in all sizes to do less and sell more. View company info, jobs, team members, culture, funding and more.

Boutir | AngelList

Boutir is a cloud-based software tool to create online stores. Its features include payments management, marketing tools, product content management, reporting &amp; analytics, and more. Pricing depends on the package and the number of features. Clients include Love Vintage, Egyptian Store, Lee Hon HK, and more. The company ...

Boutir | Tracxn

We are thrilled to announce our successful collaboration with Hang Seng Bank in their partnership with Cyberport Hong Kong to support Community Companies undergoing digital transformation. At Boutir, we pride ourselves as a leading social mobile commerce solutions provider and multi-channel ...

Boutir | LinkedIn

Owler&#x27;s exclusive company and industry insights make it easy to find and monitor competitors, prospects, and key accounts – so you can increase your revenue and grow your business.

Boutir Company Profile | Owler

Boutir's Competitors, Revenue, Number of Employees ... - Owler

boutir - view company info, available jobs, team size, office location and more.

boutir | Himalayas

Find useful insights on Boutir’s company details, tech stack, news alerts, competitors and more. Use Slintel to connect with top decision-makers at Boutir.

Boutir Company Insights, Tech Stack, and Competitors | Slintel

Boutir top competitors are BigCommerce, Magento and Miva and they have annual revenue of $435k and 3 employees.

Boutir: Revenue, Competitors, Alternatives

You can read employee interviews and the latest company&#x27;s initiative of Boutir. Social Mobile Commerce solution for individual retailers and enterprise retailers to set up online stores and run business via a mobile app.

About Boutir - Wantedly

Apply to job opportunities at Boutir. Get the latest information about building career at Boutir, reviews &amp; the company culture

Boutir Career Information 2022 | Glints

Find contact information for Boutir. Learn about their Flowers, Gifts &amp; Specialty Stores, Retail market share, competitors, and Boutir&#x27;s email format.

Boutir Company Profile | Management and Employees List

Established since 1999 in Hong Kong, Invision Worldwide Ltd is a focused marketing and distribution organisation. With a long established presence and deep understanding in Hong Kong, China, Macau, Taiwan and Singapore; we are committed to support our principal's needs in building market demand, generating and supporting sales and serving as an important link to customers throughout the region. Focusing on consumer products, we offer extensive local market access with a high degree in specialisation. Read below for more information of the products we manage: Consumer Goods - HEALTH and WELLNESS 1. Ysnore anti snoring nasal spray - Over The Counter homeopathic nasal spray to relief snoring and reduce the cause of snoring effectively. US Patented. www.ysnore.com.sg www.ysnore.com.hk 2. Sprayable Sleep - Sleep in a Spray. Helps people to get a better sleep in a spray. US Patented. Hong Kong distribution. https://www.facebook.com/pages/Sprayable-Sleep/473574849469186 3. Fire Garlic MaMa Black Garlic - "a garlic a day, keeps the doctor away". Organic. STC Tested. https://www.linkedin.com/pulse/black-good-your-health-maggi-ho?trk=pulse_spock-articles www.facebook.com/firegarlicmama Consumer Goods - CONSUMER ELECTRONICS 1. Bladeless Ceiling Fan - World's 1st new invention. Distribution for China, Hong Kong, Macau, Taiwan and Singapore. US Patented. https://www.facebook.com/pages/Exhale-Fans-Hong-Kong/1140936282586887 www.ExhaleFans.com.hk www.ExhaleFans.com.tw www.ExhaleFans.com.sg

Boutir

Indoor navigation and machine learning combination both for helping users to find the most suitable stores and for helping stores to advertise their products. This is my first article for the last few months and I am incredibly happy to get back. During this time my life turned in a different direction and now I’m doing something completely different from what I did half a year ago. But still, I remained faithful to neural networks, machine learning, and technology in general. Now I am developing a mobile SDK and Android application at Navigine team. A few words about the Navigine — comprehensive indoor positioning platform (I did not come up with anything, just took a phrase from our website). I think it should have become clear to the reader that today we will talk about indoor positioning and navigation. If you read at least some of my articles, it will become obvious to you that I am a big fan of machine learning and augmented reality and therefore today’s article will certainly not only be about indoor navigation but about its use in conjunction with machine learning. Well, let’s try to understand all the opportunities that these two technologies provide for us and maybe some of you will be able to create something incredible soon. Or maybe it will be me! Implementing Indoor Positioning First, let’s deal with indoor navigation, and then move on to dessert, that is, I wanted to say to machine learning and predictions. In the field of indoor positioning and navigation, there is not only one single solution, already on the first page of Google search you can find some good options, but since I am well acquainted with our solution, I will talk based on it. First things first, you need to create the digital map of your location, in the case of this article, this will be the map of the shopping mall. Now you need to add the Bluetooth beacons to this location and link them in the app to the places where you deployed them. By the way, the more beacons you add, the better the quality of positioning and navigation you will get. As for beacons, I will leave you the choice of their producer, dear reader. Do not forget to add zones, barriers, draw routes and mark all the venues, so the user will be able to find the place he needs faster. And the next step is the most interesting part for me — using Navigine SDK in your iOS and Android applications. You can use Navigine SDK to add indoor navigation, push notifications and tracking functions. Let’s take a deeper look at each of these opportunities. — it is obvious that users will use it to build optimal routes to the destination points and to find their positions. But if you look at the title, you will understand that we can get some more interesting information from this point. Indoor navigation —Push notifications are a separate very extensive topic, so I will cover this in another article. Push notifications — this will allow you to see the full route of the user at every second when he uses the app. As you probably already guessed, on this functionality we will focus on the next part of this article. Tracking functions It becomes obvious what kind of data we can get using , so let’s start moving on to the most interesting part of this story. Further, the story will go on how we can use this data, what things and events we can predict and what interesting functionality we can add to the Shopping Mall application. Navigine SDK Machine Learning and Data Science part In this section, let’s look at two cases when the user does not need to register in your application and you do not receive any data about him. Well, and the second case, when you know his age, gender and some other personal data that he had to enter when he registered. Of course, the second case gives us many more opportunities in predicting and analyzing data but even without these data, you can achieve any results. Without user data In this case, we will have to get out on the basis of the data that we have, but even here we can achieve great results. Even if we don’t have user information, we still know that repeated searches for routes are made from the same device and therefore we understand which routes belong to a specific user. I will give some examples of how you can use the data, but of course, no code will be given, as well as explanations of how to implement this, I will leave it to you. Knowing the routes each user builds, we can group them according to these routes. We can already use these data in different ways, for example, to analyze at what time each group goes to shopping centers and thereby we can offer them certain services. Also based on this data, we can determine the interest of new users by their first few searches. Or for example, to notice different trends, as one group of people after a certain time begins to be interested in other things and use this knowledge in the right direction. These are probably the most obvious options that come to mind, but with their help, you can achieve very large and interesting results. So let’s move on to the way when we know at least some user data and see what obvious solutions we can find. With having some user data Imagine the same points as in the previous paragraph, but just add there that we still know the gender of the user, his age and some other personal data, such as the address of residence or something like that. Now we will be able to do clustering not only by interests but also by many other parameters, for example, by sex, by age, by place of residence and notice the exceptional interests of each group. And of course the most important thing, now when registering a new user, we can immediately recognize his interests and predict which stores may be more interested in him, which will allow us to advertise the right offers and. This data will be useful not only for the users themselves, but also for the owners of shopping malls, they will understand which stores are more interesting for users, this will allow opening more similar shops, also knowing these they can offer the correct rental value, and many other interesting solutions and useful information can be fished out by holding a small brainstorm. Conclusion Summing up all the above, I want to say that indoor navigation can be used in very interesting places and based on its data, you can analyze a lot of interesting and most importantly valuable information. Technologies allow us to improve our lives and reduce the number of tasks that we have to think about, freeing up much more time so that we can do more useful things. No matter how you feel about it, the time for great technological solutions has already come and every day it improves our life, even if we do not notice most of it. Therefore, I wish you to advance in the study of technology and science as far as possible and I hope someone will benefit from this article. Previously published at https://towardsdatascience.com/indoor-positioning-and-predicting-the-most-suitable-boutique-for-customers-in-shopping-malls-8149b3097b57

