Omniflo is a data-driven digital platform to enable fast and efficient offline retail distribution for online brands.

Omniflo - Crunchbase Company Profile & Funding

Sell where people shop · © Omniway Technologies Pvt Ltd

Omniflo

Omniflo | 973 followers on LinkedIn. Enabling omnichannel expansion for D2C brands. | We take D2C Brands omnichannel from online to offline markets. Sell where people shop!

Omniflo | LinkedIn

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

Omniflo Company Profile: Valuation & Investors | PitchBook

Omniflow developed a Smart IoT Lamppost powered by wind and solar transforms a regular street light into a sustainable smart infrastructure capable of housing multiple added-value applications like 5G Small Cells, Edge Computing ,Computer Vision and deliver high quality data from software services.

Omniflow - Crunchbase Company Profile & Funding

Omniflo is a data-driven digital platform to enable fast and efficient offline retail distribution for online-first/D2C brands.

Omniflo - Entrepreneur First

Omniflo - Provider of multi-channel commerce suite solutions for D2C brands. Raised a total funding of $57.8K over 1 round from 2 investors.

Omniflo - Company Profile - Tracxn

&quot;Bengaluru-based Omniflo helps clients expand their addressable market by not only providing what the customer wants but also providing it where they want it. In September 2021, UK-based investment firm Entrepreneur First invested in Omniflo.&quot;

Omniflo Company Profile, information, investors, valuation & Funding

Omniflow | 4,631 followers on LinkedIn. Transforming street lights into carbon neutral smart IOT/5G infrastructures | Omniflow provides sustainable smart city solutions. We Help Cities and Organizations to drop the power consumption and carbon footprint more than 90% on lighting and provide ...

Omniflow | LinkedIn

Omniflow provides sustainable solutions for Smart Cities powered by wind and solar. Our best products are Smart Lamppost, Smart Bench, Solar Smart Lighting, Smart Pole, enhanced with IoT Software, edge computing, video analytics. CO2 reduction, decarbonization, Sustainable services.

Smart IoT lamppost powered by Wind & Solar | Omniflow

Omniflo Why Omniflo Made It To The List While businesses are going increasingly digital and consumers are leaning towards the trend, Bengaluru-based Omniflo is helping D2C brands build an offline presence to get them started on an omnichannel journey. According to the company, 90% of product ...

Omniflo - Products, Competitors, Financials, Employees, Headquarters ...

Apply privately to 130,000+ remote jobs and startup jobs near you with one application. See salary and equity upfront. Find the latest tech jobs, company overviews, benefits and more at Wellfound (formerly AngelList Talent).

Omniflo Careers

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Omniflo - Commerce and Shopping Startup, Bengaluru

Omniflo - Funding, Financials, Valuation & Investors

OMNI Flow Computers, Inc. | 1,390 followers on LinkedIn. OMNI Flow Computers, Inc. is the largest independent manufacturer of custody transfer flow computers and the industry leader in oil and gas measurement solutions. Built on a sterling reputation for being the standard in liquid and gas ...

OMNI Flow Computers, Inc. | LinkedIn

OMNI is the most recognized and trusted brand of flow computers for oil and gas measurement. We have the technology and talent to deliver the right solution for your toughest applications · We have the largest installed base in the industry — connected to more than 50,000 custody meters ...

Home - OMNI Flow Computers, Inc

We take D2C Brands omnichannel from online to offline markets. Sell where people shop!

The wait is over! - it’s time to celebrate the champion startups of the world. Shout out to all of the participants in our ! You did a wonderful job showcasing your incredible startups and powering through another year. 2023 Startups of the Year is a community-driven voting platform brought to you by HackerNoon that recognizes and celebrates tech startups changing technology and the world for the better. The award started on May 8th, 2023, where the internet nominated and voted for 30k startups around the world. The voting period remained open until December 31, 2023, and now we are here with the winner announcement after a comprehensive evaluation by the HackerNoon team. Startups of the Year 2023 To see the top 3 startups in each respective city, visit and pick a city. hackernoon.com/startups You’ll get a little surprise 😉 Here are the Startups of the Year Regional Announcements: North America Europe Asia Africa South America Oceania Misc/Remote From all of us at HackerNoon, thank YOU for your excellent campaign perseverance 🥺 This year has been awesome! Startups of the Year 2023 is concluded with 623k+ total votes, up from 215k+ votes in the inaugural startup competition. We look forward to seeing you again in the next campaign (stay tuned 😉)! Without further ado, let us kick off the announcement by celebrating the cities with top votes per region for 2023 🎉 North America (11,697 votes): Winner: Bloomfilter Cleveland, Ohio (8,835 votes) - Winner: SerpApi Austin, Texas , California (5,564 votes) - Winner: Finch San Francisco (4,258 votes) - Winner: RELAYTO SoMa, California - (3339 votes) Winner: Windscribe Toronto, Canada, North America (3304 votes) - Winner: Vouched Seattle (2716 votes) - Winner: Seccuri Palo Alto, CA, North America (2671 votes) - Winner: Salsa Valley Miami, FL, North America (2,613 votes) - Winner: Majhi Group Manhattan, New York (2423 votes) - Winner: Flieber, Inc. New York City, NY, North America See the complete announcement for the . Startups of the Year, North America, here Europe (45,612 votes) - Winner: Algomo London, UK (2,344votes) - Winner: Data Lake Warsaw, Poland (1,955 votes) - Winner: Hoken Tech Bari, Italy (1716 votes) - Winner: Not8 Amsterdam, Netherlands (1657 votes) - Winner: KYVE Frankfurt Am Main, Germany (1566 votes) - Winner: BazaIT Kyiv, Ukraine (1496 votes) - Winner:  Unity Network Tallinn, Estonia (1,478 votes) - Winner: Volcaino Ghent, Belgium (1,288 votes) - Winner: Owl Me Dublin, Ireland (1198 votes) - Winner: Groover Paris, France See the complete announcement for the . Startups of the Year, Europe, here Oceania (3,350 votes) - Winner: Sharepass Melbourne (2,107 votes) - Winner: The Catfisher Project Perth, Australia (220 votes) - Winner: Gemini AI Solutions Auckland, New Zealand, Oceania (213 votes) - Winner: Nexustorage Wellington, New Zealand, Oceania (138 votes) - Winner: Coviu Sydney (124 votes) - Winner: Bopple Brisbane, Australia, Oceania (124 votes) - Winner: Regional CFO New South Wales, Australia, Oceania (106 votes) - Winner: Edit on the Spot Gold Coast, Australia, Oceania (93 votes) - Winner: Knowledge Satnav Canbera, Australia, Oceania , Australia, Oceania (48 votes) - Winner: Peptalk360 North Melbourne, Melbourne See the complete announcement for the . Startups of the Year, Oceania, here Asia (16,345 votes) - Winner: Serenity Shield Singapore (13,588 votes) - Winners: QUIXY Telangana, India (10,168 votes) - Winner: HealthySure Mumbai, India (3,865 votes) - Winner: InterviewBuddy Visakhapatnam, India (3,733 votes) - Winner: Omniflo Bengaluru, India (4589 votes) - Winner: MeNow Tel Aviv (3877 votes) - Winner: ForestVPN Dubai (2478 votes) - Winner: TechGraph Powai, Mumbai, India (1004 votes) - Winner: Reelo Ahmedabad, GJ, India (875 votes) - Winner: Debt Hunter Hong Kong, China See the complete announcement for the . Startups of the Year, Asia, here Africa (8,179 votes) - Winner: GO PLATFORM Algiers, Algeria (767 votes) - Winner: Tudu Accra, Ghana (415 votes) - Winner: Treford Lagos, Nigeria (265 votes) - Winner: Phalconwise Ogbomosho, Nigeria (157 votes) - Winner: AbuErdan Cairo (151 votes) - Winner: Eazipay Lekki (144 votes) - Winner: KaziConnect Dar es Salaam, Tanzania (101 votes) - Winner: faceATT Gauteng, South Africa (79 votes) - Winner: Dimagi Cape Town (71 votes) - Winner: Sabi Addis Ababa See the complete announcement for the . Startups of the Year, Africa, here South America (376 votes ) - Winner: UpGirl Santiago, Chile (217 votes) - Winner: Klever Sao Paulo, Brazil (191 votes) - Winner: Tributo Simple Buenos Aires, Argentina (127 votes) - Winner: Light-it Montevideo, Uruguay (87 votes) -Winner: Thousand Antioquia, Colombia (108 votes) - Winner: GetLavado Lima (101 votes) - Winner: Cogniflow Medellin (73 votes) - Winner: TPAGA Bogota (73 votes) - Winner: Reliv Quito (47 votes) - WInner: Quantex Cordoba See the complete announcement for the . Startups of the Year, South America, here Misc/Remote: Featured Startups (1500 votes) - Winner: CIC Chain Remote, Earth (1193 votes) - Winner: Reship Colony US Misc (146 Votes) - Winner: Partful UK, Misc (116 votes) - Winner: GoMining British Virgin Islands Misc (283 Votes) - Winner: tomorrowSpace Germany Misc (225 votes) - Winner: Dtravel Cayman Islands See the complete announcement for Misc/Remote startups . here Once again, HUGE CONGRATULATIONS and BIG PROPS to all of the top Startups of each region this year! The whole team at HackerNoon would like to thank you for your perseverance in the campaign, and we look forward to seeing you in the next campaign. About HackerNoon’s Startups Of The Year Startups of The Year is HackerNoon’s Flagship community-driven event celebrating startups that survived and thrived in 2023. 30,000 startups across 4200+ cities and six continents participated this year to be crowned the best startup in their city. Visit our page to learn more. FAQ Companies that blog more get 67% more leads - Jumpstart your company’s blogging journey by purchasing our . Business Blogging Package The 2023 Startups Of The Year is sponsored by: . . The winners get a free .Tech Domain, a HackerNoon NFT, and a Tech Company News Page. TECH Domains

