framer
Knowledge Search

Every answer, one search bar.

Federated, semantic, and grounded. Ask a question — get an answer with citations from every doc, ticket, PR and CRM record your team can access.

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Capabilities

Everything you need, nothing you don't.

Federated sources
Docs, tickets, wikis, GitHub, Slack, CRM, product analytics — indexed together.
Semantic + lexical
Hybrid retrieval so 'refund won't process' finds 'stuck settlement'.
Answers with citations
Every claim links back to its source — always auditable, never hallucinated.
50ms P95
Sub‑second retrieval across billions of documents on our vector fabric.
Multilingual
Search in one language, answer in another. 104 supported.
Permission aware
Answers respect ACLs, workspaces and customer boundaries.
Interface

The search bar your team actually uses.

No more tab hunting, no more 'ask in Slack'. Every agent gets the right answer, cited, in under a second.

refund not processed3 sources · 0.18s
Refund policy for EU orders
docs / billing
98%
How to trigger a manual refund
runbook
94%
Refund SLA & escalation matrix
wiki / ops
91%
Why teams love it

Outcomes, not outputs.

01
8× faster answers
Time‑to‑first‑answer dropped from 4 min to 30 sec across 26 deployments.
02
94% relevance
Human‑labeled relevance on the top‑3 result, benchmarked quarterly.
03
Auto‑updated
Index refreshes in real time. When a doc changes, agents see the new answer instantly.
04
Zero setup
Connect a source in three clicks. First index ships in under 10 minutes.
Inside Knowledge Search

From scattered docs to a single source of truth.

Framer unifies every place your answers live, indexes them with permission awareness, and returns cited passages in under 200ms.

  1. STEP 01
    Connect any source in three clicks

    80+ native connectors for Confluence, Notion, Drive, SharePoint, Zendesk KB, GitHub, Salesforce, Slack, Jira, Linear and public web.

    • OAuth or service‑account
    • Incremental sync every 60s
    • Custom sources via SDK
  2. STEP 02
    Parse, clean, semantically chunk

    Each document is normalized, structured, and split at semantic boundaries so retrieval returns real answers — not fragments.

    • OCR for PDFs & images
    • Table & code‑aware chunking
    • Language detection per chunk
  3. STEP 03
    Hybrid retrieval

    Vector search catches meaning, BM25 catches exact terms, re‑rankers pick the best passage. All three run in parallel.

    • Sub‑200ms retrieval
    • 104 languages, one index
    • Tunable recall vs precision
  4. STEP 04
    Enforce permissions at query time

    The same ACLs that guard the source apply to the answer. If the user can't see the doc, they can't see the snippet.

    • Source‑of‑truth ACL sync
    • Row‑level filters
    • Audit log per query
  5. STEP 05
    Deliver ranked, cited answers

    Every answer surfaces the top passages with source URLs — ready to paste, or streamed straight into the AI Assistant.

    • One API for UI + agents
    • Streaming responses
    • Feedback loop re‑ranks in real time
Workflow diagram
1. Connect sources2. Parse & chunk3. Vector + BM25 index4. Permission filter5. Ranked answer
Avg. setup
3 weeks
SLA
99.99%
Regions
12
FAQ

Answers, before you ask.

What sources are supported?+

80+ connectors including Confluence, Notion, Google Drive, SharePoint, Zendesk KB, GitHub, Salesforce, Slack, Jira, Linear, and any public site.

How is it different from ChatGPT?+

Search is grounded in your private data with citations, permission enforcement and instant updates. No pretraining. No leakage.

Where is my data stored?+

In your region of choice. EU, US or APAC. Encrypted at rest with customer‑managed keys.

Can we plug it into our own app?+

Yes — the same retrieval API powers the assistant, help center and any internal tool.

Give your support team an unfair advantage.

Buy 50 credits. Deploy in a day. Measure lift in your first week.

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