Indoor Positioning and Predicting the Most Suitable Boutiques in Shopping Malls for Customers

Creating High-Performing CTA’s: The Ultimate Guide

We are notoriously open about our agency's failures. Being a startup and boutique fintech consultancy firm, we surely have a lot of those: First, we could not acquire a contract with the local banks while being established in Georgia. We had to establish an entity in UAE to win a proper payment partnership.
We were sure that launching an e-commerce store would not require an IT guy. Now, we are happily bound by our relationship with an IT guy, probably forever.
When we launched the sales of our country's deep-dive profiles, we expected a lot more demand than we got. Now it is time to recognize that it did not work as we thought it would. What we’ve found and why pivoting Our target audience is small and HIGHLY specific, consisting of professionals in fintech and related digital industries. Instead of buying reports, they are bringing new exciting projects and custom research orders to our table because we seem to know our stuff. The only type of reports in hot demand right now are industry-specific. This led us to understand that our gain is not the hard cash per report; it is the lead generation that our free country’s fintech profile reports are creating. Thanks to our country profiling work, we are blessed with the greatest clients and exciting research and consulting projects. The FinTech Wikipedia Without further ado, we decided to open up all the fintech profile deep-dive reports presented on the website previously for sale. While updating the data across these papers and formatting every country profile, we came up with the idea of building the first-ever absolutely free FinTech Wikipedia—a global database divided into regions and countries and available in three languages: English, Spanish, and French. 🔎 Hint for desktop browsing lovers: every click across this map leads to an open and detailed country profile! Now, there are 31 free country reports online: 🌄 Africa ▪️ Algeria ▪️ Kenya ▪️ Nigeria ▪️ South Africa 🕌 Middle East ▪️ Iran
▪️ Saudi Arabia
▪️ Turkey
▪️ UAE 🚌 Asia&Pacific ▪️ Australia
▪️ China
▪️ India
▪️ Indonesia
▪️ Japan
▪️ Mongolia
▪️ Thailand 🦙 Americas ▪️ Argentina
▪️ Brazil
▪️ Canada
▪️ Colombia
▪️ Mexico
▪️ Peru
▪️ USA 🏰 Western Europe ▪️ Germany
▪️ Italy
▪️ Portugal
▪️ Spain
▪️ Sweden
▪️ UK 🌅 Eastern Europe & Middle Asia ▪️ Kazakhstan
▪️ Russia
▪️ Serbia Enjoy reading the latest trends and insights. Feel free to share it with your peers and colleagues. Send your feedback to the WTM team. Keep pushing the boundaries of financial knowledge! ‘What the Money?’ is a fintech consultancy bureau that advises on doing business across the globe and talks about digital innovations, payment landscapes, and e-commerce. WTM releases news digests and analytics, country reports, and op-eds on hot topics in digital industries. Find available reports on the website. Follow WTM socials to learn more fintech insights and news: official blog, LinkedIn community, and Telegram channel. We are notoriously open about our agency's failures. Being a startup and boutique fintech consultancy firm, we surely have a lot of those: First, we could not acquire a contract with the local banks while being established in Georgia. We had to establish an entity in UAE to win a proper payment partnership. We were sure that launching an e-commerce store would not require an IT guy. Now, we are happily bound by our relationship with an IT guy, probably forever. When we launched the sales of our country's deep-dive profiles, we expected a lot more demand than we got. Now it is time to recognize that it did not work as we thought it would. First, we could not acquire a contract with the local banks while being established in Georgia. We had to establish an entity in UAE to win a proper payment partnership. acquire a contract We were sure that launching an e-commerce store would not require an IT guy . Now, we are happily bound by our relationship with an IT guy, probably forever. would not require an IT guy When we launched the sales of our country's deep-dive profiles , we expected a lot more demand than we got. Now it is time to recognize that it did not work as we thought it would. the sales of our country's deep-dive profiles What we’ve found and why pivoting Our target audience is small and HIGHLY specific, consisting of professionals in fintech and related digital industries. Instead of buying reports, they are bringing new exciting projects and custom research orders to our table because we seem to know our stuff. The only type of reports in hot demand right now are industry-specific. This led us to understand that our gain is not the hard cash per report; it is the lead generation that our free country’s fintech profile reports are creating. Thanks to our country profiling work, we are blessed with the greatest clients and exciting research and consulting projects . exciting research and consulting projects The FinTech Wikipedia Without further ado, we decided to open up all the fintech profile deep-dive reports presented on the website previously for sale. While updating the data across these papers and formatting every country profile, we came up with the idea of building the first-ever absolutely free FinTech Wikipedia —a global database divided into regions and countries and available in three languages: English, Spanish, and French. FinTech Wikipedia 🔎 Hint for desktop browsing lovers: every click across this map leads to an open and detailed country profile! this map Now, there are 31 free country reports online: 🌄 Africa ▪️ Algeria Algeria ▪️ Kenya Kenya ▪️ Nigeria Nigeria ▪️ South Africa South Africa 🕌 Middle East ▪️ Iran ▪️ Saudi Arabia ▪️ Turkey ▪️ UAE Iran Saudi Arabia Turkey UAE 🚌 Asia&Pacific ▪️ Australia ▪️ China ▪️ India ▪️ Indonesia ▪️ Japan ▪️ Mongolia ▪️ Thailand Australia China India Indonesia Japan Mongolia Thailand 🦙 Americas ▪️ Argentina ▪️ Brazil ▪️ Canada ▪️ Colombia ▪️ Mexico ▪️ Peru ▪️ USA Argentina Brazil Canada Colombia Mexico Peru USA 🏰 Western Europe ▪️ Germany ▪️ Italy ▪️ Portugal ▪️ Spain ▪️ Sweden ▪️ UK Germany Italy Portugal Spain Sweden UK 🌅 Eastern Europe & Middle Asia ▪️ Kazakhstan ▪️ Russia ▪️ Serbia Kazakhstan Russia Serbia Enjoy reading the latest trends and insights. Feel free to share it with your peers and colleagues. Send your feedback to the WTM team. Keep pushing the boundaries of financial knowledge! Enjoy reading ‘What the Money?’ is a fintech consultancy bureau that advises on doing business across the globe and talks about digital innovations, payment landscapes, and e-commerce. WTM releases news digests and analytics, country reports, and op-eds on hot topics in digital industries. Find available reports on the website . Follow WTM socials to learn more fintech insights and news: official blog , LinkedIn community , and Telegram channel . ‘What the Money?’ ‘What the Money?’ the website official blog LinkedIn community Telegram channel

How we Failed Again, but You Won. A Startup Story Pivoting to a Free FinTech Wikipedia

কিভাবে আমরা আবার ব্যর্থ, কিন্তু আপনি জিতেছি. একটি স্টার্টআপ স্টোরি একটি ফ্রি ফিনটেক উইকিপিডিয়ায় পিভোটিং

Wie wir wieder gescheitert sind, aber Sie gewonnen haben.  Die Geschichte eines Startups auf dem Weg zu einer freien FinTech-Wikipedia

Cómo volvimos a fallar, pero tú ganaste. Una historia de startup que gira hacia una Wikipedia FinTech gratuita

Comment nous avons encore échoué, mais vous avez gagné. Une histoire de startup tournant vers un Wikipédia FinTech gratuit

हम फिर कैसे असफल हुए, लेकिन आप जीत गए। एक स्टार्टअप स्टोरी जो मुफ़्त फिनटेक विकिपीडिया की ओर मुड़ती है

私たちはまた失敗しましたが、あなたは勝ちました。無料のフィンテックウィキペディアに転換したスタートアップストーリー

우리가 또 실패했지만 당신이 승리한 방법. 무료 핀테크로 전환하는 스타트업 스토리 Wikipedia

Como falhamos novamente, mas você venceu. Uma história de startup que gira em torno de uma Wikipédia FinTech gratuita

