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Icreon

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According to market research firm , the impact of COVID-19 (coronavirus) on industries around the world continues to climb everyday. With coronavirus cases spreading rapidly in Germany and Italy, pressure is growing for a broader response in the country’s IT & tech and business industry. IBISWorld The report by suggests that around 69% cross-border purchases come from within Europe to Germany. Over 55% of shoppers from another country don’t feel comfortable shopping on a foreign e-commerce website that is not in Germany. EcommerceWiki Germany is a very strong market for e-commerce startups. Check the retail e-commerce sales stats in Germany for the period of 2017 to 2023. So, If you’re planning for a business expansion in the e-commerce market, you should definitely take the Germany market into consideration. Are you also looking to design a new web application for retailing? Are you planning to relaunch your existing online retail store? If the answer is yes, then to provide you with information on e-commerce companies, I've centralized the resources here. We all know that hiring a right tech partner is important for retailers because without that you can’t make your dreams true. And, when I say dreams, I mean your very first web application or web store. Although, the world of the internet is there, how you will find that one company for your development project. Maybe you will compare services of two, three or five companies. Maybe you ask your friends to refer to some good options. However, this will never give you the right choices. I have been approached by many startup owners to give them advice on the best e-commerce development firms. I give them the right advice based on the company's success metrics, growth stats, work quality, number of clients, region-wise preference, and clients reviews. This is certainly a reason they trust my advice. Here I am giving a list of e-commerce development companies for your help by taking the following parameters into consideration. Company’s performance Company’s reliability quotient Quality of professional services provided Team strength of a firm Client’s reviews & feedback The list of companies I am sharing here also have a friendly outsourcing policy, high-quality development, low cost service offering, and favorable time zone. Here is the list of companies based out in Germany. 1. Inpsyde Inpsyde is one of the best WordPress agencies to hire for e-commerce development service in Germany. Their team has project managers, concept creators, developers and designers that specializes in building high-performing websites, online web shops, and applications for retailers. Inpsyde has already been recognized many times by WordPress and WooCommerce. This is the only company to become Germany's based WordPress VIP Partner and WooExpert Gold Partner. Service Overview: Realize Enterprise CMS Solutions Custom APIs and API integrations Big Data Migration (API/CLI driven) Customized Plugin Development ERP Integration ElasticSearch UI/UX Design Blockchain Performance Optimization Code Auditing and Reviews Custom Publishing Workflows Continuous Maintenance and Longtime Partnership Min. Project Size: $10,000+ Hourly Rate: $150 - $199 / hr Team Size: 10 - 49 Founded: 2006 (15 Years of Experience in the E-commerce Development Domain) Key clients: PayPal, SAP, Bernina, Smashing Magazine, AGD, ANOUK Fashion, Eurotext, CCV Case Studies: , MarketPress Relaunch Vectorcam online shop Clutch Rating: 4.5 stars Location: Bergisch-Gladbach, Germany 2. Cocomore Cocomore is an e-commerce development agency in Germany with over 150 employees. There is no better choice than Cocomore for web and e-commerce development services in Germany.0 They are partnered with some of the internationally acclaimed organizations - Drupal Delivery, Gigya, Facelift Agency, Sitecore, and Adobe Technology (Silver Partner). They also share long-term partnerships with , , the and . They have proven their worth in the industry. Acquia contentful German Research Center for Artificial Intelligence (DFKI) Kairion Service Overview Brand Management E-Commerce development UX Design Omnichannel Data Analytics CRM Social Media Mobile app development Software development Min. Project Size: $5,000+ Hourly Rate: $50 - $99 / hr Team Size: 50-49 Founded: 2000 (20 Years of Experience in the E-commerce Development Domain) Key clients: Bärenmarke, Eurovision, HDI, Merz, Nestlé, Koelnmesse, Klöckner, Procter & Gamble, Rabobank, Tele Columbus and many more Case Studies: , Luxair Technical relaunch of the booking platform Nestlé: Creative brand showcasing Clutch Rating: 4.3 stars Location: Frankfurt, Germany 3. 