
Haystack Analytics
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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.
We all know that expectations for chatbots are high, but most of the time theyโre just not up to the job. Amazing technologies built by humans constantly fail to deliver real value, and thatโs something that we want to fix. With Activechat, your smart AI business assistant is ready in minutes and keeps improving forever. Just extract data from existing conversation logs with โInsightsโ and automate your natural language assistant skills with โIntentsโ.
Our mission is to put the power of conversational AI into the hands of customer service leaders all over the world. We do this so that customer service teams could harness the power of machine learning to solve their day-to-day tasks and improve their routines.
Haystack Analytics
ActiveChat.aiHaystack Analytics's answer
Engineering Leaders and Managers
This has been my #1 choice for building chatbot. The visual builder is great and very convenient.
I am new to bots and have no development background. I have found Activechat to in the top 3 UI's, it is easy to use, inuitive and has a strong community.
You can easily build simple directional and AI bots. I was able to build complex bots using Active Chat. I used it to capture leads, respond to common questions, loyalty programs and integrate directly to Google Sheet. There's still room for improvements but overall this is currently the best chatbot builder by far!!! Thanks to Andrii, Roman K. and the rest of Active Chat team.
Based on our record, Haystack Analytics seems to be more popular. It has been mentiond 2 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
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