Haystack Analytics
LinearB
GitPrime
Waydev
Swarmia
CodeClimate
Athenian
Teamplify
AWS Personalize
Scikit-learn
machine-learning in Python
Google Cloud TPU
python-recsys
Amazon Forecast
Qubole
Microsoft Recommendations API
Haystack is a real-time delivery analytics platform designed for engineering leaders like CTOs, VPs of Engineering, Directors of Software Engineering, and Engineering Managers. Haystack provides actionable insights that enable data-driven decision-making, aligning engineering performance with business objectives. Haystack platform integrates seamlessly with essential developer tools like GitHub and JIRA, offering a comprehensive view of team productivity and delivery efficiency.
Leading companies like AngelList, Shutterstock, Schneider Electric, and many more trust Haystack to optimize their development processes. By transforming historical Git data into objective insights, we help you identify bottlenecks and visualize trends, ensuring timely project delivery and sustained business growth. Our analytics dashboard allows you to monitor critical metrics such as cycle time, making it easier to spot inefficiencies before they escalate into costly delays.
Haystack helps engineering leaders to mitigate risks and improve workflow efficiency. With a unified view of the entire delivery lifecycle, you can track KPIs, compare performance trends, and make informed decisions that drive measurable outcomes. Our platform goes beyond merely measuring productivity; it equips you with the tools to foster continuous improvement and innovation within your teams.
Designed to scale with your organization, Haystack is the competitive advantage that data-driven engineering teams need to thrive. By leveraging analytics, you can transform your engineering operations, enhance collaboration, and accelerate your path to market success. Join top companies in harnessing the power of Haystack for a more efficient and effective engineering process.
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Haystack Analytics's answer
Engineering Leaders and Managers
Based on our record, AWS Personalize should be more popular than Haystack Analytics. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Heads up: site is not loading. Ios Safari & macOS Chrome. Mixed Content: The page at 'https://usehaystack.io/' was loaded over HTTPS, but requested an insecure favicon 'http://www.usehaystack.io/favicon.ico'. This request has been blocked; the content must be served over HTTPS. - Source: Hacker News / over 5 years ago
Hey HN! I'm Julian, co-founder of Haystack (https://usehaystack.io). Weโre building one-click dashboards and alerts using Github data. While managing teams from startups to more established companies like Cloudflare, my cofounder Kan and I were constantly trying to improve our team and process. But it was pretty tough to tell if our efforts were paying off. Even tougher to tell where we could improve. We tried... - Source: Hacker News / over 5 years ago
E-commerce Personalization: Platforms analyze user behavior to recommend products, creating personalized shopping experiences. Here is a service I can recommend for recommendations Amazon Personalize. - Source: dev.to / over 1 year ago
Amazon personalize Amazonโs recommendation system is one of the best recommendation systems in existence. While Amazon hasnโt open sourced its recommendation model, you can still gain access to their algorithm by paying a nominal fee. You can tune it using your own data and use it in production. Companies like LOTTE, Discovery, etc., also use Amazon Personalize to power their recommendation system. You can find... - Source: dev.to / almost 2 years ago
Solution Using AI APIs:To address this issue, the platform integrated Amazon Personalize, an AI API from Amazon Web Services (AWS), to implement personalized recommendation features. Amazon Personalize uses machine learning algorithms to analyze user behavior and preferences, generating individualized product recommendations. The integration process involved:. - Source: dev.to / about 2 years ago
Over the past few months I've been spending a fair amount of time working on personalization, leveraging one of my new favorite AWS services - Amazon Personalize. Needless to say there is much more that goes into building and launching a personalization system than just turning on a few services and feeding in some data. In this article I'll focus on what it takes to launch a new personalization strategy, and... - Source: dev.to / almost 3 years ago
Check this out https://aws.amazon.com/personalize/. Source: over 3 years ago
LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
machine-learning in Python - Do you want to do machine learning using Python, but youโre having trouble getting started? In this post, you will complete your first machine learning project using Python.
Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.
Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.