711 Media 711 Media offers outstanding e-commerce development services to a variety of industry verticals and business domains. From conceptualization and business analysis, prototyping and development, to deployment of a total e-commerce solution, the 711 Media team guides customers through the complete development life cycle. Service Overview E-commerce and web development Digital Marketing Creative Production Research & Consulting Social Media Marketing Branding Search Engine Optimization Min. Project Size: $50,000+ Hourly Rate: $50 - $99 / hr Team Size: 50-249 Founded: 2002 (18 Years of Experience in the Marketing & E-commerce Development Domain) Key clients: MovenPick, OX Stay Open, Wolters Kluwer, Roto Case Studies: , , , Glass Ladder Titan Upgrades Limon Legal The Matian Firm Clutch Rating: 4.5 stars Location: Stuttgart, Germany 4. ClecoTech International A leading e-commerce development company in Germany with over 10+ years of experience in the domain. With a world-class team of software engineers they serve web application development, e-commerce development, mobile development, IoT, and Machine learning services. They have successfully delivered over 56+ projects and earned 38+ happy customers. They believe in the transformative power of technology. Service Overview Website Designing E-commerce Development Software Development Business Consulting Access to the latest technology for development Online Marketing Min. Project Size: $10,000+ Hourly Rate: < $25 / hr Team Size: 10 - 49 Founded: 2016 (5 Years of Experience in the E-commerce Development Domain) Key clients: DealHaba, Thea.Care, Sahaya4Us, Host My CV Case Studies: , Sahaya4Us Thea.Care Clutch Rating: 5 stars Location: Dusseldorf, Germany 5. Syncrasy Tech Since 2016, Syncrasy Technologies is one of the e-commerce development companies in Germany which has helped over 100+ companies digitally transform their retail businesses. Having 250 employees, they offer both onshore and offshore professional e-commerce development services and enterprise platforms. Partnered with Pimcore an open source digital experience platform for enterprises, team Syncrasy is serving startups as well as enterprises in Europe. They are specialized in e-commerce web, cloud, and web development projects. Service Overview E-commerce Development Pimcore PIM, DAM, CMS Implementation Website Development Software Development Blockchain Development Salesforce Consulting Min. Project Size: $5,000+ Hourly Rate: < $25 / hr Team Size: 49-249+ Founded: 2016 (5 Years of Experience in the E-commerce Development Domain) Key clients: M.S. Rau Antiques, Sticker You, Icreon, Vennscience Case Studies: , RevolveTech Liberty Financial Group Canada Clutch Rating: 4 stars Location: Germany, USA This is the list of e-commerce development companies that would help you choose the right one for your project. This will also help you with the growth of your current organization. If you have ever worked with any of these companies listed above, then please share your experience in the comment section or any feedback if you have.

Germany-based E-commerce Providers  For Retail Startups 

Machine learning (ML) and artificial intelligence (AI) technologies can hardly be called emerging in 2019. For the last decade, domains of all sorts have been leveraging them, and speaks to the fact. Today, ML and AI create value for organizations across Consumer Services, Automotive, Agriculture, Retail, Healthcare, and other major industries. the visualization by McKinsey Global Institute As businesses realize these technologies are a boon, the demand for machine learning consulting companies is skyrocketing, which predictably influences the supply. In such a way, today’s IT market is literally larded with ML vendors tackling projects of any scope and budget. To help you make your way through this enormous and diverse offering, we assembled a list of today’s most trustworthy vendors of machine learning consulting and development services. Our IT market analysts assessed an extensive range of companies according to the following objective criteria: Proven machine learning expertise Prior projects: size and complexity Diversity of business domains served Client references Speed and quality of customer service As a result, we got a list of 30 companies worthy of attention. For readers’ convenience, we present the vendors in descending order. 1. Itransition A recognized custom software development company, Itransition has delivered 1,500 projects over the span of its 20-year market presence. With more than 2,000 IT experts on board, the company has served 810 clients from 30 countries. Among the ML services the company provides there are data mining, natural language processing, computer vision, robotic process automation, and machine learning consulting. To deliver its ML solutions, Itransition uses such technologies as Python, R, Azure, Google Cloud, and AWS. Location: Denver, CO Established: 1998 Project budgets start at: $10,000 Key clients: Expedia, Xerox, Toyota, eBay, PayPal, Shell, adidas Other, non-ML services: custom software development, CRM consulting, ecommerce development Website: https://www.itransition.com/ 2. Tooploox EU-based Tooploox has around 100 skilled experts on board. For seven years of the company’s operation, they delivered 150+ successful projects. Tooploox is a machine learning consulting company using this technology to deliver computer and 3D vision, sensor fusion, deep learning, natural language processing, reinforcement learning, and other ML-related services. The company has expertise with other emerging technologies, such as blockchain. Location: Wrocław, Poland Established: 2012 Project budgets start at: $25,000 Key clients: CoinDesk, DTS, ING, Spire Health, Group Nine Other, non-ML services: mobile app development, product design Website: https://www.tooploox.com/ 3. Skim Technologies London-based Skim Technologies is an internationally recognized machine learning consulting company delivering a wide range of related services. The company’s data scientists offer chatbot development, custom ML model creation, and