Как мы снова проиграли, но вы победили. История стартапа, переходящего на бесплатную FinTech Википедию

Nasıl Yine Başarısız Olduk Ama Sen Kazandın. Ücretsiz FinTech Vikipedi'ye Dönen Bir Startup Hikayesi

Chúng ta lại thất bại như thế nào nhưng bạn đã thắng. Câu chuyện khởi nghiệp hướng tới Wikipedia FinTech miễn phí

我们再次失败，但你赢了。一个转向免费金融科技维基百科的创业故事

Welcome to HackerNoon’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. THE LIST is a luxury fashion marketplace powered by <GENESYS>, an AI-based API developed in-house. THE LIST allows the world’s best boutiques and brands to run AI-driven catalog production at current 810x cost efficiency vs. traditional product catalog production, enabling retailers to sell in 190 countries with integration time in single-digit days. THE LIST was founded by Andreas Skorski and has offices in New York City and Dubai. 1. What is your company in 2–5 words? Luxury fashion powered by AI. 2. Why is now the time for your company to exist? Luxury ecommerce has imploded in the last year or so (Financial Times, NYT). This is not an understatement. Online marketplaces for luxury brands are weighed down by incredibly high costs: tech development, catalog production, shipping, and data architecture. The tech behind luxury fashion marketplaces is 10 years behind and extremely inefficient. Even with margins of 50%, these marketplaces can’t make it work. That said, the market for luxury is not going anywhere.We built The List to showcase what the next stage of e-commerce is: that AI can operate a luxury fashion marketplace. We are building the largest LLM library in the industry to eliminate some of the market’s critical operational inefficiencies. Our AI-based API, <GENESYS> is the first viable, market-tested AI solution in the luxury industry, and powers other major retailers as well. Our machine learning API transforms any in-store retail product into a catalog in real-time by mapping ERP (enterprise resource planning) data, extracting attributes, and enriching data from images,  producing dozens of relevant data points  to describe it as such. It doesn’t just see a photo of a shoe. It understands the height of the heel, the fact that it’s suede, the exact color, the seasons it can be worn in. It’s 98.9% accurate and working for hundreds of thousands of products in real-time. 3. What do you love about your team, and why are you the ones to solve this problem? Many of our data scientists previously worked for a competitor or the biggest global retail brands. They see how the future of e-commerce could look like and want to actually build something that operates at the same level AI really operates today, having efficiency as the number 1 priority in mind. The cost of getting a single product (SKU) into a catalog can be up to $80 per SKU. It’s fairly common for marketplaces to add 100,000 new SKUs to their sites weekly, so our competitors are burning a ton of cash every week. Our team has been watching, training, and guiding our own model of catalog production for years. Our cost is now down to less than 10 cents per SKU. So the team is remarkably goal-oriented and determined to find solutions to problems they personally experienced as data scientists in the industry. 4. If you weren’t building your startup, what would you be doing? Probably building some other startup. When I was 17 I created the first ad scanner technology for print magazines in Germany. Since then I haven’t really stopped. 5. At the moment, how do you measure success? What are your metrics? We are a software-focused retail marketplace, so we look at both the retail success of our marketplace and the efficiency of our <GENESYS> API. For us it is all about giving a top-class experience to our customers while driving down costs for our suppliers. From a software POV: Accuracy rate of our LLMs — how often is human intervention needed?


Items scanned – SKUs processed per month by our API


Integration time – how long does it take for a retailer to put their products on The List? From a retail POV we are looking at: Gross Merchandise Value
Customers and their stickiness
Suppliers and their stickiness 6. In a few sentences, what do you offer to whom? If you buy luxury fashion: You can expect to find all your favorite brands on The List at the best possible price globally available, enabled through <GENESYS>. If you are a decision maker at a company that sells luxury fashion: You can expect the fastest integration time globally available with no engineering cost involved from your side, market-tested AI-based catalog production, and related AI-driven efficiencies in marketing, shipping, and pricing. If there is an inefficiency in the value chain we are likely already working on the models to fix it. 7. What’s most exciting about your traction to date? Luxury fashion is perfect for data scientists to train a model. It’s very fast moving and changes all the time. There’s seasonality in collections, now even more with capsule collections. And the more variations you feed into a model, the faster it learns. We started out years ago, and at the time, AI-driven efficiencies were not hot. The progress of LLMs on the market has accelerated interest in what we do, which is very exciting. You can do a lot with open source models, but you have an advantage if you already have a database that you’ve been training with your own models and scanning millions of data points. Tens of thousands of customers have validated our AI with their purchases.  It’s gratifying to be getting traction now with suppliers and other major players in the industry. 8. Where do you think your growth will be next year? We are going to scale our direct to consumer marketplace growth this year in more markets while  also building out our platform business with our b2b customers. 9. Tell us about your first paying customer and revenue expectations over the next year. We had our first paying customer years ago! We’re pivoting. 10. What’s your biggest threat? Our biggest threat is a general bearishness in the luxury market at the moment. Retailers are skittish about investing in multi brand marketplaces after what has happened to our competitors. They’re looking at finding better solutions, but there is still a lot of education to be done in the AI space to showcase it is already a commercially viable and operating solution and not just a dream of the future. Our task is to convince them that marketplaces aren’t the problem; it’s just that they need to be better and evolve. The List is the next evolution of how to operate e-commerce 2.0 in luxury fashion. This startup founder interview template is based on HackerNoon Founder & CEO David Smooke’s ten questions for startup founders. