Answer observations
Record what an approved prompt returned, when it was observed, and which method produced it.
Cirv Sight · Product direction · Founding cohort
Make AI-answer evidence inspectable.
Cirv Sight is a proposed evidence workspace for recording what an AI-answer system returned, what supports the observation, what is missing, and what can be checked next.
Discuss the founding cohort Workspace is not publicly open
Current statusProduct direction and founding-cohort conversations. There is no public app or self-serve access.
Evidence model · Four explicit record classes
Evidence stays attached to the claim.
The model is designed to keep an observation, its support, its authorization, and its limitations distinct enough to inspect.
Source-linked records
Keep citations, source versions, artifact hashes, and missing support attached to the claim they inform.
Verified websites
Separate authorized domains and evidence sources from sites or records that have not been verified.
Visible limitations
Leave failed, partial, unavailable, and not-observed states visible instead of inventing a score.
Proposed workflow · Four reviewable steps
From boundary to next action.
Each step produces a visible record. Nothing becomes a universal visibility score or a guaranteed commercial outcome.
- 01
Define the evidence boundary
Agree the organization, domain, prompt set, locale, date window, method, and authorized source.
- 02
Capture observations
Import or record approved observations without turning missing evidence into a positive or negative result.
- 03
Inspect the ledger
Review each answer, citation, source record, state, limitation, and available correction path.
- 04
Prioritize the next action
Use the evidence record to decide what deserves verification, revision, or further observation.
Evidence boundary
What the record does not prove remains visible.
An observation is not exhaustive market coverage, a ranking guarantee, verified traffic, revenue attribution, crawler payment, or publisher payout. Failed and unavailable observations remain failed and unavailable. Every live claim still depends on an approved method, authorized source, and reviewable evidence.
Founding cohort
Help shape an evidence workspace worth trusting.
We are speaking with teams that need a clearer, inspectable record of AI-answer observations and their limits.
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