NLP engineering. Skim Technologies also delivers AI workshops as well as ML and AI consulting services. Location: London, United Kingdom Established: 2014 Project budgets start at: $10,000 Key clients: Jones Lang-Lasalle, Breast Cancer Care, Quant Insight Other, non-ML services: business intelligence consulting, custom software development Website: https://www.skimtechnologies.com/ 4. ThirdEye Data US-based ThirdEye Data has been delivering its ML development services for nine years. The company specializes in chatbot development, custom ML algorithms, and machine learning consulting. Among the data science technologies the company works with, there are Spark, TensorFlow, Caffe, and others. Location: Santa Clara, CA Established: 2010 Project budgets start at: $25,000 Key clients: Microsoft, Amazon, Nokia, Ford Direct, Getty Images, Amgen Other, non-ML services: business intelligence consulting, cloud consulting Website: https://thirdeyedata.io/ 5. Chatbots.Studio As its name implies, Chatbots.Studio is a company focusing on AI-powered chatbot development. It builds multichannel conversational platforms, automates business processes, and designs conversations. The company’s technology stack includes React, Redux, Angular 6, Node.js, Express.js, Botkit, and others. Location: Lviv, Ukraine Established: 2016 Project budgets start at: $5,000 Key clients: Visa, Unibot, Aldi, Digital Flex Other, non-ML services: custom software development Website: https://chatbots.studio/ 6. Azati Software Since 2001, Azati's experts have cooperated with 330 clients globally. Among the ML competencies of the company there are supervised and unsupervised learning, distributed computing, natural language processing, digital signal processing, and machine learning consulting. Azati’s tech toolkit includes CuDNN, Scikit Learn for Python, and Tensor Flow. The company mainly targets clients in the Insurance domain. Location: Livingston, NJ Established: 2001 Project budgets start at: $1,000 Key clients: MedPro Group, SequenceBase, Casio, Thomson Reuters Other, non-ML services: mobile app development, web development Website: https://azati.ai/ 7. Hidden Brains Since its foundation in 2003, Hidden Brains has cooperated with clients from 107 countries. The company delivers AI, ML, deep learning, and data science services. It also specializes in developing natural language processing software. Hidden Brains also delivers chatbots, including those for Facebook, Telegram, WhatsApp, and Slack. Location: Ahmedabad, India Established: 2003 Project budgets start at: $10,000 Key clients: McAfee, Raymond, Maxtor, SanDisk Other, non-ML services: mobile app development, web development Website: https://www.hiddenbrains.com/ 8. InData Labs Established in 2014, InData Labs houses 50+ data scientists, engineers, and analysts. The company develops ML algorithms and natural language processing solutions. Besides, InData Labs specializes in computer vision and predictive modeling. The company's stack includes Python, SpaCy, TensorFlow, Keras, and more proven languages and frameworks. Location: Minsk, Belarus Established: 2014 Project budgets start at: $5,000 Key clients: Captiv8, Flo Health, Wargaming Other, non-ML services: business intelligence consulting Website: https://indatalabs.com/ 9. Arcanys Since 2010, Philippines-based Arcanys has been delivering its ML and AI services to clients from all over the world. The company specializes in sentiment analysis, recommender systems, and image recognition. As one of its cooperation models, the company provides dedicated teams of highly experienced data scientists and developers. Location: Cebu City, Philippines Established: 2010 Project budgets start at: $100,000 Key clients: General Electric Korea, Enfo, Payment Logic, L’Oreal, Spinetix Other, non-ML services: custom software development, mobile app development Website: https://www.arcanys.com/ 10. MobiDev Since 2009, MobiDev’s IT experts have delivered 350+ software solutions. While headquartered in the US, the company provides its services globally. MobiDev uses the following machine learning technologies: Python, R, C++, Go, TensorFlow, ONNX, and Keras. MobiDev’s mobile ML toolkit includes Core ML, TensorFlow Lite, and Cafe2Go. On top of that, the company provides machine learning consulting. Location: Atlanta, GA Established: 2009 Project budgets start at: $10,000 Key clients: Verizon Media, Comcash, Quality Bridge, SmartTab, SMS Group Other, non-ML services: IoT development, web development Website: https://mobidev.biz 11. Spire Digital For over 20 years that Spire Digital has been providing IT services, it has cooperated with 600+ global customers. Among the ML and AI development services the company offers, there are natural language processing, supervised and unsupervised learning, and sentiment analysis. Also, Spire Digital creates chatbots for Facebook Messenger, Slack, Skype, and Cisco WebEx. Location: Denver, CO Established: 1998 Project budgets start at: Undisclosed Key clients: TomTom, Lockheed Martin, US Navy, USDA, Western Union Other, non-ML services: custom software development, mobile app development Website: https://www.spiredigital.com/ 12. Icreon New York-based Icreon is a digital innovation agency mostly targeting medium-sized businesses. The company uses AI and ML technologies to create innovative applications, platforms, and ecosystems. The company’s technological expertise in ML includes