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Welcome to HackerNoon’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. Welcome to HackerNoon ’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. HackerNoon The link for the template is HERE. THE LIST is a luxury fashion marketplace powered by <GENESYS>, an AI-based API developed in-house. THE LIST THE LIST allows the world’s best boutiques and brands to run AI-driven catalog production at current 810x cost efficiency vs. traditional product catalog production, enabling retailers to sell in 190 countries with integration time in single-digit days. THE LIST was founded by Andreas Skorski and has offices in New York City and Dubai. Andreas Skorski 1. What is your company in 2–5 words? Luxury fashion powered by AI. 2. Why is now the time for your company to exist? Luxury ecommerce has imploded in the last year or so ( Financial Times , NYT ). This is not an understatement. Financial Times Financial Times NYT NYT Online marketplaces for luxury brands are weighed down by incredibly high costs: tech development, catalog production, shipping, and data architecture. The tech behind luxury fashion marketplaces is 10 years behind and extremely inefficient. Even with margins of 50%, these marketplaces can’t make it work. That said, the market for luxury is not going anywhere. We built The List to showcase what the next stage of e-commerce is: that AI can operate a luxury fashion marketplace. We are building the largest LLM library in the industry to eliminate some of the market’s critical operational inefficiencies. Our AI-based API, <GENESYS> is the first viable, market-tested AI solution in the luxury industry, and powers other major retailers as well. Our machine learning API transforms any in-store retail product into a catalog in real-time by mapping ERP (enterprise resource planning) data, extracting attributes, and enriching data from images,  producing dozens of relevant data points  to describe it as such. It doesn’t just see a photo of a shoe. It understands the height of the heel, the fact that it’s suede, the exact color, the seasons it can be worn in. It’s 98.9% accurate and working for hundreds of thousands of products in real-time. 3. What do you love about your team, and why are you the ones to solve this problem? Many of our data scientists previously worked for a competitor or the biggest global retail brands. They see how the future of e-commerce could look like and want to actually build something that operates at the same level AI really operates today, having efficiency as the number 1 priority in mind. The cost of getting a single product (SKU) into a catalog can be up to $80 per SKU. It’s fairly common for marketplaces to add 100,000 new SKUs to their sites weekly, so our competitors are burning a ton of cash every week. Our team has been watching, training, and guiding our own model of catalog production for years. Our cost is now down to less than 10 cents per SKU. So the team is remarkably goal-oriented and determined to find solutions to problems they personally experienced as data scientists in the industry. 4. If you weren’t building your startup, what would you be doing? Probably building some other startup. When I was 17 I created the first ad scanner technology for print magazines in Germany. Since then I haven’t really stopped. 5. At the moment, how do you measure success? What are your metrics? We are a software-focused retail marketplace, so we look at both the retail success of our marketplace and the efficiency of our <GENESYS> API. For us it is all about giving a top-class experience to our customers while driving down costs for our suppliers. From a software POV: Accuracy rate of our LLMs — how often is human intervention needed? Items scanned – SKUs processed per month by our API Integration time – how long does it take for a retailer to put their products on The List? Accuracy rate of our LLMs — how often is human intervention needed? Accuracy rate of our LLMs — how often is human intervention needed? Items scanned – SKUs processed per month by our API Items scanned – SKUs processed per month by our API Integration time – how long does it take for a retailer to put their products on The List? Integration time – how long does it take for a retailer to put their products on The List? From a retail POV we are looking at: Gross Merchandise Value Customers and their stickiness Suppliers and their stickiness Gross Merchandise Value Customers and their stickiness Suppliers and their stickiness 6. In a few sentences, what do you offer to whom? If you buy luxury fashion: If you buy luxury fashion: You can expect to find all your favorite brands on The List at the best possible price globally available, enabled through <GENESYS>. If you are a decision maker at a company that sells luxury fashion: If you are a decision maker at a company that sells luxury fashion: You can expect the fastest integration time globally available with no engineering cost involved from your side, market-tested AI-based catalog production, and related AI-driven efficiencies in marketing, shipping, and pricing. If there is an inefficiency in the value chain we are likely already working on the models to fix it. 7. What’s most exciting about your traction to date? Luxury fashion is perfect for data scientists to train a model. It’s very fast moving and changes all the time. There’s seasonality in collections, now even more with capsule collections. And the more variations you feed into a model, the faster it learns. We started out years ago, and at the time, AI-driven efficiencies were not hot. The progress of LLMs on the market has accelerated interest in what we do, which is very exciting. You can do a lot with open source models, but you have an advantage if you already have a database that you’ve been training with your own models and scanning millions of data points. Tens of thousands of customers have validated our AI with their purchases.  It’s gratifying to be getting traction now with suppliers and other major players in the industry. 8. Where do you think your growth will be next year? We are going to scale our direct to consumer marketplace growth this year in more markets while  also building out our platform business with our b2b customers. 9. Tell us about your first paying customer and revenue expectations over the next year. We had our first paying customer years ago! We’re pivoting. 10. What’s your biggest threat? Our biggest threat is a general bearishness in the luxury market at the moment. Retailers are skittish about investing in multi brand marketplaces after what has happened to our competitors. They’re looking at finding better solutions, but there is still a lot of education to be done in the AI space to showcase it is already a commercially viable and operating solution and not just a dream of the future. Our task is to convince them that marketplaces aren’t the problem; it’s just that they need to be better and evolve. The List is the next evolution of how to operate e-commerce 2.0 in luxury fashion. This startup founder interview template is based on HackerNoon Founder & CEO David Smooke’s ten questions for startup founders. This startup founder interview template is based on HackerNoon Founder & CEO David Smooke ’s ten questions for startup founders . HackerNoon Founder & CEO David Smooke ten questions for startup founders Would you like to take a stab at answering some of these questions? The link for the template is HERE. Would you like to take a stab at answering some of these questions? The link for the template is HERE. The link for the template is HERE.