Stand Up for the Champion Startups of the Year! 

বছরের চ্যাম্পিয়ন স্টার্টআপের জন্য দাঁড়ান!

Setzen Sie sich für die Champion-Startups des Jahres ein!

¡Defiende a las startups campeonas del año!

Défendez les startups championnes de l’année !

वर्ष के चैंपियन स्टार्टअप के लिए खड़े रहें!

今年のチャンピオンスタートアップのために立ち上がろう!

올해의 챔피언 스타트업을 위해 일어서세요!

Defenda as startups campeãs do ano!

Встаньте на защиту стартапов-чемпионов года!

Yılın Şampiyon Startup'ları için Ayağa Kalkın!

Hãy ủng hộ các công ty khởi nghiệp vô địch của năm!

为年度冠军初创企业挺身而出！

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Andrey Zhmoginov, Google Research & {azhmogin,sandler,mxv}@google.com;
(2) Mark Sandler, Google Research & {azhmogin,sandler,mxv}@google.com;
(3) Max Vladymyrov, Google Research & {azhmogin,sandler,mxv}@google.com. Table of Links Abstract and Introduction
Problem Setup and Related Work
HyperTransformer
Experiments
Conclusion and References
A Example of a Self-Attention Mechanism For Supervised Learning
B Model Parameters
C Additional Supervised Experiments
D Dependence On Parameters and Ablation Studies
E Attention Maps of Learned Transformer Models
F Visualization of The Generated CNN Weights
G Additional Tables and Figures D DEPENDENCE ON PARAMETERS AND ABLATION STUDIES Most of our parameter explorations were conducted for OMNIGLOT dataset. We chose a 16-channel model trained on a 1-shot-20-way OMNIGLOT task as an example of a model, for which just the logits layer generation was sufficient. We also chose a 4-channel model trained on a 5-shot-20-way OMNIGLOT task for the role of a model, for which generation of all convolutional layers proved to be beneficial. Figures 5 and 6 show comparison of training and test accuracies on OMNIGLOT for different parameter values for these two models. Here we only used two independent runs for each parameter value, which did not allow us to sufficiently reduce the statistical error. Despite of this, in the following, we try to highlight a few notable parameter dependencies. Note here that in some experiments with particularly large feature or model sizes, training progressed beyond the target number of steps and there could also be overfitting for very large models. Number of transformer layers. Increasing the number of transformer layers is seen to be particularly important in the 4-channel model. The 16-channel model also demonstrates the benefit of using 1 vs 2 transformer layers, but the performance appears to degrade when we use 3 transformer layers. Local feature dimension. Particularly low local feature dimension can be seen to hurt the performance in both models, while using higher local feature dimension appears to be advantageous cases except for the 32-dimensional local feature in the 4-channel model. Embedding dimension. Particularly low embedding dimension of 16 can be seen to hurt the performance of both models. Number of transformer heads. Increasing the number of transformer heads leads to performance degradation in the 16-channel model, but does not have a pronounced effect in the 4-channel model. Shared feature dimensions. Removing the shared feature, or using an 8-dimensional feature can be seen to hurt the performance in both cases of the 4- and 16-channel models. Transformer architecture. While the majority of our experiments were conducted with a sequence of transformer encoder layers, we also experimented with an alternative weight generation approach, where both encoder and decoder transformer layers were employed (see Fig. 4). Our experiments with both architectures suggest that the role of the decoder is pronounced, but very different in two models: in the 16-channel model, the presence of the decoder increases the model performance, while in the 4-channel model, it leads to accuracy degradation. Inner transformer embedding sizes. Varying the ν parameter for different components of the transformer model (key/query pair, value and inner fully-connect layer size), we quantify their importance on the model performance. Using very low ν for the value dimension hurts performance of both models. The effect of key/query and inner dimensions can be distinctly seen only in the 4-channel model, where using ν = 1 or ν = 1.5 appears to produce the best results. Weight allocation approach. Our experiments with the “spatial” weight allocation in 4- and 16-channel models showed slightly inferior performance (both accuracies dropping by about 0.2% to 0.4% in both experiments) compared to that obtained with the “output” weight allocation method. This paper is available on arxiv under CC 4.0 license. Authors: (1) Andrey Zhmoginov, Google Research & {azhmogin,sandler,mxv}@google.com; (2) Mark Sandler, Google Research & {azhmogin,sandler,mxv}@google.com; (3) Max Vladymyrov, Google Research & {azhmogin,sandler,mxv}@google.com. This paper is available on arxiv under CC 4.0 license. Authors: (1) Andrey Zhmoginov, Google Research & {azhmogin,sandler,mxv}@google.com; (2) Mark Sandler, Google Research & {azhmogin,sandler,mxv}@google.com; (3) Max Vladymyrov, Google Research & {azhmogin,sandler,mxv}@google.com. Table of Links Abstract and Introduction Problem Setup and Related Work HyperTransformer Experiments Conclusion and References A Example of a Self-Attention Mechanism For Supervised Learning B Model Parameters C Additional Supervised Experiments D Dependence On Parameters and Ablation Studies E Attention Maps of Learned Transformer Models F Visualization of The Generated CNN Weights G Additional Tables and Figures Abstract and Introduction Abstract and Introduction Problem Setup and Related Work Problem Setup and Related Work HyperTransformer HyperTransformer Experiments Experiments Conclusion and References Conclusion and References A Example of a Self-Attention Mechanism For Supervised Learning A Example of a Self-Attention Mechanism For Supervised Learning B Model Parameters B Model Parameters C Additional Supervised Experiments C Additional Supervised Experiments D Dependence On Parameters and Ablation Studies D Dependence On Parameters and Ablation Studies E Attention Maps of Learned Transformer Models E Attention Maps of Learned Transformer Models F Visualization of The Generated CNN Weights F Visualization of The Generated CNN Weights G Additional Tables and Figures G Additional Tables and Figures D DEPENDENCE ON PARAMETERS AND ABLATION STUDIES Most of our parameter explorations were conducted for OMNIGLOT dataset. We chose a 16-channel model trained on a 1-shot-20-way OMNIGLOT task as an example of a model, for which just the logits layer generation was sufficient. We also chose a 4-channel model trained on a 5-shot-20-way OMNIGLOT task for the role of a model, for which generation of all convolutional layers proved to be beneficial. Figures 5 and 6 show comparison of training and test accuracies on OMNIGLOT for different parameter values for these two models. Here we only used two independent runs for each parameter value, which did not allow us to sufficiently reduce the statistical error. Despite of this, in the following, we try to highlight a few notable parameter dependencies. Note here that in some experiments with particularly large feature or model sizes, training progressed beyond the target number of steps and there could also be overfitting for very large models. Number of transformer layers. Increasing the number of transformer layers is seen to be particularly important in the 4-channel model. The 16-channel model also demonstrates the benefit of using 1 vs 2 transformer layers, but the performance appears to degrade when we use 3 transformer layers. Number of transformer layers. Local feature dimension. Particularly low local feature dimension can be seen to hurt the performance in both models, while using higher local feature dimension appears to be advantageous cases except for the 32-dimensional local feature in the 4-channel model. Local feature dimension. Embedding dimension. Particularly low embedding dimension of 16 can be seen to hurt the performance of both models. Embedding dimension. Number of transformer heads. Increasing the number of transformer heads leads to performance degradation in the 16-channel model, but does not have a pronounced effect in the 4-channel model. Number of transformer heads. Shared feature dimensions. Removing the shared feature, or using an 8-dimensional feature can be seen to hurt the performance in both cases of the 4- and 16-channel models. Shared feature dimensions. Transformer architecture. While the majority of our experiments were conducted with a sequence of transformer encoder layers, we also experimented with an alternative weight generation approach, where both encoder and decoder transformer layers were employed (see Fig. 4). Our experiments with both architectures suggest that the role of the decoder is pronounced, but very different in two models: in the 16-channel model, the presence of the decoder increases the model performance, while in the 4-channel model, it leads to accuracy degradation. Transformer architecture. Inner transformer embedding sizes. Varying the ν parameter for different components of the transformer model (key/query pair, value and inner fully-connect layer size), we quantify their importance on the model performance. Using very low ν for the value dimension hurts performance of both models. The effect of key/query and inner dimensions can be distinctly seen only in the 4-channel model, where using ν = 1 or ν = 1.5 appears to produce the best results. Inner transformer embedding sizes. Weight allocation approach. Our experiments with the “spatial” weight allocation in 4- and 16-channel models showed slightly inferior performance (both accuracies dropping by about 0.2% to 0.4% in both experiments) compared to that obtained with the “output” weight allocation method. Weight allocation approach.

