SAGA-AI
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01Overview

SAGA-AI audits when AI outputs overclaim.

An authenticated API that routes AI-generated claims into PASS, REVIEW, or HIGH_RISK based on whether the authority assigned to the claim is warranted by the evidence.

02The problem

Overclaiming is not the same as hallucinating.

Most AI evaluation tools focus on hallucinations, factuality, or confidence. But many risky outputs are not simply false — they are over-authorized.

A benchmark result becomes deployment safety.

A correlation becomes causation.

A model prediction becomes decision authority.

03Audit examples

The same underlying fact, three different epistemic statuses.

Input claim
"A model that scores 92% on a held-out benchmark has demonstrated performance on that benchmark under the stated evaluation protocol."
SAGA-AIPASS
Input claim
"A high benchmark score shows the model is reliable for similar real-world tasks."
SAGA-AIREVIEW
Input claim
"The model passed the benchmark, so it is safe for deployment."
SAGA-AIHIGH_RISK
04What SAGA-AI returns

Structured JSON, built for pipelines.

Every audit returns a deterministic record you can store, route, or block on.

Response payloadapplication/json
  • action band
  • active claim
  • assigned status
  • warranted status
  • short explanation
  • safer rewrite
  • human-review flag
05Who it's for

Teams accountable for what AI claims, not just what it generates.

AI governance teams
RAG teams
Enterprise AI teams
AI safety evaluation groups
Legal-tech
Health-tech
Finance AI
Research & policy
06Current status
  • StagePrivate alpha
  • AccessAuthenticated API
  • WorkflowsSingle audit · Batch audit · Batch report
  • AvailabilityCurrently accepting early conversations
07Early access

Want to audit AI outputs before they become decisions?