Tech Behind Luxury Fashion Marketplaces is 10 Years Behind, Says The List Founder Andreas Skorski

Really? So you're just going to open anyway? I really wanted you to skip this one. I was busy travelling, and I had nothing to write. Came back from an 18 hour flight and kept thinking of what to write, but I couldn’t. So I figured I would ask for a favor and have you pass this one. Yet here we are.. So thanks for that.. What I am supposed to do now? Let me think. Oh— You know what? I have a quick story to tell. I was visiting my brother on a small and (very) remote island of French Polynesia called Nuku Hiva. So small, in fact, that it doesn’t even appear on the map unless you zoom wayyy in. Don’t believe me? The point is, it’s a small airport, and you have to walk yourself to the terminal. They have cones that tell you where to walk, but most importantly, where they don’t want you to walk past. On the way in, I was tired from my long journey there. I just followed the line. On the way out, I was feeling a little more like myself. I saw these cones again. And they saw me. They were lined up like soldiers, proudly wearing bright orange. Probably to show off, and also form a contrast to the tarmac. The cones seemed to stare back at me with a challenge. I am pretty sure they were whispering “Go ahead, step over. We dare you.” Wait. What? I looked at them. My pulse quickened immediately. I was being challenged. “What do you mean you dare me to step over? Do you even know me? I can do whatever I want.” I glance around. Everyone else is obediently tracing the path to the plane. Not me. The impulse takes over. I step over the cone barrier, and my foot lands on the other side.. I suddenly feel like a moonwalker claiming uncharted territory. The hot Polynesian air crackled with tension. I could feel the cones' silent outrage at my audacity. The thrill of the forbidden surges through me. My heart thumps in exhilaration. I am euphoric. But then, as if on cue, “Excuse me, sir, please return to the path,” a voice cut through my daydream. A staff member waved her hands with a mix of fear and anger. And just like that—I was caught. My quest was over. I had to wave my white flag, and step back over. Although they reclaimed my newly acquired territory, they did not take away my victory. I stepped back into line, but I had a smirk on my lips. The thrill of defiance had sent a jolt of excitement through my veins. It was a potent mixture of satisfaction and adrenaline. A simple act of rebellion that felt disproportionately exhilarating. Anyway.. I make my way to my seat on the plane. And then I start thinking.. Why do these feelings emerge so strongly when we push against boundaries? You see, it wasn't about the cones or the airport—it was a snapshot of a deeper, almost instinctual drive within us all. This urge to defy the norm. The urge to resist restrictions. It taps into something fundamental about human nature. The intrinsic desire for autonomy and freedom. This instinct inspired today's letter. It's about the allure of the forbidden and the resistance to being told what not to do. As it turns out, it plays in various facets of our lives. The small acts of rebellion when we pick the road less traveled The significant decisions that define our individuality The way we make decisions in general How we are influenced by people, companies, and marketing 1. Why We Chase the Forbidden Reflecting on that moment of rebellion at the airport. It’s clear this isn't just personal. It's universal. This instinct to challenge the boundaries is deeply embedded in us all. Just look at how Apple used this trait with their "Think Different" campaign. Apple didn’t sell products—they sold an idea. You know how? They aligned their brand with Einstein, Dylan, and MLK. Apple celebrated those who defy norms. They joined those who tap our desire to be part of something different. The Genius of "Think Different" Apple's strategy was a cultural statement more than it was pure marketing. These icons weren’t just talented; they were revolutionaries. Their simple message? It's cool to be different; and it's powerful to think outside the box. This strategy wasn't about selling; it was about igniting a cultural shift. Think about it—how often do we gravitate towards things just because they offer us a taste of defiance? That’s what Apple mastered. It’s almost like they marketed a rebellion. 2. The Neuroscience Behind the Temptation When we're told not to do something, our brain's instinct isn't just to listen—it's often to rebel. This rebellion is powered by our brain's reward system. Neurotransmitters, like dopamine, play a crucial role in it. We often pair dopamine with pleasure. But it's also about motivation, learning, and seeking rewards. When faced with a prohibition, our brain perceives it as a challenge. Engaging in the forbidden act and succeeding triggers a release of dopamine, which feels rewarding. Then there’s the prefrontal cortex—our brain’s rational part that tries to keep us in check. Dopamine signals pleasure and potential reward. The prefrontal cortex calculates the consequences. It tries to apply the brakes, weighing long-term outcomes against immediate gratification. Fun fact. This part of the brain is still developing in young adults. This explains why teenagers often take more risks. And boy was mine still developing during my teenage years. When you and I were barely walking on two feet and had hair to make Chewbacca jealous, our survival relied on curiosity and exploration. Survival depended on exploring the unknown and overcoming obstacles. This required questioning and testing the environment all the time. It was not about liking to try new things; it's about the neurological reward systems that encouraged those traits. It was necessary for survival, and it was neural, too. I was necessary for things like discovering what to eat. Imagine our ancestors venturing into new territories in search of something to eat. They come across a mushroom, bright red with white spots—pretty much screaming, "Don't touch me bro". But, curiosity and defiance? It's built-in. So, someone had to take the first bite, right? And you can bet they regretted it right after. That’s the kind of trial and error that taught everyone else to steer clear of the fancy fungi. But not all explorations ended badly. Sometimes, they found new, nourishing foods. These foods became staples in their diet. It makes me wonder about the first person who discovered fire—what an intense moment that must have been. Anyway, just some food for thought on your own terms. Fast forward to today. This system still urges us to push boundaries and explore new possibilities. This is true even when we’re safe from saber-toothed tigers. This legacy influences everything. It affects how we approach challenges. It explains why a simple "Do not push" button becomes almost irresistible. It explains why you felt compelled to open this letter even when explicitly told not to. Understanding these impulses allows us to channel them well. We can use them to motivate ourselves, manage others, and craft messages that resonate on a gut level. By acknowledging and embracing this innate curiosity, we can turn a simple urge into a powerful tool for engagement. 3. Defying Conventions: My Path to Independence Thinking back on where I am today, a lot of it came from just not fitting the mold. I wanted to go to an architecture school, but never could. Why? Well, I just didn't vibe with the whole school scene. My grades weren't great—not because I couldn't handle the work of because or below average intelligence. It was because I couldn't stand the way they taught things. So, I'd end up doodling and distracting others instead of paying attention. My jobs? I've always had a bit of a tough time with authority. Starting my company was my way out. I did not like having to obey my superiors at work simply because they were my superiors. When they were wrong, I made sure they knew. They did not like it, and I rarely kept a job for more than 6 months. Looking back, each of those defiant steps led me right here, to doing my own thing my own way. This journey isn't just mine. It's a testament to the power of questioning norms. This power can redefine personal paths and how we approach marketing and social engagement. Speaking of Marketing.. 4. Impact on Marketing and Social Behavior My journey away from traditional roles mirrors the tactics businesses use to captivate consumers. Here's the thing about marketing—it thrives on our natural urge to reach for the forbidden. Take "limited edition" products or "members-only" sales. This is about scarcity, but not only. It’s makes us feel like we're part of an exclusive club, stepping past the rope where others can't go. In video games, they hide Easter eggs you can only find by not following the usual paths. It turns players into insiders, sharing secrets that feel almost rebellious. Fashion plays with this, too. Look at those unannounced drops—they create a buzz by being elusive, sparking a mad dash to grab something unique before it disappears. This marketing savvy taps directly into our love for the elusive and the exclusive, turning simple buying decisions into moments of personal triumph against the norm. After stepping back into line at the airport, smirking from my small act of rebellion, I realized something crucial: the same thrill of defiance that fuels our personal choices can powerfully drive our business strategies. This realization isn't just about me—it's about how any business can tap into these universal instincts to craft compelling marketing strategies and create unforgettable customer experiences. Let's explore how this instinct for defiance can be strategically harnessed in your business to captivate and engage your audience. 5. How to Use This in Your Business - Framework and ideas Understanding Reactance in Marketing Let's talk about using reactance in a way that really resonates with people. How about we make our marketing a bit rebellious? Imagine you own a boutique coffee shop that prides itself on unique, ethically sourced beans. To use reactance, you could launch a campaign called "Not your grandma’s Bustelo." It would say that your coffee is for those who dare to taste the unique and bold. This resonates with consumers' desire to rebel. Each purchase is an act of defiance. Scarcity and Exclusivity Ever noticed how a 'limited-time offer' makes us want to buy something right now? That's scarcity at work. It's like telling people, "Hey, these gems won’t last." It makes whatever you're selling seem more valuable. It has everyone rushing to make sure they don’t miss out. Imagine this. You are a business coach. You're offering an elite retreat named " " to your top-tier clients. Figure It Out, or Die It starts with a tough, three-day jungle trek. The trek pushes clients to their physical and mental limits. This adventure sets the stage for the climax. It's a coaching session in total darkness, deep in a secluded jungle cabin. There are no distractions. This compels clients to rely only on their sharp instincts and introspective insights. Limit it to just three clients annually. This exclusive setup not only ensures a transformative experience but also plays on the scarcity effect. How much would a thrill-seeking CEO pay for such a unique challenge if marketed just right? We offer products for a limited time. This taps into a consumer's urge to defy the fear of missing out. It turns the purchase into a rebellion against the market's scarcity. Storytelling Techniques Craft your brand's story to resonate with the spirit of independence. Narratives that highlight overcoming adversity or defying odds can inspire customers to align with your brand as a statement of their values. You are the founder and can’t find a story? Call the business coach above and attend his retreat. You’ll have one 🙂 Such stories can inspire customers. They show them how to align with your brand as a statement of their values. : Contrarian Content Engage your audience with content that challenges mainstream ideas. This could be through thought leadership pieces. They take a new stance on common issues. This attracts those who appreciate a fresh perspective. Do you run a financial advisory firm? Do you want to challenge normal retirement planning? You could create a series of blog posts or videos titled “ ”. You Might Lose It All, But Your Grandkids Will Be Proud Ok, that might be a little bold. But you get the idea. And you’ll certainly get their attention. Our content challenges mainstream thoughts. It appeals to those who pride themselves on questioning the norm and valuing independent thought. In the end, whether it's stepping over a line of cones at a Polynesian airport or defying conventional marketing tactics, the allure of the forbidden runs deep within us. We have primal instincts for survival. They drive our decisions and actions. From them to the strategies of modern businesses, the urge to challenge boundaries shapes us. As you reflect on this newsletter (that you were kindly asked not to open), remember this. The most intriguing adventures start with a simple act of defiance. Embracing the spirit of rebellion can lead to unexpected discoveries and transformative experiences. As you navigate your own journey, may you find joy in pushing boundaries. Until next time, keep defying expectations and embracing the thrill of the forbidden. Strategizingly yours, Ben

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Interview with Dr. Yonatan Sompolinsky of Kaspa