HyperTransformer: D Dependence On Parameters and Ablation Studies

HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning: Experiments

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Andrey Zhmoginov, Google Research & {azhmogin,sandler,mxv}@google.com;
(2) Mark Sandler, Google Research & {azhmogin,sandler,mxv}@google.com;
(3) Max Vladymyrov, Google Research & {azhmogin,sandler,mxv}@google.com. Table of Links Abstract and Introduction
Problem Setup and Related Work
HyperTransformer
Experiments
Conclusion and References
A Example of a Self-Attention Mechanism For Supervised Learning
B Model Parameters
C Additional Supervised Experiments
D Dependence On Parameters and Ablation Studies
E Attention Maps of Learned Transformer Models
F Visualization of The Generated CNN Weights
G Additional Tables and Figures B MODEL PARAMETERS Here we provide additional information about the model parameters used in our experiments. Image augmentations and feature extractor parameters. For OMNIGLOT dataset, we used the same image augmentations that were originally proposed in MAML. For MINIIMAGENET and TIEREDIMAGENET datasets, however, we used ImageNet-style image augmentations including horizontal image flipping, random color augmentations and random image cropping. This helped us to avoid model overfitting on the MINIIMAGENET dataset and possibly on TIEREDIMAGENET. The dimensionality d of the label encoding ξ and weight slice encoding µ was typically set to 32. Increasing d up to the maximum number of weight slices plus the number of per-episode labels, would allow the model to fully disentangle examples for different labels and different weight slices, but can also make the model train slower. Transformer parameters. Since the weight tensors of each layer are generally different, our perlayer transformers were also different. The key, query and value dimensions of the transformer were chosen to be equal to a pre-defined fraction ν of the input embedding size, which in turn was a function of the label embedding and feature dimensionality as well as the size of the weight slices. The inner dimension of the final fully-connected layer in the transformer was also chosen using the same approach. In our MINIIMAGENET and TIEREDIMAGENET experiments, ν was chosen to be 0.5 and in OMNIGLOT experiments, we used ν = 1. Each transformer typically contained 2 or 3 encoder layers and used 2 or 8 heads for OMNIGLOT and MINIIMAGENET, TIEREDIMAGENET, correspondingly. Learning schedule. In all our experiments, we used gradient descent optimizer with a learning rate in the 0.01 to 0.02 range. Our early experiments with more advanced optimizers were unstable. We used a learning rate decay schedule, in which we reduced the learning rate by a factor of 0.95 every 105 learning steps. This paper is available on arxiv under CC 4.0 license. Authors: (1) Andrey Zhmoginov, Google Research & {azhmogin,sandler,mxv}@google.com; (2) Mark Sandler, Google Research & {azhmogin,sandler,mxv}@google.com; (3) Max Vladymyrov, Google Research & {azhmogin,sandler,mxv}@google.com. This paper is available on arxiv under CC 4.0 license. Authors: (1) Andrey Zhmoginov, Google Research & {azhmogin,sandler,mxv}@google.com; (2) Mark Sandler, Google Research & {azhmogin,sandler,mxv}@google.com; (3) Max Vladymyrov, Google Research & {azhmogin,sandler,mxv}@google.com. Table of Links Abstract and Introduction Problem Setup and Related Work HyperTransformer Experiments Conclusion and References A Example of a Self-Attention Mechanism For Supervised Learning B Model Parameters C Additional Supervised Experiments D Dependence On Parameters and Ablation Studies E Attention Maps of Learned Transformer Models F Visualization of The Generated CNN Weights G Additional Tables and Figures Abstract and Introduction Abstract and Introduction Problem Setup and Related Work Problem Setup and Related Work HyperTransformer HyperTransformer Experiments Experiments Conclusion and References Conclusion and References A Example of a Self-Attention Mechanism For Supervised Learning A Example of a Self-Attention Mechanism For Supervised Learning B Model Parameters B Model Parameters C Additional Supervised Experiments C Additional Supervised Experiments D Dependence On Parameters and Ablation Studies D Dependence On Parameters and Ablation Studies E Attention Maps of Learned Transformer Models E Attention Maps of Learned Transformer Models F Visualization of The Generated CNN Weights F Visualization of The Generated CNN Weights G Additional Tables and Figures G Additional Tables and Figures B MODEL PARAMETERS Here we provide additional information about the model parameters used in our experiments. Image augmentations and feature extractor parameters. For OMNIGLOT dataset, we used the same image augmentations that were originally proposed in MAML. For MINIIMAGENET and TIEREDIMAGENET datasets, however, we used ImageNet-style image augmentations including horizontal image flipping, random color augmentations and random image cropping. This helped us to avoid model overfitting on the MINIIMAGENET dataset and possibly on TIEREDIMAGENET. Image augmentations and feature extractor parameters. The dimensionality d of the label encoding ξ and weight slice encoding µ was typically set to 32. Increasing d up to the maximum number of weight slices plus the number of per-episode labels, would allow the model to fully disentangle examples for different labels and different weight slices, but can also make the model train slower. Transformer parameters. Since the weight tensors of each layer are generally different, our perlayer transformers were also different. The key, query and value dimensions of the transformer were chosen to be equal to a pre-defined fraction ν of the input embedding size, which in turn was a function of the label embedding and feature dimensionality as well as the size of the weight slices. The inner dimension of the final fully-connected layer in the transformer was also chosen using the same approach. In our MINIIMAGENET and TIEREDIMAGENET experiments, ν was chosen to be 0.5 and in OMNIGLOT experiments, we used ν = 1. Each transformer typically contained 2 or 3 encoder layers and used 2 or 8 heads for OMNIGLOT and MINIIMAGENET, TIEREDIMAGENET, correspondingly. Transformer parameters. Learning schedule. In all our experiments, we used gradient descent optimizer with a learning rate in the 0.01 to 0.02 range. Our early experiments with more advanced optimizers were unstable. We used a learning rate decay schedule, in which we reduced the learning rate by a factor of 0.95 every 105 learning steps. Learning schedule.