Amazon Web Services, Azure, Caffe2, Google Cloud, Keras, and more. Location: New York, NY Established: 2000 Project budgets start at: $25,000 Key clients: National Geographic Channel, FOX Movies, Harry Winston, Nokia Other, non-ML services: custom software development Website: https://www.icreon.us/ 13. Miquido For eight years, Miquido's team has successfully completed more than 100 projects, including in machine learning. The company offers solutions for AI-based personalization, predictive and behavioral analytics, and churn prediction. Miquido also develops chatbots. Recognized by Deloitte as one the fastest growing companies in Europe, Miquido also offers UI/UX design creation and mobile apps development. Location: Kraków, Poland Established: 2011 Project budgets start at: $25,000 Key clients: Skyscanner, Abbey Road Studios, HelloFresh Other, non-ML services: mobile app development, web development Website: https://www.miquido.com/ 14. Neoteriс Founded in 2005, Europe-based Neoteric offers a wide range of ML solutions, including predictive analytics, recommendation engines, NLP, robotic process automation, and machine learning consulting. The company also specializes in such AI platforms as SaaS Manager, SoapBox, AppOrchid, and RapidSOS. Location: Gdańsk, Poland Established: 2005 Project budgets start at: $10,000 Key clients: LunchBadger, Arvata, IT Trans Other, non-ML services: custom software development, web development Website: https://neoteric.eu/ 15. Unicsoft Established in 2005, Unicsoft employs more than 100 specialists in emerging technologies and software development. Within its ML tech stack, the company offers development of predictive and behavioral analytics solutions, neural networks, and recommendation engines, among other ML applications. The company also delivers consulting services, and maintenance of existing ML platforms. Location: Kiev, Ukraine Established: 2005 Project budgets start at: $5,000 Key Clients: Hoodifood, Executive Eye, GOFORIT, Intellica Group Other, non-ML services: blockchain Website: https://unicsoft.com/ 16. Abto Software With 12 years of its market presence, Abto Software’s has worked with 200+ global customers. Specializing in AI and ML, the company offers custom enterprise solutions for advanced and predictive analytics, virtual assistants, recommendation systems, and intelligent business process automation. Abto Software works with the following tools and frameworks, among others: TensorFlow, Keras, Caffe, OpenCV, and AWS. Location: New York, NY Established: 2007 Project budgets start at: Undisclosed Key clients: Just Answer, Skybow, Medikit, Up Great Other, non-ML services: web development, enterprise app modernization Website: https://www.abtosoftware.com/ 17. Accubits Technologies, Inc. US-located Accubits started in 2012 and has already cooperated with 140+ clients. The company’s ML capabilities include development of conversational and classification tools, video, image and text analytics solutions, as well as predictive analytics software. Besides, Accubits offers machine learning consulting. The company’s experts work with NumPy, PHP, Python, SpaCy, Spark, and several other platforms. Location: Vienna, VA Established: 2012 Project budgets start at: $5,000 Key сlients: Dubai Land Department, Smart Dubai, Eduvalue, Landmark Other, non-ML services: blockchain, custom software development Website: https://accubits.com/ 18. BotsCrew Established in 2016, BotsCrew is a global leader in chatbot development, delivering to mid-sized companies and startups. BotsCrew has its own enterprise chatbot platform that is ready to be customized and optimized according to customers' needs. Besides the proprietary platform, the company offers development of voice assistants and IoT bots. Location: London, United Kingdom Established: 2016 Project budgets start at: $10,000 Key clients: Ailira, IVA, ReVA, Dr. Dean Other, non-ML services: None Website: https://botscrew.com/ 19. STX Next Founded in 2005, STX Next is a custom software development company that specializes in streamlining IT solutions with AI and ML technologies. The company’s main technological advantage is in its exceptionally skilled Python developers. For 14 years on the market, STX Next has delivered over 250 successful projects. Location: Poznań, Poland Established: 2005 Project budgets start at: $25,000 Key clients: Seerene, Verve, Hogarth WW, Pixomondo, Unity Technologies Other, non-ML services: web development, custom software development Website: https://stxnext.com/ 20. Dogtown Media California-based Dogtown Media specializes in delivering mobile applications, enhanced with ML and AI technologies. Besides ML-powered mobile apps, the company provides machine learning consulting. For the last eight years, Dogtown Media has brought to life at least 200 applications. Location: Venice Beach, CA Established: 2011 Project budgets start at: $25,000 Key clients: Google, Lexus, United Nations, Citibank, Red Bull, YouTube Other, non-ML services: mobile app development, IoT development Website: https://www.dogtownmedia.com/ 21. Sigmoidal Sigmoidal is a New-York-based consultancy specializing in machine learning and data science, mostly for companies in Finance, Trading, and Pharma. The company integrates these technologies into web and mobile applications and APIs. It also offers solutions for NLP, computer vision, and predictive analytics. Location: New York, NY Established: 2016 