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Kiriaki Frangias;
(2) Andrew Lin;
(3) Ellen Vitercik;
(4) Manolis Zampetakis. Table of Links Abstract and Introduction Warm-up: Agents with known equal disutility Agents with unknown disutilites Experiments Conclusions and future directions, References A Summary of notation B Omitted proofs from Section 2 C Omitted proofs from Section 3 D Additional Information about Experiments 5 Conclusions and future directions We studied the multifaceted problem of designing a crowdsourcing mechanism that efficiently and accurately ranks a set of items using pairwise comparisons from rational agents. We based our approach on the classic principal-agent model from contract theory. To distribute comparisons among agents, we used an unexpected connection to the social golfer problem which allowed us to simultaneously minimize the agents’ workload and ensure enough agents evaluate each comparison. We showed that by optimizing the payment mechanisms, the principal can incentivize enough agents to exert effort, ensuring our algorithm recovers the ground-truth ranking. Our experiments showed that even when noise is added to our original model, our method consistently aids the principal in retrieving the accurate ground-truth ordering. llude, which allowed us to assign the same set of verified comparisons to all agents. How should our mechanism change if agents can collude? Moreover, we assumed that agents who do not exert effort will return comparisons consistent with a uniformly-random permutation of the items. What other models of agent behavior can we study under this framework? Finally, as is standard in contract theory, we assumed that the principal knows the probability π that an effortful agent is good. How should we handle the case where π is unknown? References [1] Abolfazl Asudeh, Gensheng Zhang, Naeemul Hassan, Chengkai Li, and Gergely V. Zaruba. Crowdsourcing pareto-optimal object finding by pairwise comparisons. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (CIKM), 2015. [2] Ralph Allan Bradley and Milton E Terry. Rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39(3/4):324–345, 1952. [3] Yang Cai, Constantinos Daskalakis, and Christos Papadimitriou. Optimum statistical estimation with strategic data sources. In Conference on Learning Theory (COLT), 2015. [4] Xi Chen, Paul N Bennett, Kevyn Collins-Thompson, and Eric Horvitz. Pairwise ranking aggregation in a crowdsourced setting. In Proceedings of the International Conference on Web Search and Data Mining, pages 193–202, 2013. [5] Yuxin Chen and Changho Suh. Spectral MLE: Top-k rank aggregation from pairwise comparisons. In International Conference on Machine Learning (ICML), 2015. [6] Paul Duetting, Tomer Ezra, Michal Feldman, and Thomas Kesselheim. Combinatorial contracts. In Symposium on Foundations of Computer Science (FOCS), 2022. [7] Anindya Ghose, Panagiotis G Ipeirotis, and Beibei Li. Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Science, 31(3):493–520, 2012. [8] John Guiver and Edward Snelson. Bayesian inference for plackett-luce ranking models. In International Conference on Machine Learning (ICML), 2009. [9] Stephen Guo, Aditya Parameswaran, and Hector Garcia-Molina. So who won? dynamic max discovery with the crowd. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD ’12, page 385–396, New York, NY, USA, 2012. Association for Computing Machinery. ISBN 9781450312479. doi: 10.1145/2213836.2213880. URL https://doi.org/10.1145/2213836.2213880. [10] Guru Guruganesh, Jon Schneider, and Joshua Wang. Contracts under moral hazard and adverse selection. In ACM Conference on Economics and Computation (EC), 2021. [11] R. Jurca and B. Faltings. Mechanisms for making crowds truthful. Journal of Artificial Intelligence Research, 34:209–253, mar 2009. doi: 10.1613/jair.2621. URL https://doi.org/10.1613%2Fjair.2621. [12] Radu Jurca and Boi Faltings. Robust incentive-compatible feedback payments. In Workshop on Trading Agent Design and Analysis, 2006. [13] Radu Jurca and Boi Faltings. Minimum payments that reward honest reputation feedback. In ACM Conference on Economics and Computation (EC), 2006. [14] Jiawen Kang, Zehui Xiong, Dusit Niyato, Dongdong Ye, Dong In Kim, and Jun Zhao. Toward secure blockchain-enabled internet of vehicles: Optimizing consensus management using reputation and contract theory. IEEE Transactions on Vehicular Technology, 68(3):2906–2920, 2019. [15] Ngai Meng Kou, Yan Li, Hao Wang, Leong Hou U, and Zhiguo Gong. Crowdsourced top-k queries by confidence-aware pairwise judgments. Proceedings of the 2017 ACM International Conference on Management of Data, 2017. URL https://api.semanticscholar.org/CorpusID:36647621. [16] Jean-Jacques Laffont and David Martimort. Moral Hazard: The Basic Trade-Offs, pages 145–186. Princeton University Press, 2002. URL http://www.jstor.org/stable/j.ctv7h0rwr.8. [17] Shili Lin. Rank aggregation methods. Wiley Interdisciplinary Reviews: Computational Statistics, 2(5):555–570, 2010. [18] Tyler Lu and Craig Boutilier. Learning mallows models with pairwise preferences. In International Conference on Machine Learning (ICML), 2011. [19] C. L. Mallows. Non-null ranking models. i. Biometrika, 44:114–130, 1957. URL https://api.semanticscholar.org/CorpusID:121527283. [20] Fei Mi and Dit-Yan Yeung. Probabilistic graphical models for boosting cardinal and ordinal peer grading in moocs. In AAAI Conference on Artificial Intelligence, 2015. [21] Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong Do, Andrew Ng, and Daphne Koller. Tuned models of peer assessment in moocs. In Proceedings of The 6th International Conference on Educational Data Mining (EDM), 2013. [22] R. L. Plackett. The Analysis of Permutations. Journal of the Royal Statistical Society Series C, 24(2):193–202, June 1975. doi: 10.2307/2346567. URL https://ideas.repec.org/a/bla/jorssc/v24y1975i2p193-202.html. [23] Karthik Raman and Thorsten Joachims. Methods for ordinal peer grading. In International Conference on Knowledge Discovery and Data Mining (KDD), 2014. [24] Karthik Raman and Thorsten Joachims. Bayesian ordinal peer grading. In Proceedings of the ACM Conference on Learning at Scale, 2015. [25] Vikas C Raykar, Shipeng Yu, Linda H Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, and Linda Moy. Learning from crowds. Journal of machine learning research, 11(4), 2010. [26] Nihar Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, and Martin Wainwright. Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2015. [27] Nihar B Shah, Joseph K Bradley, Abhay Parekh, Martin Wainwright, and Kannan Ramchandran. A case for ordinal peer-evaluation in moocs. In NIPS Workshop on Data-Driven Education, 2013. [28] Louis Leon Thurstone. The method of paired comparisons for social values. The Journal of Abnormal and Social Psychology, 21:384–400, 1927. URL https://api.semanticscholar.org/CorpusID:144595330. [29] Markus Triska. Solution Methods for the Social Golfer Problem. PhD thesis, Vienna University of Technology, March 2008. Available from https://www.metalevel.at/mst.pdf. [30] Kristi Tsukida, Maya R Gupta, et al. How to analyze paired comparison data. Department of Electrical Engineering University of Washington, Tech. Rep. UWEETR-2011-0004, 1, 2011. [31] Bo Waggoner and Yiling Chen. Output agreement mechanisms and common knowledge. