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Ground its answers

Link answers back to their sources

Let readers move from an agent's response back to the organization material that informed it.

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Captured from the product Demo workspace
Show citations for the source passages supplied or returned with the turn.

What this changes for your team.

When knowledge is injected or retrieved, Yekar.AI carries source and passage identifiers into the response record so the interface can display citations. A citation names the passage the turn actually had in front of it, so a reader can open the source and check the reading for themselves.

How it works in practice.

  1. 01

    Retrieve or inject passages with their source metadata attached.

  2. 02

    Ask the model to associate supported statements with the available evidence references.

  3. 03

    Render citation links that reopen the corresponding source passage for review.

What you can plan around.

The behaviour you can design against, stated concretely.

Knowledge chunks retain provenance back to an organization article or file.

Grounding metadata distinguishes knowledge evidence from tool-only or unsourced output.

Citations are limited to evidence present in the turn; they are not fabricated for general-knowledge fallback.

Complete the operating path

View all capabilities
Ground its answersChoose what happens beyond the corpus

Trade coverage for grounding explicitly instead of leaving fallback behavior ambiguous.

Ground its answersKeep answers grounded as knowledge grows

Let Yekar.AI adapt retrieval automatically as the selected knowledge grows.

Build the agentBuild agents with AI

Turn a working brief into a reviewable agent draft without starting from a blank setup.

Bring one real process

See how Yekar.AI fits the way you work.

Start with a job your team already owns, plus the tools and decisions around it.

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