Project budgets start at: $1,000 Key clients: Undisclosed Other, non-ML services: business intelligence consulting Website: https://sigmoidal.io/ 22. Cyber Infrastructure Established in 2003, Cyber Infrastructure is a custom software development company with 100+ clients worldwide. Its ML expertise includes development of virtual assistants and chatbots for a variety of domains. Cyber Infrastructure also provides machine learning consulting and employs Python, Java, C++, Lisp, and R as its primary ML and AI stack. Location: San Francisco, CA Established: 2003 Project budgets start at: $5,000 Key clients: Mannatech, Bell Other, non-ML services: custom software development, web development Website: https://www.cisin.com/ 23. Azilen Technologies US-headquartered Azilen Technologies has 250+ IT experts on board distributed across four offices worldwide. They employ ML technologies to deliver customer service, survey, and informational bots. On top of that, the company delivers facial recognition and predictive analytics solutions. Location: West Bloomfield, MI Established: 2009 Project budgets start at: $25,000 Key clients: Samsung, Pizza Hut, Sodexo, ICICI Bank Other, non-ML services: custom software development Website: https://www.azilen.com/ 24. Stermedia Stermedia has been delivering its ML and data science services since 2007. The company’s dedicated teams of data scientists and software architects design ML algorithms and models for extracting knowledge from big data sets. The company also provides NLP solutions and uses such technologies as TensorFlow and Keras, to name just a few. Location: Wroclaw, Poland Established: 2007 Project budgets start at: $10,000 Key Clients: Family Fabric, WorkService, ISOK Other, non-ML services: custom software development, web development Website: https://stermedia.ai/ 25. Belatrix Having five offices with 600+ professionals all around the world, Belatrix is one of the most fast-evolving machine learning consulting companies on the market today. Its machine learning experts have a proven track record of building various solutions, from predictive modeling to communication automation. Location: Mendoza, Argentina Established: 2003 Project budgets start at: $5,000 Key clients: Disney, Adobe, AOL, FIS, Chatman Financial Other, non-ML services: custom software development, mobile app development Website: https://www.belatrixsf.com/ 26. DataRoot Labs DataRoot Labs is an agency focusing on ML and AI development. It delivers full-cycle ML software development, including project evaluation, machine learning consulting, strategy development, architecture, integration, and support. Besides, DataRoot Labs helps enterprises with digital transformation with AI at the core. Location: Kiev, Ukraine Established: 2016 Project budgets start at: $5,000 Key clients: Servers.com, Everad, ABM Cloud, Cargofy Other, non-ML services: custom software development, mobile app development Website: https://datarootlabs.com/ 27. Softengi Since 1995, Softengi has completed 900+ projects for clients across six continents. The company’s ML services include chatbot engineering and NLP algorithms. For these purposes, Softengi uses R, Hadoop, and Python, among other tools. Location: Kiev, Ukraine Established: 1995 Project budgets start at: $10,000 Key clients: Boeing, Zeppelin, Enviance, OneRoof Energy Other, non-ML services: custom software development, AR/VR development, IoT development Website: http://softengi.com/ 28. Waverley With 27 years of software development experience, Waverley is a company housing 370K talented engineers. Among other services, they offer ML-centric solutions such as data clustering and unsupervised algorithms. On top of that, the company offers NLP and computer vision solutions and chatbots. To deliver ML products, Waverley’s engineers use Java, Python, Scala, and R. Location: Palo Alto, CA Established: 1992 Project budgets start at: $50,000 Key clients: Mozilla, Qualcomm, Swisscom, American Express Other, non-ML services: custom software development, mobile app development, IoT development Website: https://waverleysoftware.com/ 29. Imaginovation Founded in 2011, Imaginovation is a software development agency that has successfully completed 300+ IT projects of various complexity. As for ML and AI, the company develops recommendation and effectiveness assessment engines as well as solutions for speech and text processing automation. Location: Cary, NC Established: 2011 Project budgets start at: $10,000 Key clients: MetLife, Nestle, UNC Pembroke, Contractor Score Other, non-ML services: custom software development, mobile app development, web development Website: https://www.imaginovation.net/ 30. E2logy Established in 2005, E2logy has delivered 300+ projects to businesses of various sizes. Being a leading Amazon Web Services and Azure AI vendor, the company develops ML algorithms and chatbots. They also offer machine learning consulting. In addition to their ML services, E2Logy brings custom IoT solutions to its global customers. Location: Ahmedabad, India Established: 2005 Project budgets start at: $5,000 Key clients: McMillan Publishers, Polaris Industries, Vodafone Other, non-ML services: custom software development, web development Website: https://e2logy.com/ This was a full list of the top 30 machine learning consulting companies in 2019. If you cooperated with any of the presented vendors, please do get in touch and share your story.