HyperTransformer: B Model Parameters

Productivity has always been a ground criterion for success. And it’s extremely crucial for software engineers in such a rapidly growing informational world to be consistently focused, dedicated, and persevering. Nonetheless, we all know that being highly efficient during the whole day can be a challenge, especially when we ought to meet tight deadlines, tackle complex tasks, and reduce numerous distractions. I have over 10 years of professional experience in software development and engineering management and I suffered a multitude of productivity problems throughout my entire career. I had to swing for the fences just like you and “adapt, improvise, overcome” a number of tasks continuously expanding on my plate. So I made a decision to share my I use on a daily basis to get ahead in life and elevate my productivity. These practices successfully helped me, my mentees, and my clients a lot to get all ducks in a row. I will give you a series of examples so that you can recognize the pattern and adapt it to your own life. I truly hope that you will reap the benefits of it too! TOP 5 productivity Tips & Tricks 1. ONE Thing A game-changer methodology developed by Gary Keller and Jay Papasan - The idea is the following: - and you can achieve more significant results with less effort. . "The ONE Thing: The Surprisingly Simple Truth Behind Extraordinary Results" Focus on only ONE thing at a time When you wake up in the morning, prior to starting off your working routine ask yourself - . Not 2, 3, 4 - pick up . And as soon as you identify the one most important thing, make it your "What is my ONE Thing for today such that by doing it, everything else will be easier or unnecessary?" ONLY ONE TOP priority. When your manager at work assigns plenty of tasks on your plate, ask yourself or your manager: “ This could be fixing a critical bug, implementing a new feature, or optimizing performance, whatever it could be. By focusing on the most important task first and eliminating distractions, you can attain the greatest progress in the shortest amount of time. What’s the ONE Thing (task) for today that will make the biggest impact?”. In the beginning, it’s going to be complicated to define your ONE Thing. You may erroneously consider that the lion’s share of your tasks deserves the same amount of salience, but let’s be honest, it’s unreal to manage them all at once, so you will have to prioritize against all odds. Trust me, down the road not only you, but even your coworkers will start noticing that you’re getting more organized, your productivity grows and you become a more valuable employee in the company. I want you to learn here: TWO MORE THINGS Ensure to eliminate any possible distractions while working on your task: 1) NO DISTRACTIONS. Turn off notifications on your phone; Mute unimportant chats; Close unnecessary tabs in your browser; Hold off background conversations; Find a quiet workspace. The more you stay focused, the more effective you are during the day. Ever wondered how interrupted workflow may cause your schedule? Check out this diagram: Remember! Yeah, yeah - don’t miss breaks! Sitting for hours on a single task can be mentally and physically draining. I even occasionally combine my ONE Thing with the : 25 mins of focused work followed by a 10 mins break to drink a coffee, take a walk, read emails and chats, answer missed calls, etc. Short breaks will help you stay refreshed and energized. 2) TAKE BREAKS. Pomodoro technique 2. Consequences over Priorities Consequences and priorities are both important factors to make proper decisions and set goals. Priorities help us determine what is paramount and what we should focus on, however, if we don't consider the potential outcomes of our actions, we may unintentionally trigger many problems for ourselves and others. Let’s take a look at an example. When you have two or more tasks with the same priority on your plate, don’t rush in a hurry, just ask yourself for each of these tasks: or “What bad may happen if I don’t complete this task now?” “What will the outcomes be if I don’t tackle this task first?” And ensure that you approach these questions from various angles, including the impact on yourself, your team, your customers, your boss, and your organization as a whole. And act based on the answers. I’ve noticed that even some TOP managers forget about this straightforward principle when making decisions. Will you be fired or lose the customer if you don’t complete this task by tomorrow? How will the task negatively affect the product overall? Will it make the code less clean, readable, structured, or maintainable? If you take your time to determine the potential outcomes of your actions, you will make more informed decisions that consider the potential risks and benefits. This will ultimately help you evaluate the effectiveness of your choices, ensure that your priorities are aligned and determine whether you’re on the right way. One of the books that may help you delve into it is by Brian Tracy. “Master your time” 3. GTD: Getting Things Done If you want to be at the TOP of Industry Experts, you can not resist it - . This methodology is undoubtedly one of the most effective productivity systems I’ve ever seen. It was created by David Allen and introduces a unique way to manage tasks and priorities in a more efficient and organized way. It’s already helped a ton of famous people worldwide like Barack Obama, Elon Musk, Oprah Winfrey, Will Smith, Tom Cruise, Tony Robbins, etc GTD: The Art of Stree-free Productivity I’ve read this book personally around 5 times during the last 5 years and my life has changed entirely since I got accustomed to adapting it to my daily routine while working as a Software Developer, Engineering Manager, Mentor, Solutions Architect, and CTO. And I truly hope it will change your life of yours! Let’s cut to the case and see how it works. In simple terms, it’s a 5-steps workflow: 📥 CAPTURE Let’s say your boss asks you to put together a daily report, send an email, or help your team member, but you’re already on your ONE Thing. Make sure you right away put these tasks in your INBOX as soon as you have a break. Whatever comes to your head as a task - COLLECT EVERYTHING! ✏️ CLARIFY & PRIORITIZE Nothing is possible without The task is considered accomplished only if there are NO next steps to be done**.** Here you determine which tasks are on the back burner and which require imminent attention. Next Actions (NA). Clarify them, decompose them, and set the next steps. Let’s say you have a task to help your teammate on It sounds way too abstract, so I’d decompose it and transform it into somewhat like this: Example: project ABC. ABC // Me // NA #1: Learn task requirements; ABC // Me // NA #2: Call with my teammate to brainstorm and advice; ABC // Me // NA #3: Send the call summary & make agreements; ABC // Teammate // (Note: I delegate it and ask my teammate to ping me when he moves forward to ensure he’s on the right track) NA #4: Write me back on the progress. 