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1): 220–226, Sep. 2014. doi: 10.1609/hcomp.v2i1.13151. URL https://ojs.aaai.org/index.php/HCOMP/article/view/13151. [32] Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, and Michael I. Jordan. The sample complexity of online contract design. In ACM Conference on Economics and Computation (EC), 2023. This paper is available on Arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. Authors: (1) Kiriaki Frangias; (2) Andrew Lin; (3) Ellen Vitercik; (4) Manolis Zampetakis. This paper is available on arxiv under CC 4.0 license. Authors : Authors (1) Kiriaki Frangias; (2) Andrew Lin; (3) Ellen Vitercik; (4) Manolis Zampetakis. Table of Links Abstract and Introduction Abstract and Introduction Warm-up: Agents with known equal disutility Warm-up: Agents with known equal disutility Agents with unknown disutilites Agents with unknown disutilites Experiments Experiments Conclusions and future directions, References Conclusions and future directions, References A Summary of notation A Summary of notation B Omitted proofs from Section 2 B Omitted proofs from Section 2 C Omitted proofs from Section 3 C Omitted proofs from Section 3 D Additional Information about Experiments D Additional Information about Experiments 5 Conclusions and future directions We studied the multifaceted problem of designing a crowdsourcing mechanism that efficiently and accurately ranks a set of items using pairwise comparisons from rational agents. We based our approach on the classic principal-agent model from contract theory. To distribute comparisons among agents, we used an unexpected connection to the social golfer problem which allowed us to simultaneously minimize the agents’ workload and ensure enough agents evaluate each comparison. We showed that by optimizing the payment mechanisms, the principal can incentivize enough agents to exert effort, ensuring our algorithm recovers the ground-truth ranking. Our experiments showed that even when noise is added to our original model, our method consistently aids the principal in retrieving the accurate ground-truth ordering. llude, which allowed us to assign the same set of verified comparisons to all agents. How should our mechanism change if agents can collude? Moreover, we assumed that agents who do not exert effort will return comparisons consistent with a uniformly-random permutation of the items. What other models of agent behavior can we study under this framework? Finally, as is standard in contract theory, we assumed that the principal knows the probability π that an effortful agent is good. How should we handle the case where π is unknown? References [1] Abolfazl Asudeh, Gensheng Zhang, Naeemul Hassan, Chengkai Li, and Gergely V. Zaruba. Crowdsourcing pareto-optimal object finding by pairwise comparisons. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (CIKM), 2015. [2] Ralph Allan Bradley and Milton E Terry. Rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39(3/4):324–345, 1952. [3] Yang Cai, Constantinos Daskalakis, and Christos Papadimitriou. Optimum statistical estimation with strategic data sources. In Conference on Learning Theory (COLT), 2015. [4] Xi Chen, Paul N Bennett, Kevyn Collins-Thompson, and Eric Horvitz. Pairwise ranking aggregation in a crowdsourced setting. In Proceedings of the International Conference on Web Search and Data Mining, pages 193–202, 2013. [5] Yuxin Chen and Changho Suh. Spectral MLE: Top-k rank aggregation from pairwise comparisons. In International Conference on Machine Learning (ICML), 2015. [6] Paul Duetting, Tomer Ezra, Michal Feldman, and Thomas Kesselheim. Combinatorial contracts. In Symposium on Foundations of Computer Science (FOCS), 2022. [7] Anindya Ghose, Panagiotis G Ipeirotis, and Beibei Li. Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Science, 31(3):493–520, 2012. [8] John Guiver and Edward Snelson. Bayesian inference for plackett-luce ranking models. In International Conference on Machine Learning (ICML), 2009. [9] Stephen Guo, Aditya Parameswaran, and Hector Garcia-Molina. So who won? dynamic max discovery with the crowd. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD ’12, page 385–396, New York, NY, USA, 2012. Association for Computing Machinery. ISBN 9781450312479. doi: 10.1145/2213836.2213880. URL https://doi.org/10.1145/2213836.2213880. [10] Guru Guruganesh, Jon Schneider, and Joshua Wang. Contracts under moral hazard and adverse selection. In ACM Conference on Economics and Computation (EC), 2021. [11] R. Jurca and B. Faltings. Mechanisms for making crowds truthful. Journal of Artificial Intelligence Research, 34:209–253, mar 2009. doi: 10.1613/jair.2621. URL https://doi.org/10.1613%2Fjair.2621. [12] Radu Jurca and Boi Faltings. Robust incentive-compatible feedback payments. In Workshop on Trading Agent Design and Analysis, 2006. [13] Radu Jurca and Boi Faltings. Minimum payments that reward honest reputation feedback. In ACM Conference on Economics and Computation (EC), 2006. [14] Jiawen Kang, Zehui Xiong, Dusit Niyato, Dongdong Ye, Dong In Kim, and Jun Zhao. Toward secure blockchain-enabled internet of vehicles: Optimizing consensus management using reputation and contract theory. IEEE Transactions on Vehicular Technology, 68(3):2906–2920, 2019. [15] Ngai Meng Kou, Yan Li, Hao Wang, Leong Hou U, and Zhiguo Gong. Crowdsourced top-k queries by confidence-aware pairwise judgments. Proceedings of the 2017 ACM International Conference on Management of Data, 2017. URL https://api.semanticscholar.org/CorpusID:36647621. [16] Jean-Jacques Laffont and David Martimort. Moral Hazard: The Basic Trade-Offs, pages 145–186. Princeton University Press, 2002. URL http://www.jstor.org/stable/j.ctv7h0rwr.8. [17] Shili Lin. Rank aggregation methods. Wiley Interdisciplinary Reviews: Computational Statistics, 2(5):555–570, 2010. [18] Tyler Lu and Craig Boutilier. Learning mallows models with pairwise preferences. In International Conference on Machine Learning (ICML), 2011. [19] C. L. Mallows. Non-null ranking models. i. Biometrika, 44:114–130, 1957. URL https://api.semanticscholar.org/CorpusID:121527283. [20] Fei Mi and Dit-Yan Yeung. Probabilistic graphical models for boosting cardinal and ordinal peer grading in moocs. In AAAI Conference on Artificial Intelligence, 2015. [21] Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong Do, Andrew Ng, and Daphne Koller. Tuned models of peer assessment in moocs. In Proceedings of The 6th International Conference on Educational Data Mining (EDM), 2013. [22] R. L. Plackett. The Analysis of Permutations. Journal of the Royal Statistical Society Series C, 24(2):193–202, June 1975. doi: 10.2307/2346567. URL https://ideas.repec.org/a/bla/jorssc/v24y1975i2p193-202.html. [23] Karthik Raman and Thorsten Joachims. Methods for ordinal peer grading. In International Conference on Knowledge Discovery and Data Mining (KDD), 2014. [24] Karthik Raman and Thorsten Joachims. Bayesian ordinal peer grading. In Proceedings of the ACM Conference on Learning at Scale, 2015. [25] Vikas C Raykar, Shipeng Yu, Linda H Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, and Linda Moy. Learning from crowds. Journal of machine learning research, 11(4), 2010. [26] Nihar Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, and Martin Wainwright. Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2015. [27] Nihar B Shah, Joseph K Bradley, Abhay Parekh, Martin Wainwright, and Kannan Ramchandran. A case for ordinal peer-evaluation in moocs. In NIPS Workshop on Data-Driven Education, 2013. [28] Louis Leon Thurstone. The method of paired comparisons for social values. The Journal of Abnormal and Social Psychology, 21:384–400, 1927. URL https://api.semanticscholar.org/CorpusID:144595330. [29] Markus Triska. Solution Methods for the Social Golfer Problem. PhD thesis, Vienna University of Technology, March 2008. Available from https://www.metalevel.at/mst.pdf. [30] Kristi Tsukida, Maya R Gupta, et al. How to analyze paired comparison data. Department of Electrical Engineering University of Washington, Tech. Rep. UWEETR-2011-0004, 1, 2011. [31] Bo Waggoner and Yiling Chen. Output agreement mechanisms and common knowledge. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1): 220–226, Sep. 2014. doi: 10.1609/hcomp.v2i1.13151. URL https://ojs.aaai.org/index.php/HCOMP/article/view/13151. [32] Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, and Michael I. Jordan. The sample complexity of online contract design. In ACM Conference on Economics and Computation (EC), 2023. This paper is available on Arxiv under CC 4.0 license. This paper is available on Arxiv under CC 4.0 license. Arxiv