Top 30 Machine Learning Consulting Companies

Top Custom Software Development Companies

Where the agora meets the blockchain. It's not a revolution with blaring trumpets; it's the quiet evolution of governance. In the timeless drama of "Antigone" (442 BCE), King Creon faces the paradox of enforcing city laws at the expense of divine mandates. A tale that underscores the need for collective wisdom in navigating the complexities of governance. Now, imagine blending this ancient wisdom with a sprinkle of cutting-edge tech magic. That's the future I sketch here—one where the agora meets the blockchain, and democracy gets a contemporary makeover. Unveiling a Modern Agora: Athenian Vibes in a Digital Forum This vision begins by reviving the spirit of Athenian direct democracy in a digital agora—a virtual gathering place. Echoing the days when citizens actively shaped their city's fate, our agora is a nod to the ancient forums, now translated into digital conversations where citizens can voice their opinions and make decisions collectively. Building Trust in the Digital Age: The Subtle Magic of Blockchain Now, here's where the tech magic quietly slips in. Behind the scenes is blockchain, a digital ledger that ensures transparency and security without much fuss. Think of it as the quiet custodian of our democratic decisions, recording each move without the drama. It's the backstage hero, keeping our democratic show tamper-proof and trustworthy. Economic Empowerment: Councils for Every Voice Shifting gears to the economic stage, we introduce worker and consumer councils for democratic economic planning—modern assemblies inspired by the Athenian ethos of direct democracy, not the liberal representative “democracies” that function more like oligarchies. These councils give individuals a seat at the economic table, where they can shape production, influence working conditions, and even have a say in product design and distribution. It's democracy at work, quite literally. AI: The Wise Sidekick in Decision-Making This vision doesn't stop at historical echoes; it embraces the future with artificial intelligence (AI). AI algorithms work behind the scenes, offering councils a helping hand in decision-making. It's not about replacing human insights but enhancing them. The councils get a digital sidekick, making informed decisions a breeze. Governance in Layers: Nested Federated Assemblies In the governance realm, we're introducing nested federated assemblies—a multilayered approach inspired by ancient Greek polis. Local autonomy meshes seamlessly with global collaboration. It's a subtle self-reflective dance of decentralized decision-making that ensures decisions are finely tuned to local needs while tackling broader societal challenges, expressing self-awareness, and placing sustainable limitations on economic growth. Equity in Action: A Classless Society in the Making Addressing societal imbalances, this vision champions balanced divisions of labor and fair compensation. Automation steps in to handle the mundane, freeing individuals to pursue more fulfilling roles. It's a quiet revolution, striving to close the wealth and power gap and reimagine societal structures without much fanfare. Education: Nurturing the Informed Citizens of Tomorrow Education becomes the cornerstone, mirroring the essence of Athenian paideia, the city, and broader society. We're fostering critical thinking, technology literacy, and civic responsibility. Citizens graduate not just with degrees but with the tools and experiences to navigate the nuanced world of self-governance and economics. It's education as an invisible superpower. A Decisive Moment for Democracy: A Nudge from Castoriadis As we stand at this crossroads, philosopher Cornelius Castoriadis offers a gentle nudge. It's a call to shift perspectives, a subtle rebellion against the dominance of the economic sphere. Castoriadis invites us to reconnect with our essential mortality, shaping a future where autonomy triumphs over barbarism. A quiet revolution in the making, on the ontological plane. In conclusion, this future society weaves together the wisdom of antiquity with a sprinkle of contemporary tech enchantment. The agora meets the blockchain, and democracy gets a fundamental, yet low-key, makeover. It's not a revolution with blaring trumpets; it's the quiet evolution of governance, where ancient ideals dance with modern possibilities. Welcome to the future—a place where democracy isn't just a system but a subtle symphony of voices shaping our collective destiny. delegat0x is a libertarian anti-capitalist R&D Engineer in the crypto space. They write about the intersections between philosophy, politics, media, alternatives to capitalism, social movements, and collective autonomy. Image produced by delegate0x using DALL-E Also published here

How Democracy Can Be Revitalized With an Ancient Twist and a Tech Upgrade: A Peek Into the Future

A SHORT CHRONICLE

The Odyssey: Book XI

