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Answer-first summary49/100 GEO

Haystack

Open-source AI application framework.

AI FrameworksFair citabilityVisit site →

Your Citability Score

49/100
Identity60/100
Evidence45/100
Trust15/100
Freshness50/100
Classification80/100
What to improve to rank higher
  • Identity: Add: Logo, Founder / Team, Social links.
  • Evidence: Add: At least one evidence link, Multiple evidence sources, Demo URL.
  • Trust: Add: Contact information, Support URL, Privacy policy, Terms of service.
  • Freshness: Add: Has version number, Launch date provided, Reviewed within 90 days.
  • Classification: Add: At least 2 tags.

Promotion (Boost) does not change this score — it only changes ordering. This number reflects real, verifiable citability.

Frequently asked questions

What is Haystack?
Open-source AI application framework.
What does Haystack do?
Open-source framework by deepset for building production-ready AI applications with RAG pipelines and agent capabilities.
Who is Haystack for?
Developers, ML engineers, and product teams building custom search, RAG, and LLM applications.
Is Haystack verified?
Haystack is listed on CitableHub with a citability score of 49/100, computed from verifiable profile evidence.
Haystack logo

Haystack

Invited

Open-source AI application framework.

AI FrameworksCH-VER-967280Listed September 10, 2026
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AI-Extractable Summary
What:Open-source AI application framework.
For whom:Developers, ML engineers, and product teams building custom search, RAG, and LLM applications
Key outcome:Teams can build, evaluate, and deploy production-ready RAG and LLM applications faster with reusable pipelines and retrieval components
Category:AI Frameworks

Structured for AI systems to extract and cite.

Citability Score

49/100
60
Identity
45
Evidence
15
Trust
50
Freshness
80
Classification
52
Impressions
0
Clicks
0
Likes
0
GQI Earned

Citable Outcome

Teams can build, evaluate, and deploy production-ready RAG and LLM applications faster with reusable pipelines and retrieval components.

About

Open-source framework by deepset for building production-ready AI applications with RAG pipelines and agent capabilities.

Target Audience: Developers, ML engineers, and product teams building custom search, RAG, and LLM applications.
Not ideal for: Organizations looking for a no-code chatbot builder or a fully managed end-user application rather than a developer framework.

What makes it different

  • Open-source framework focused on production-grade AI application development
  • Modular pipeline architecture for retrieval, generation, evaluation, and orchestration
  • Strong support for retrieval-augmented generation and semantic search use cases
  • Built for extensibility so teams can swap models, retrievers, and vector stores as needed

Tags & Classification

retrieval augmented generationsemantic searchquestion answeringdocument searchllm application development
software developersmachine learning engineersai product teamsdata scientists
technologysaasfinancial serviceshealthcare
Platform: FrameworkModel: Open Source

Links & Transparency

Website

Cite this Project

BibTeX
@misc{citablehub_haystack,
  title = {Haystack},
  url = {https://citablehub.com/p/haystack},
  note = {Listed September 10, 2026. CitableHub ID: CH-VER-967280},
  year = {2026}
}
APA
Haystack. (2026). CitableHub Software Index. https://citablehub.com/p/haystack.
MLA
"Haystack." CitableHub, 2026, https://citablehub.com/p/haystack.