📆 ORGANIZE Every task must have a and due date assignee. Ask yourself: “Am I sure that I have to work on this task myself? Can I delegate it? When should it be delivered? What outcomes are expected from me?” If you don’t set specific due dates and assignees, sooner or later you will stumble into continuously missing deadlines and be wondering how come your boss, your team lead or your client is disappointed about your work. Their expectations may not just match yours. Ensure you're the right person for the task and affirm the deadlines with your boss, lead, or client (ideally on paper, not in words). Let’s see an example of when you need to help your teammate: Learn my teammate’s task requirements // ABC // Me //  (20 mins) today 5 pm Call with my teammate to brainstorm & advice // ABC // Me // (30 mins) tmrw 2 pm Send the call summary & make agreements // ABC // Me // (15 mins) tmrw 6 pm Write me back on the progress // ABC // Teammate // in two days 4 pm Send it over to your manager to confirm and start working on it without stress 🤝. It will let you ensure that everyone is on the same page and there are no misunderstandings between you and your leaders. 🔎 REVIEW As you work on your tasks, things may change, priorities may shift, or new tasks may come up. So get used to frequently reviewing and revising your tasks. Do smaller daily reviews and bigger weekly ones. It will guarantee that everything is still relevant and up-to-speed. Here you also ensure that your ONE Thing is correctly set for the next day, upcoming week, month, etc. This is how I do it (same as / tasks): monthly yearly When I go to bed, I review all my tasks for the next day and ensure that they are still relevant and organize them in proper order, polish deadlines, rearrange some to other days, add new assignees, and set the next steps. At last, I define my ONE Thing for the day. Daily: On Sunday I allocate around one hour to review my tasks for the upcoming week and do the same as I’ve done on the daily review. Weekly: 🚀 ENGAGE That’s it! Start doing your work! 🛠️ TOOLS What can help you adapt this GTD methodology? tools Here are TOP-3 of my favorite ones: 🏆 Todoist 🥈 OmniFocus 🥉 Things After using tens of productivity apps I’ve finally settled on because of its most flexible features, intuitive user interface, cross-platform support, and ability to completely align with the GTD methodology. LMK if you want me to create a separate article for you to learn more about how to effectively use it in your day-to-day life. I’ll be elated to share my own 4 years of practice with the app Todoist Todoist 4. Important vs Urgent Probably many of you heard of the ** **that lets you avoid the urgency trap. I beg to differ you’ve come across a situation where you receive an email in your inbox that starts with the words - or – and you drop all your other tasks to handle that email right away since it looks extremely urgent, right? If you do so, you’ve fallen into the urgency trap! switch your focus to something else, drink a glass of water to bypass the emotions, peruse the email again, and ask yourself: and react based on the steps below. Eisenhower Matrix URGENT, NOW, ASAP STOP 🛑 for a moment, “Is it really that urgent and important?” Create a and as follows: 2x2 grid label the quadrants and - DO IT! Your ONE Thing and your first focus. URGENT IMPORTANT , but - No clear deadlines? Schedule and push back. NOT Urgent Important but - Urgent, but goes against your ONE Thing? Delegate! Urgent, NOT Important and - Any distractions or unnecessary tasks? It’s your back burner! NOT Urgent NOT Important If you always focus on what's urgent but not important, you're more likely to feel stressed, overwhelmed, and burnt out. Categorizing tasks according to their level of urgency and importance will allow you to focus on the tasks that have the highest priority and will have the most significant impact on your productivity. You will notice how you set about investing your time and energy wisely. 5. S.M.A.R.T. A methodology is a prevalent life hack for setting your goals and completing your tasks on time. As a software developer, setting your daily, weekly, or even longer tasks based on this methodology can help you achieve your goals more effectively. Let’s see how it works! S.M.A.R.T. Specific Your task has to be specific and clearly define what you need to do. I want to learn React (way too abstract) ❌ Bad Example: ✅ Good Example: I will enroll in and pass an online course on React on Udemy.com by this month; I will learn deeply official React docs by the next month; I will create a pet project to hone in on my React skills by the summer. Measurable The task should allow you to track your progress I want to increase my KPI at work. ❌ Bad Example: I will inculcate the GTD and perform my tasks at work twice faster (or by 30%) by the next quarter. ✅ Good Example: Attainable Your task needs to be realistic and easily achievable I want to learn AWS. ❌ Bad Example: I will dedicate 1.5 hours each day to passing AWS online course and practicing it in my pet project so that I can be certified as an AWS Associate Developer by the end of this year. ✅ Good Example: Relevant Your task needs to corelate with your priorities, values, dreams, and ambitions. I want to enroll in an online course on Python, so I will practice Java first to learn the ropes of backend development. ❌ Bad Example: I want to enroll in an online course on Python, so I will find a relevant Python online course on Udemy.com for beginners and find a Senior Python Developer as a Mentor to track my progress. ✅ Good Example: Time-Bound Your task needs to have a due date. Do NOT ever start a task without a deadline on it. I need to fix the bug ASAP ❌ Bad Example: I will fix the bug by Wednesday, validate by Friday, and deploy the fix by Monday. ✅ Good Example: Conclusion By setting clear goals, minimizing distractions, taking breaks, using the right tools, and collaborating effectively, you can stay on top of your work and be more efficient to deliver high-quality software projects. Don’t wait for the right time to start - it’s a losing strategy. If you feel like it’s hard to kick off something - try to set about small steps and gradually ramp up. It’s essential to note that every individual is unique and what works for me may not ideally work for you. Therefore, in order to elevate your productivity as a Software Engineer you need to experiment with various techniques including the ones listed in this article, and find those that best suit your personality and abilities. Don’t forget that productivity is not about working harder, but about working smarter. I hope my expertise will help you be at least more focused, organized, and motivated. Don’t hesitate to drop me a line by email - and I will pull out all the stops to help you identify suitable practices and tools for boosting your productivity so you can be proud of your own achievements! andrew.maksimchenko@gmail.com