The digital revolution, accompanied by the rapid growth of data and its management, has made certain technologies indispensable in application design. Elastic Search is one such critical component in the data management toolbox due to its advanced data indexing features, full-text search capabilities, and its ability to scale. Basically, Elastic is a search engine that builds upon Lucene, an library. Its architecture, which is both distributed and multi-tenant, paired with its real-time analytics, has made it useful in various applications, including those related to enterprise search, log and event data management, and anomaly detection. open-source software The capacity of to rapidly index large datasets and carry out intricate queries with minimal delay makes it a loved choice among developers worldwide. It comes particularly handy in high-load scenarios where massive volumes of data must be indexed, stored, and accessed quickly. Elastic Search The development and management of high-load applications often involve serious challenges, mostly due to the immense data volume they have to handle. These apps require robust systems that can process and deliver information with minimal latency, especially when serving multiple users at the same time. One such challenge is optimizing the app for enhanced speed and performance. Traditional databases may fall short in this aspect, as they may not handle the processing speed required for vast and complex data sets. Here's where the strength of Elastic Search shows. By providing immediate data access, it minimizes the possibility of performance delays, promising a smooth user experience even under a substantial workload. Its distributed design lends itself to horizontal scaling: as data volume grows, additional nodes can be seamlessly integrated into the cluster without hindering current operations. However, Elastic is a really effective tool, but not a silver bullet. Employing it to its full potential requires a firm understanding of its functionality, proper configuration, and continuous monitoring. Key performance metrics for Elastic Search, and how high-load applications can them Understanding important performance metrics of Elastic Search is crucial in evaluating its efficacy within a high-load environment. A key metric is Query Latency, which measures the time taken to execute a search or a request. In high-load apps, the volume of simultaneous requests can seriously influence query latency. Keeping track of this metric helps you pinpoint possible system constraints and inefficiencies. Next, we have the Indexing Rate — the speed of new data indexing. One of Elastic’s best attributes is its ability to index substantial data quantities swiftly. However, high-load applications can push this capacity to its limit, so the monitoring of the indexing rate is imperative here to ensure optimal performance. The Garbage Collection Duration metric provides insights into the time taken by the JVM to reclaim unused memory. Extended garbage collection times can mean insufficient heap memory or inefficient use of resources. As high-load applications deal with extensive data, they can significantly stress memory, affecting garbage collection times. CPU Usage is another critical indicator. Elastic Search is a resource-intensive engine, and high-load applications can increase CPU demand. High CPU usage can indicate that Elastic is working hard to index new data or process complex queries. This metric should be closely monitored to prevent hardware overuse. One more metric is Disk I/O, which provides a picture of how much data is being written to or read from the disk. High-load applications can push the Disk I/O, and an increase in this metric can indicate that Elastic Search is struggling to keep up with the data influx. Elastic Search's Cluster Health status is a quick indicator of the overall functioning of the search engine. It considers a range of factors, including whether all data is correctly replicated and if the shards are evenly distributed. High-load apps can cause issues such as data replication delays, affecting the cluster's health status. Common problems when using Elastic Search in high-load applications As compelling as Elastic Search can be for managing high-load apps, it is not without its share of challenges. Understanding them can be instrumental in optimizing the system in advance and maintaining smooth operations. Slow queries often surface as one of the most common issues when utilizing Elastic in high-load scenarios. The speed of data retrieval is vital to ensure user satisfaction and system efficiency. Slow queries may be a result of insufficient hardware, improper indexing, or complex query structures, leading to increased latency and hampering application performance. Node failure is another potential problem that can negatively impact system performance. In Elastic Search, a cluster has multiple nodes that distribute and manage data. If a node fails, due to hardware issues or network disconnections, it disrupts the data distribution and redundancy, potentially causing data loss and impacting system availability. Excessive memory usage can also be a concern with high-load applications. As data volumes surge, Elastic’s JVM heap can get overwhelmed, leading to extended garbage collection times or even OutOfMemoryErrors. These situations can disrupt the operation of Elastic Search, causing slow responses and, in severe cases, downtime. Another common challenge is the improper configuration of shards and replicas. If shards are not correctly distributed or if there are insufficient replicas, it can lead to overburdening of some nodes. This can cause latency in data retrieval and put the overall data integrity at risk. To mitigate these challenges, you need a robust monitoring and alerting system. Identifying issues early can prevent them from escalating and affecting application performance. Moreover, it is essential to optimize Elastic