Planned

Research.

Measure trustworthiness of AI research output, not recall.

Research measures whether AI research agents produce findings you can actually trust. It ingests query-and-answer pairs, source citations, and human reviewer flags to score citation accuracy, source coverage, and factual reliability.

96% verified
Findingcited
Revenue grew 24% YoY, led by enterprise.
[1]10-K 2024, p.45
[2]Q3 earnings call
[3]Press release, Mar
$7.40 / finding
How it works

Ingest, measure, trust.

01
Ingest

Feed in query-answer pairs, source citations, and reviewer flags.

02
Measure

Score citation accuracy, source coverage, and factual error rate.

03
Trust

Ship only the findings that clear the trust bar.

The measurements

What it measures.

01
Citation accuracy

Cited sources that genuinely support the claim, verified against fetched content.

02
Source coverage

Independent sources per claim. Avoid single-point-of-truth findings.

03
Factual error rate

Flagged hallucinations, wrong dates, wrong numbers. Negative weight on the score.

04
Recency scoring

How fresh the cited sources are vs the topic timeline.

05
Depth score

Did the agent go beyond the first page of search results.

06
Cost per validated finding

Token spend divided by human-validated findings.

Who it's for

Who reaches for Research.

  • ·Research operations leaders
  • ·Consulting firms
  • ·Market intelligence teams
Same suite

Pairs with the rest of Observe.

Want Research in your stack?

We're onboarding design partners now. Join the waitlist to be in the Research cohort.

Just email is required. One email when Research goes live. Nothing else.