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The modular design of the Cosmos SDK is one of its most powerful features. As the SDK upgrades and improves, exciting new features are introduced to the Cosmos stack as modules, similar to how the was improved with amazing functionality over time. International Space Station Blockchains in the Cosmos ecosystem and their end users are excited to adopt new upgrades to the SDK, but at times aren’t fully aware of the huge benefits some of these modules can provide. In light of that, we’d like to highlight two highly powerful modules that were part of the release last year: & . v0.43 Authz Fee Grant Cosmos SDK Authz Module Short for , allows you to an address to perform a specific action on your behalf. Authorization Authz authorize Imagine you have a wallet with a lot of funds stored on it but there are regular transactions you might need to perform, like voting on governance proposals or claiming your staking rewards. You might get a bit annoyed each time you have to connect your Ledger or try to access your wallet in cold storage and, understandably so, you’d prefer to just use a browser wallet like Keplr whenever possible. With Authz, you can authorize a different address to perform these specific transactions for you, without worrying that this address will be able to take any other actions with your funds. This effectively allows you to perform your regular activities without worrying about compromising your valuable wallet. App developers can also create their own custom authorization types for their own SDK modules. You are welcome to read the full technical specification . here Cosmos SDK Fee Grant Module In many ways, the module can be seen as a companion to Authz. This module enables users to other people an allowance to be used to pay for gas fees, without actually transferring any tokens to the other address. The beauty here lies in the fact that the funds remain in control of the user who created the allowance. Fee Grant grant Imagine you are building the next best NFT marketplace using the Cosmos SDK. You might be worried about user adoption knowing people will have to buy your token on an exchange just to pay gas fees on the platform — a significant barrier to entry for new blockchain users though generally fine for users who have already been onboarded to the ecosystem. With the Fee Grant module, you can create an allowance for new users so that they can start using your application without worrying about gas, streamlining the onboarding to your dApp. It’s a much better alternative than directly sending tokens to new users because you don’t have to worry about tokens being used for anything other than gas fees, and unused tokens are never wasted. In fact, you can even find a great example of this in the wild right now! is Fee Grant to both pay for the fees of new users on their platform, and to cover the fees relayers incur when transferring tokens and data over the Inter Blockchain Protocol. Allowing them to launch their platform without actually needing their native token to be liquid and available to users just yet. OmniFlix currently using These Fee Grant allowances can be a one time grant that gets depleted or a recurring grant that refills at specified intervals. As with the Authz module, these allowances and permissions can be revoked at any time, but in the case of the Fee Grant module, they can have an expiration date too. The full technical specification of the Cosmos SDK Fee Grant module is available . here The Future of Authorizations Many Cosmos blockchains have already implemented these powerful features, including the Cosmos Hub. However, the end user friendly UI/UX tooling around them is mostly still in the works. We’re seeing great progress being made on an Authz web interface in development by (funded by the ) and we’re excited to see what other front-end developers and wallets providers come up with as they’re working hard to build the interfaces that enable everyone to use the full power of AuthZ and Fee Grant! Adoriasoft Interchain Foundation Many more use cases than the few described in this blog post do exist and we encourage you to explore all potential possibilities available to users. If you’re a builder and would like to experiment with these modules, we have some great tutorials up on the as well as a vibrant community on that is happy to answer any questions you might have! Cosmos Developer Portal Discord

What Are the Secret Powers of Authz and Fee Grant Modules?