Search settings according to the specific needs of your application, considering factors like hardware capabilities, data characteristics, and expected query patterns. Optimization To extract maximum performance from Elastic in high-load apps, you need to optimize. There’s a range of strategies here, from tuning Elastic Search indices and refining queries to upgrading hardware configurations. Firstly, optimizing Elastic Search indices is a crucial starting point. The shard count and size can significantly impact system performance. It's necessary to maintain a balance: too few shards can lead to large, unwieldy indices, while too many can consume excessive resources. Proper index mapping, and defining the data types for your fields, also enhances the search efficiency and minimizes storage use. Next, query optimization plays a vital role in enhancing the performance of Elastic. Adopting structured queries, which are more precise, can lead to faster results. While scripting offers flexibility, it can also slow down the system; hence, you should limit its usage to when absolutely necessary. In addition, using filters over queries when applicable can help, because filters are cacheable and can provide serious speed gains. Hardware optimization is equally important for managing high-load applications. For example, you should choose the appropriate disk types: SSDs generally offer faster I/O operations than HDDs. Another aspect of hardware optimization is proper memory allocation. Usually, it’s recommended that 50% of the server's available RAM is allocated to Elastic’s heap memory, with the rest reserved for the operating system. However, heap memory should not exceed 32GB to avoid pointer compression issues in JVM. Built-in features for optimization Elastic Search offers a lot of built-in features that help you in system optimization. In managing high-load apps, they can be especially useful. One of these features pertains to cache settings. Elastic utilizes various caches to speed up operations, including the node query cache and the shard-level request cache. Correctly managing these cache settings can help you improve performance in a big way. Another inherent feature is bulk indexing. When dealing with large volumes of data, the bulk API allows for multiple operations to be executed in a single request, improving indexing speed. Elastic Search also allows the adjustment of refresh intervals — the frequency at which data written to Elastic becomes searchable. A lower interval can provide near real-time search, but it also consumes more resources. In high-load scenarios, adjusting the interval to a slightly higher value might improve overall performance. When it comes to scaling, Elastic Search offers both horizontal and vertical options. Horizontal scaling, or scaling out, involves adding more nodes to a cluster. This method helps distribute the load, manage larger data volumes, and improve system resilience. For the effective distribution of indices and shards across the nodes, Elastic uses a process called sharding. This ensures that data is spread evenly and allows parallel processing of queries, which enhances search speed. On the other hand, vertical scaling, or scaling up, involves enhancing the hardware capabilities of existing nodes. This might include upgrading the CPU, increasing memory capacity, or improving disk storage. Adjusting the heap size, a critical component of Elastic’s JVM settings is also a part of vertical scaling. Though escalating heap size allows more in-memory data processing, it's important to avoid settings it too high to prevent long garbage collection pauses or memory swapping. When properly configured, these features can boost Elastic’s performance noticeably. By combining them with horizontal and vertical scaling strategies, you can ensure Elastic Search remains an agile, responsive, and resilient system even under heavy loads. Trends and prospects optimization keeps evolving and presenting new technologies. For example, Machine Learning is more and more often applied in Elastic Search optimization. The technology can assist in predicting query patterns, allocating resources proactively, and automating the optimization of various configurations. It can identify trends and anomalies in system metrics, which gives you insights for effective decision-making. Elastic Search Another promising thing is automated performance tuning. Configuring Elastic manually can be daunting, and even more so for high-load apps. Automated performance tuning tools can make this process much easier, continually monitoring system metrics and adjusting settings to ensure optimal performance. These tools can offer real-time solutions, reducing the need for constant manual adjustments. Together, Machine Learning and auto-tuning can make running high-load apps easier, letting developers step back from tricky manual tuning and concentrate on more important tasks. Also, these technologies can make systems tougher, since they can deal with changing workloads and keep performing well even under big loads. While Elastic Search has already established itself as a vital tool for managing high-load applications, the integration of advanced technologies can expand its capabilities even further. As these technologies get better, they are set to start a new phase of managing high-load apps, marked by efficiency, adaptability, and consistent performance.

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