SAGA helps teams detect and prevent AI claims that exceed their evidence. SAGA Core is the flagship reasoning-layer infrastructure that preserves evidence boundaries before a conclusion is generated. SAGA Audit is the complementary post-output layer that evaluates outputs already produced.
Reasoning-layer infrastructure that preserves evidence boundaries before AI output. Checks whether a conclusion is authorized by the underlying evidence — before it is ever generated.
Companion layer. Audits finished or near-finished AI outputs before they enter decisions, publications, or deployment workflows.
SAGA Core protects reasoning before output. SAGA Audit checks outputs after.
SAGA is not just hallucination detection, RAG validation, confidence scoring, or a generic guardrail. Many risky AI outputs are not simply false — they are over-authorized. SAGA evaluates whether a claim is being granted more authority than its evidence supports.
Snapshots below. For the full animated walkthrough of both flows, watch the redacted demo.
"The evidence partly suggests a trend, but the draft conclusion says this is definitely proven."
Withhold or reframe.
Conclusion exceeds permitted use of available evidence.
"AI-generated claim: This treatment is proven to work for everyone."
Claim exceeds available evidence.
Reframe or send to human review.
Public demos show redacted outputs only. Internal resolver logic is private and not exposed through API responses, website copy, or documentation.
SAGA is currently accepting early technical conversations, pilot evaluation discussions, and licensing inquiries.