Skip to main content

​
Retrieval keeps live answers current and accountable.

Callaro can retrieve knowledge during a live call so the AI answers with current, approved information rather than guessing from stale model memory.
1

Detect an information need

The runtime identifies that the current turn requires factual grounding or tenant-specific data.
2

Query the approved knowledge source

Only the configured knowledge base or allowed retrieval surfaces are queried.
3

Return a grounded response

The model uses the retrieved evidence to answer directly and concisely.
4

Log the outcome

Retrieval-backed behavior can be inspected through transcript and trace data for QA and continuous improvement.

​
Knowledge quality checklist

  • Keep sources scoped by tenant/domain and publish state.
  • Remove stale or duplicate documents that compete for the same intent.
  • Include versioned process documents for policy-sensitive answers.
  • Audit retrieval-backed transcripts to identify missing knowledge coverage.
Do not give the runtime unrestricted access to large, noisy document sets. Retrieval quality depends on disciplined knowledge curation and publication review.