With another incredible year behind us, many major milestones reached, and an explosion of innovation throughout the growing Cosmos ecosystem, . 2021 was an interstellar year But launching IBC and completing the Cosmos whitepaper isn’t where our story ends. We’re only at the start of this amazing journey with so many exciting plans on the horizon and plenty of developments already in the pipeline for 2022. Check out the highlights. With another incredible year behind us, many major milestones reached, and an explosion of innovation throughout the growing Cosmos ecosystem, . 2021 was an interstellar year But launching IBC and completing the Cosmos whitepaper isn’t where our story ends. We’re only at the start of this amazing journey with so many exciting plans on the horizon and plenty of developments already in the pipeline for 2022. Check out the highlights. The Cosmos Hub Will Continue to Grow There are many new features coming to the Cosmos Hub in 2022, with a major upgrade planned at least once a quarter. If you want to dive into the technical details and get the specs for all the separate upgrades, take a look at the on GitHub. If you want a birds-eye view, find the big stuff below — and why it matters to you. Cosmos Hub Roadmap 2.0 Interchain Security is currently being developed by the Interchain Foundation and . This shared security service allows Cosmos chains to effectively lease security to each other so that new chains can bootstrap their economies and validators and delegators on larger chains can earn rewards for the service. Interchain Security Informal Systems Better yet, Interchain Security will allow validators and delegators to earn rewards on multiple chains in multiple tokens just by staking ATOM on the Hub. New chains will benefit from a robust validator security set and get their tokens in front of Cosmos community members in the early stages. At the same time, Cosmos Hub stakers get early access to innovative projects and increased utility for their ATOM. Interchain Accounts Interchain Accounts will be landing on the Cosmos Hub with the completion of the Theta upgrade expected in Q1 2022. Interchain Accounts have several major implications for the Cosmos ecosystem, one of which is the power to elevate Cosmos DeFi to the next level. This is because Interchain Accounts allow ecosystem chains to securely control accounts on other ecosystem chains, rather than simply transferring tokens from one chain to another. Consider Ethereum for a moment. Complex financial instruments are traded permissionless-ly over a set of smart contracts, which each handle a part of an overall business process. In the Cosmos ecosystem, smart contracts don’t have immediate access to each other because each smart contract, or application, is essentially a blockchain itself. With IBC, you can move tokens between networks, but you don’t have the ability to trigger an action on another chain as you do with smart contracts on Ethereum. Interchain Accounts change all that by providing the composability and interoperability that smart contracts need to create a DeFi explosion within application-specific blockchains! Interchain Accounts will also make connecting with IBC easier for developers as new chains can leverage the functionalities and capabilities of existing accounts, rather than having to recreate these functionalities from scratch. You can read more about how . Interchain Accounts change everything here Liquid Staking The first version of Liquid Staking spearheaded by core Cosmos contributor and founder Zaki Manian is coming as early as February 2022 and is directly integrated into the Cosmos SDK. Iqulsion Version one of Liquid Staking will allow ATOM holders to send transactions that immediately convert their bonded ATOM into transferrable representations that can be used in liquidity pools and other activities. This opens up a realm of DeFi possibilities, allowing holders to maximize their ATOM while still earning staking rewards. In V1 of Liquid Staking, the fluid tokens are bonded to the validator that the delegator stakes their ATOM with. However, this design can be restrictive and is not necessarily ideal. That’s why V2 of Liquid Staking is following quickly. The P2P team behind has that will make Liquid Staking a huge part of the Cosmos Hub. As one of Cosmos’ oldest validators, P2P developed the Liquid Staking solution for Ethereum 2.0 that allows people to stake their ether but use it at the same time. Lido now has 90% of all staked ether in ETH 2.0 and also runs Terra’s popular Liquid Staking implementation bLUNA. Lido drafted a proposal Liquid Staking is hard to achieve without smart contracts, so the Cosmos Hub team will add CosmWasm to the Cosmos Hub, allowing Lido to create the smart contracts needed for this feature. In the future, having CosmWasm on the Hub could allow it to connect to any chain, and manage their staking procedures through the IBC communication. This would place the Cosmos Hub directly at the core of the Interchain and increase its usability in line with its values and strengths, as a in the Cosmos ecosystem. Watch this space for more details. true port city IBC Will Become an Ecosystem of “200 Chains” 2021 was the year in which with major Cosmos chains forming a thriving interconnected economy — and there’s way more coming next year! IBC came to market In 2022, IBC adoption will really excel thanks to Cosmos’ powerful tech stack and developer-friendly blockchain frameworks like with IBC interoperability baked in. As Tendermint CEO Peng Zhong told , “I think we will easily see 200 chains connected via IBC by this time next year and, in the long term, even a million.” Starport CryptoSlate We’ll also see the completed work of various different teams using IBC to bridge Cosmos to their ecosystems. In 2022, that means secure connections to Bitcoin, Celo, Polkadot, Kusama, Harmony, Hyperledger Besu, Hyperledger Fabric, and even more. The free flow of assets between these major blockchains will create vast opportunities for scalability and growth — and finally, a level DeFi playing field with low fees, high throughput, and a vast selection of products! Cosmos DeFi Will Explode With more fluidity in IBC connections, the ability to manage complex transactions across blockchain accounts, and bridges to major ecosystems unlocking liquidity, Cosmos DeFi will explode. The is coming up in Spring 2022 and will bring many hotly-anticipated features including advanced capabilities for portfolio visualization, digital asset management, and service discovery. public launch of Emeris There will also be staking with auto-compounding of rewards to maximize rewards generation, cross-chain DEX aggregation, an airdrop tracker, and a browser extension that works seamlessly with the Emeris web dashboard. will also be releasing its version of Liquid Staking, called Superfluid Staking, in the coming months. Osmosis This will allow OSMO holders to use their tokens for staking and liquidity providing at the same time as well as ensuring that the protocol’s governance serves the interests of liquidity providers. Find out more about this new feature by watching charismatic Osmosis cofounder Sunny Aggarwal’s Cosmoverse presentation below. Another team making giant strides in DeFi and working hard to bring Ethereum to Cosmos is , “EVM-on-Cosmos,” (previously known as Ethermint). Evmos aims to be the EVM hub of Cosmos, making it easy for EVM smart contracts to deploy and communicate within the Cosmos ecosystem. Evmos Already in , EVM compatibility will land in Cosmos in January 2022. Evmos comes as an application-agnostic chain that’s interoperable with the Ethereum mainnet, EVM-compatible environments, and other BFT chains via IBC, and will serve as the EVM hub for any other EVM Cosmos chains. incentivized testnet Also be sure to keep a watch out for in 2022, the first DeFi protocol to offer infrastructure for cross-chain interactions. Umee raised in seed funding in 2021 backed by Tendermint, Coinbase Ventures, Jo Lubin of ConsenSys, and other large names in the industry. Umee $6.3 million Umee allows users to create lending and borrowing positions, discover yield opportunities, and explore DeFi applications trustlessly cross-chain. It’s going to be wild watching how quickly Cosmos DeFi comes into its own next year! NFTs Will Be Huge on Cosmos Beyond the rapidly growing DeFi sector, 2021 was also the year of the NFT with an explosion of interest around digital artwork, digital collectibles, and immutable digital proof of ownership. With such an appetite for NFTs among the mainstream, their popularity looks set to continue in 2022. Many projects in the Cosmos ecosystem have been laying the foundations for their launches this year, including , a public protocol for NFTs, , an interoperable system for brands and creators to build products with NFTs, , the first music NFT marketplace, , a decentralized media and network layer powered by NFTs, and , a full-stack platform and marketplace supporting Secret NFTs. Evmos will also soon support NFT deployment and host marketplaces for people to easily trade and deploy NFTs. Stargaze Pylons BitSong Omniflix Secret Network’s Stashh A special mention has to go to for releasing the first virtual town of its adventure game in 2021 complete with quests, social activities, competitive battles, and the ability to mint NFT characters, goods, and tokens! The game will be developed in increments and we look forward to future exciting releases in 2022. Strangeclan Long-time Cosmos contributor also completed trailblazing work in the NFT field in 2021, successfully conducting the in both the permissioned environment and public chain domain: WenChang Chain and IRITA Hub in BSN, IRIS Hub (aka IRISnet), and Ethereum. Now, NFTs that are the digital twins of two fine art Chinese paintings are available on OpenSea EASTIP for global markets. IRISnet first interchain NFT transfer across four blockchains We’re excited to follow the progress of all these incredible NFT projects over the coming months and will be updating you as and when they happen. More Important Airdrops in 2022 Finally, be sure not to miss out on the slew of amazing airdrops coming up in 2022. Some of the most innovative projects in the Cosmos ecosystem will be coming to production next year covering diverse areas from NFTs to decentralized social media, DeFi to gaming. Keep your eyes peeled for airdrops from , , , , , , , and Cyber, and be sure to stake your ATOM with Cosmos validators to be eligible. Evmos Umee Gravity Bridge LikeCoin Game Stargaze BitSong The Developer Community Will Continue Expanding Helping us reach our goal of 200 blockchains connected with IBC by the end of 2022 will be , the all-in-one platform to build, launch, and maintain any crypto application on a sovereign and secured blockchain with the Cosmos SDK. Starport provides the best developer experience in the industry and empowers developers to build blockchains for a multi-chain future. Starport The Starport developer community is growing quickly with created and pushed to GitHub so far. This year alone, some of Cosmos’ most interesting projects were created using Starport, including , , , , and . 422 blockchains SifChain Juno Osmosis Umee Lum Network In just two months, the group has grown into an active community of almost 600 developers. The newly-launched has reached 5,000 followers, and around 200 developers a day visit for instructions and tutorials — these are all numbers that will grow exponentially in 2022. Starport Discord Starport Twitter Starport documentation During , we received some extremely high-quality submissions for the Starport challenges and we’re looking forward to incorporating these ideas into production as well as collaborating with more open source contributors. HackAtom VI Starport will be adding some key new products and features in 2022 that will allow developers to achieve maximum success when launching their blockchains. You’ll be hearing more about this in the coming months! And Finally… We’re looking forward to another Cosmic year for our ecosystem and we thank you all for being a part of it. Let’s make 2022 our biggest year yet!

