Haystack Analytics
LinearB
GitPrime
Waydev
Swarmia
CodeClimate
Athenian
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FPDS Query
GovWin IQ
EZGovOpps Market Intelligence
Govini
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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.
FPDS Query is a federal procurement intelligence platform for contractors, consultants, analysts, and business development teams that need faster access to public U.S. government contracting data.
The platform helps users analyze FPDS contract awards, SAM.gov opportunities, contractor records, GSA contract data, subcontract awards, assistance subawards, and exclusion records in one searchable environment.
FPDS Query can be used to identify agencies buying specific products or services, research incumbent contractors, analyze competitors, review NAICS and PSC market activity, track historical award patterns, connect active SAM.gov opportunities to past federal buying behavior, and support bid/no-bid research.
Typical use cases include federal market research, capture planning, competitor analysis, agency spending analysis, opportunity discovery, incumbent research, GSA contract research, and public procurement data analysis.
Haystack Analytics
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Haystack Analytics's answer
Engineering Leaders and Managers
FPDS Query's answer:
The primary audience includes federal contractors, GovCon consultants, business development teams, capture managers, proposal teams, market researchers, procurement analysts, and small businesses entering the U.S. government contracting market.
FPDS Query is especially useful for users who need to research agencies, competitors, incumbents, NAICS/PSC markets, and federal opportunity signals before making bid/no-bid decisions.
FPDS Query's answer:
FPDS Query is built as a web-based SaaS platform using Laravel, PHP, JavaScript, ClickHouse, SQL, and AI-assisted query workflows.
The platform uses ClickHouse for large-scale federal procurement data analysis and provides a searchable interface for working with FPDS, SAM.gov, GSA, subcontract, assistance, and exclusion datasets.
FPDS Query's answer:
FPDS Query is currently used by early users, independent researchers, small business contractors, and GovCon professionals.
Public customer names are not listed at this time.
FPDS Query's answer:
FPDS Query combines multiple public federal procurement datasets in one searchable environment, including FPDS awards, SAM.gov opportunities, contractor records, GSA contract data, subcontract awards, assistance subawards, and exclusion records.
Instead of checking separate government portals manually, users can analyze agency spending, vendors, incumbents, NAICS/PSC markets, recent awards, and opportunity history from one platform.
FPDS Query's answer:
FPDS Query is built for fast, practical federal procurement research. It helps users move from public raw data to direct market intelligence questions, such as which agencies buy a service, which vendors are active, who may be the incumbent, and how current opportunities connect to historical award activity.
It is useful for contractors, consultants, capture teams, analysts, and small businesses that need procurement data without manually searching multiple federal systems.
FPDS Query's answer:
FPDS Query was created by GETWAB INC. to make public U.S. federal procurement data easier to use for real market research.
Federal procurement data is public, but it is often fragmented across multiple systems and difficult to analyze at scale. FPDS Query was built to connect awards, opportunities, contractor records, GSA contracts, subcontract data, assistance data, and exclusions into a single research environment.
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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