Algorithmic Contract Design for Crowdsourced Ranking: Conclusions, Future Directions, and References

Welcome to HackerNoon’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. 1. What is your company in 2–5 words? Digital product agency disrupting healthcare. 2. Why is now the time for your company to exist? There is no denying that the pace of innovation and technology has accelerated in the last decade. However, the healthcare industry has not evolved as quickly as other industries. It faces unique challenges, like a lack of agility, strict regulations, antiquated processes, and slow innovation. Although there are many people in the sector working to improve quality and accessibility, systemic problems and financial interests limit what can be achieved. Our strategy is to bring agility to this setting by using our knowledge of technology, user-centric approach, and in-depth knowledge of the business to create software that is strategically planned, scalable, and cleverly constructed. 3. What do you love about your team, and why are you the ones to solve this problem? When we first set out, we were quite excited about developing digital solutions that prioritized the needs and wants of users and delivered genuine value. By then, we collaborated with businesses in every sector of the economy, including real estate, retail, food, entertainment, agronomy, retail, and finance. Even though we've produced incredible products and gained a lot of knowledge from the process, we believed that focus and mission were still lacking. In 2020, during the pandemic, we made a strategic shift and decided to focus 100% on healthcare, allowing us to fully immerse ourselves in the industry, gain specialized knowledge, and, most importantly, have a shared, meaningful purpose. This change gave our entire team a compelling mission and a defined path. Who wouldn't find satisfaction in working on initiatives for a sector of the economy that ultimately saves lives? I guess that’s what I love most about the team and why we are the ones who solve problems. We’re a team of focused, knowledgeable, and creative people with a shared purpose: improving healthcare. 4. If you weren’t building your startup, what would you be doing? I would probably be building another startup. I’ve been an entrepreneur since I was a teenager, so I’m sure that if Light-it had not succeeded, I would be building something else. 5. At the moment, how do you measure success? What are your metrics? We work with OKRs (Objectives and Key Results), and they are measured quarterly. We have company-wide OKRs and OKRs per department. They help us stay aligned with the same goals quarter to quarter. 6. In a few sentences, what do you offer to whom? In broad terms, we partner with our clients to help them ideate, design, and develop healthcare digital products. The challenge we resolve is the lack of expertise in developing healthcare software with a product mindset and keeping strategy, budget, compliance, and user experience in mind.  There are hundreds of software development firms with no experience in healthcare, which can lead to short-term gains at the expense of long-term scalability and maintenance. We at Light-itadopt a unique strategy. We follow industry best practices, implementing scalable models across several platforms and providing end-to-end product development services with extensive user experience support and consulting. Since we have an agile approach, startups are our bread and butter. Nevertheless, our interactions with health systems have also been excellent. Our introduction of an agile vision and innovative mindset has been extremely effective in these circumstances, given their customary bureaucratic and slower ways. Finding a reliable partner is usually difficult for a healthcare organization, but finding someone who can offer both high-tech development and strategic advice is much more difficult. That's what makes us unique. 7. What’s most exciting about your traction to date? **Light-it'**s traction has been steadily growing year after year, an incredibly encouraging trend. Last year was particularly exciting for us as we forged partnerships with industry giants like ABInBev Foundation, the world's largest beer company, and Inviza, a groundbreaking RPM and DTX product for the US Air Force.  These collaborations are not only about business and transactions – they validate our position as leaders in our field and serve as a powerful encouragement to continue our hard work. 8. Where do you think your growth will be next year? We have been collaborating with startups, supporting them through the entire product development process, from launch to scaling. Now that we are collaborating with Health Systems, we plan to continue doing so because we have seen such a positive impact. We don't intend to expand the company too quickly because, as a team, we want to keep our boutique approach. We aim to keep our crew size between one hundred and two hundred. We always have new projects coming up. In my opinion, one of the biggest promises in health technology is generative AI. Puppeteeris a spinoff company we launched last year, and it is the result of the realization that 2024 was going to be the year of generative AI and that humanity will either have to accept it or perish. Our first round is presently being raised, and we have high hopes for it this year. Regarding our long-term future, Light-it's DNA will always embrace new technologies and pathways, so who knows what else might emerge! "You win, or you learn" strikes a chord with me. Every new endeavor, whether it succeeds or fails, adds to our development and resiliency. I'm committed to establishing a positive work environment that prioritizes curiosity, boldness, ownership, and dedication to ongoing development while also considering the well-being of our team. 9. Tell us about your first paying customer and revenue expectations over the next year. The first paying customers we had were family members and friends building e-commerces. Since then, we’ve worked with startups from pre-seed to Series D, with Fortune 500s and some of the biggest health systems in the world! In terms of revenue, we expect to keep growing at the rate of 50% per year. 10. What’s your biggest threat? We have all heard that AI will replace software engineers, so I guess that should be my biggest thread as a software development company owner. Still, I’m convinced that our team has minds that no AI can substitute: Empathy, strategy, and creativity are some of the skills needed in a product team that AI can't substitute. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Welcome to HackerNoon’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. Welcome to HackerNoon ’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. HackerNoon The link for the template is HERE. 1. What is your company in 2–5 words? Digital product agency disrupting healthcare. 2. Why is now the time for your company to exist? There is no denying that the pace of innovation and technology has accelerated in the last decade. However, the healthcare industry has not evolved as quickly as other industries. It faces unique challenges, like a lack of agility, strict regulations, antiquated processes, and slow innovation. Although there are many people in the sector working to improve quality and accessibility, systemic problems and financial interests limit what can be achieved. Our strategy is to bring agility to this setting by using our knowledge of technology, user-centric approach, and in-depth knowledge of the business to create software that is strategically planned, scalable, and cleverly constructed. 3. What do you love about your team, and why are you the ones to solve this problem? When we first set out, we were quite excited about developing digital solutions that prioritized the needs and wants of users and delivered genuine value. By then, we collaborated with businesses in every sector of the economy, including real estate, retail, food, entertainment, agronomy, retail, and finance. Even though we've produced incredible products and gained a lot of knowledge from the process, we believed that focus and mission were still lacking. In 2020, during the pandemic, we made a strategic shift and decided to focus 100% on healthcare, allowing us to fully immerse ourselves in the industry, gain specialized knowledge, and, most importantly, have a shared, meaningful purpose. This change gave our entire team a compelling mission and a defined path. Who wouldn't find satisfaction in working on initiatives for a sector of the economy that ultimately saves lives? I guess that’s what I love most about the team and why we are the ones who solve problems. We’re a team of focused, knowledgeable, and creative people with a shared purpose: improving healthcare. 4. If you weren’t building your startup, what would you be doing? I would probably be building another startup. I’ve been an entrepreneur since I was a teenager, so I’m sure that if Light-it had not succeeded, I would be building something else. Light-it Light-it 5. At the moment, how do you measure success? What are your metrics? We work with OKRs (Objectives and Key Results), and they are measured quarterly. We have company-wide OKRs and OKRs per department. They help us stay aligned with the same goals quarter to quarter. 6. In a few sentences, what do you offer to whom? In broad terms, we partner with our clients to help them ideate, design, and develop healthcare digital products. The challenge we resolve is the lack of expertise in developing healthcare software with a product mindset and keeping strategy, budget, compliance, and user experience in mind.  There are hundreds of software development firms with no experience in healthcare, which can lead to short-term gains at the expense of long-term scalability and maintenance. We at Light-it adopt a unique strategy. We follow industry best practices, implementing scalable models across several platforms and providing end-to-end product development services with extensive user experience support and consulting. Light-it Since we have an agile approach, startups are our bread and butter. Nevertheless, our interactions with health systems have also been excellent. Our introduction of an agile vision and innovative mindset has been extremely effective in these circumstances, given their customary bureaucratic and slower ways. Finding a reliable partner is usually difficult for a healthcare organization, but finding someone who can offer both high-tech development and strategic advice is much more difficult. That's what makes us unique. 7. What’s most exciting about your traction to date? **Light-it'**s traction has been steadily growing year after year, an incredibly encouraging trend. Last year was particularly exciting for us as we forged partnerships with industry giants like ABInBev Foundation, the world's largest beer company, and Inviza, a groundbreaking RPM and DTX product for the US Air Force.  These collaborations are not only about business and transactions – they validate our position as leaders in our field and serve as a powerful encouragement to continue our hard work. 8. Where do you think your growth will be next year? We have been collaborating with startups, supporting them through the entire product development process, from launch to scaling. Now that we are collaborating with Health Systems, we plan to continue doing so because we have seen such a positive impact. We don't intend to expand the company too quickly because, as a team, we want to keep our boutique approach. We aim to keep our crew size between one hundred and two hundred. We always have new projects coming up. In my opinion, one of the biggest promises in health technology is generative AI. Puppeteer is a spinoff company we launched last year, and it is the result of the realization that 2024 was going to be the year of generative AI and that humanity will either have to accept it or perish. Our first round is presently being raised, and we have high hopes for it this year. Puppeteer Regarding our long-term future, Light-it's DNA will always embrace new technologies and pathways, so who knows what else might emerge! "You win, or you learn" strikes a chord with me. Every new endeavor, whether it succeeds or fails, adds to our development and resiliency. I'm committed to establishing a positive work environment that prioritizes curiosity, boldness, ownership, and dedication to ongoing development while also considering the well-being of our team. 9. Tell us about your first paying customer and revenue expectations over the next year. The first paying customers we had were family members and friends building e-commerces. Since then, we’ve worked with startups from pre-seed to Series D, with Fortune 500s and some of the biggest health systems in the world! In terms of revenue, we expect to keep growing at the rate of 50% per year. 10. What’s your biggest threat? We have all heard that AI will replace software engineers, so I guess that should be my biggest thread as a software development company owner. Still, I’m convinced that our team has minds that no AI can substitute: Empathy, strategy, and creativity are some of the skills needed in a product team that AI can't substitute. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Would you like to take a stab at answering some of these questions? The link for the template is HERE. The link for the template is HERE.

BOUTIR

boutir.com

11-50 employees

Since 1999

COMPANY RANKING

BOUTIR

EVERGREEN INDEX #1941

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Boutir WIKI

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BOUTIR

boutir.com

11-50 employees

Since 1999

COMPANY RANKING

BOUTIR

EVERGREEN INDEX #1941

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STORIES ABOUT BOUTIR

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