Check Out Some Cool Cosmos Projects in 2022

In today's digital world, it's easier than ever to get distracted by the many features of our mobile devices. But if you want to make the most of your valuable time, learn how to take advantage of every feature of your mobile device. The iPhone's operating system, iOS, has some great built-in features to make your phone more efficient. Still, with over 1.4 million apps available, it's challenging to know which ones are truly worth downloading. Many third-party apps out there will help you boost your productivity even further on your iOS device. To help you choose the best we've compiled our top 10 list of best that you should check out if you use an iOS device. productivity apps for iPhone, iOS productivity apps In this list of 10 productivity apps for iOS, we'll show you the most useful apps you can use on your iPhone or iPad to help you stay focused and be more productive. So, with no further delays, let's get started. 1. Evernote Evernote is a powerful that enables users to capture and organize their thoughts, ideas, and to-do lists. The app syncs across all of your devices, so you can always access your notes, whether at your desk or on the go. productivity app Additionally, Evernote makes it easy to share notes and collaborate with others, making it an essential tool for work and school projects. Evernote is an excellent app for tracking your productivity. It helps you to organize and manage all of your information in one place, making it easy to find what you need when you need it. Evernote works across all of your devices, so you can easily access it from anywhere. 2. Workstatus is a great productivity app for iOS that can help you stay organized and on track. The app provides a simple and easy-to-use interface, and it lets you keep track of your tasks, deadlines, and progress. You can also set up notifications to help you stay on top of things. Workstatus 3. Reminders Reminders is a great for iOS that can help you keep track of tasks and to-dos. You can create reminders for yourself or others and set due dates and priorities. You can also integrate reminders with Siri and ask her to remind things hands-free. productivity app Moreover, you can also set reminders based on location. For example, if you're at work and want to be reminded about an important meeting in 2 hours, just tap remind me at a place, and Reminders will remind you when you get home. So whether you're trying to stay on top of work tasks or keep your personal life organized, Reminders can help you get it all done. 4. Asana One of our favorite productivity apps for iOS is Asana. Asana allows you to create tasks, projects, and lists and assign team members to those tasks and projects. It's a great way to track what needs to be done and who does it. The app also includes a calendar view that makes it easy to see what tasks are due on what day. And if you have an iPhone, you can use the 3D Touch feature to view task details or add a new task quickly. Asana also tracks productivity continuously to give you insights into how well your team is working. This is great if you're looking to evaluate which team members are getting things done and which ones need some help for better performance. 5. Dropbox The Dropbox app is a that allows you to access your files anywhere. The app also allows you to share files with others, making collaboration easier. This makes it an ideal productivity app for businesses and organizations. productivity app Both individuals and groups can use it as a productivity tool. It's one of those apps that just works, so there's no need to worry about whether it will do what you need it to do when you need it done. It's easy to use, reliable, and cheap (free). In addition, users can also save their work directly into their Dropbox account, so they don't have to worry about losing their files if something happens to their system. Dropbox is a handy tool that can make you more productive and allow you to access all of your files, regardless of where you are. 6. Trello Trello is a fantastic productivity app for iOS that allows you to manage your projects, tasks, and to-do lists in one place. It's simple and easy to use but also extremely powerful and customizable. You can easily add, edit, and remove items from your boards and move them to different columns or lists. Trello is an excellent productivity tool that can help you organize your life and get things done. It's a great app to use if you're working on multiple projects at once, as it allows you to break down each project into its list, with separate lists for tasks, checklists, and labels. You can easily add due dates or reminders to items on your lists to stay top of mind until you complete them. With all of these features combined, Trello makes it easy to manage even large projects. 7. Spark Spark is a great productivity app because it allows you to access your calendar, contacts, and email all in one place. This will enable you to check your schedule quickly, send emails, and read the vital information often sent to your email. The best thing about Spark is that it's completely free! This makes it an excellent choice if you are looking for a good productivity app without paying extra money. Also, you have access to many of Spark's features even if you don't have an email account through them, making it great for those who don't want to use their work emails on their devices. 8. OmniFocus An app that helps you focus on what's important to you. With OmniFocus, you can capture everything that matters and see it clearly to make better decisions and take action in your life. It's a great solution to help you get more done and feel more organized at home or work. Whether simply remembering a grocery list, planning a vacation, or finishing a project at work, OmniFocus will help you track your tasks with ease and give you peace of mind. OmniFocus is available on iPhone, iPad, and Mac. It's a universal app that works seamlessly across all of your devices. So you can start a task on your iPhone and finish it on your iPad or Mac. With iCloud, everything is always up to date and available everywhere you need it. And with syncing between devices, you never have to worry about losing track of what's important to you. 9. Things 3 If you have an iPhone and want to get more done in less time, Things 3 is a must-have. This productivity app helps you get organized by giving you multiple ways to keep track of your tasks. From setting reminders that pop up on your screen to creating recurring tasks that sync across all your devices, Things 3 has everything you need to stay top of your work. Moreover, you can easily sync your tasks with other apps such as Dropbox, Evernote, and Google Drive. This way, you can access your tasks from any device. It's one of our favorite and iPad, making it to our list of top productivity apps for iPhone iPhone productivity apps. 10. Hive Hive does an excellent job at keeping all of your most important team files and documents organized and in one place. It syncs with iCloud, Google Drive, Dropbox, Box, etc. You can invite anyone to a Hive to work on files together or leave notes on documents. The app has a simple interface that includes task lists and calendar views and a picture-based folder organization that makes it easy to find what you're looking for. Hive tracks the productivity of each member of your team and will notify you of any activity that's been taking place. It also has a feature called Hive Mind that lets you see what other members are working on at any given time. This makes it easy to coordinate with others so that everyone is always up-to-date. Hive is worth checking out if you need an all-in-one tool to enhance productivity and organize your team's documents and files. Conclusion Overall, the help you efficiently manage your tasks and schedule. There are many options available to choose from in this day and age. best iPhone productivity apps However, the apps mentioned above are some of the best. They each offer unique features that can significantly affect your productivity levels. These are just a few of our favorite . We hope you enjoyed reading about them and maybe even found one or two that you want to try out. Let us know how they work out for you in the comments section below! iPhone productivity apps Also, don't forget to share this post with your friends and family. We will catch you in another post soon. Till then, stay connected. Thank You !!

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OMNIFLO

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