LA LatentAtlas Request diagnostic
RAG False Evidence Audit

LatentAtlas audits whether AI evidence actually supports the answer.

Retrieval can return sources that look relevant but are not enough to justify the final answer. LatentAtlas separates supported answers from related-but-not-enough evidence, missing context, stale sources, contradictions, and review-needed cases.

Request the USD 15,000 diagnostic See demo proof
10 days business-day diagnostic
300-1,000 masked evidence packets
$15,000 fixed founding fee
Evidence Boundary Run
sample: masked packets
READY FOR READOUT
2.69M synthetic rows tested
0 false-evidence allows
PASS release and leak gates
SHOW Governed synthetic evidence decisions and reason-code routing. demo_ready
HOLD Real customer data stays blocked until controlled intake is approved. data_blocked
ROUTE Weak, stale, missing-context, or contradictory evidence is not treated as support. review_gate

The failure is not always retrieval. It is evidence sufficiency.

A source can be semantically close and still be the wrong basis for an answer. LatentAtlas tests the boundary between retrieved material and the answer being produced.

Related is not enough

Topical similarity does not prove that a source supports the final answer.

Context can be missing

Answers often need authority, date, status, owner, or policy context.

Risk needs routing

Weak evidence should request context, go to review, or be held back.

The demo proves the operating boundary.

The current demo uses synthetic packets only. It shows how LatentAtlas parses evidence, separates support from related-but-not-enough material, routes weak claims, and keeps real customer data out until controlled intake is approved.

Synthetic only No customer, tenant, personal, or proprietary data is used in the demo pack.
0 allows False-evidence allow count is zero in the current synthetic proof run.
Pass gates Release readiness and leak checks pass before the demo is used in sales.
No mutation The demo does not modify production truth, customer systems, or policy rules.
Can show Governed synthetic evidence decisions, negative controls, leak checks, review handoff, and controlled review gates.
Cannot claim No live customer deployment, real customer-data processing, legal/procurement approval, or production write-back.
Why it matters The buyer can inspect the evidence boundary before sharing a masked sample for the paid diagnostic.
Founding Diagnostic USD 15,000

One-time fixed fee for a 10-business-day audit of 300 to 1,000 masked query/evidence packets.

Contact Huseyin
Input Decision id, query or claim, evidence snippets, policy context, and source metadata where available.
Process Schema fit, masking check, evidence qualification, reason-code distribution, and row-level inspection.
Output Executive readout, structured decisions, sanitized examples, and decision-gate recommendation.
Boundary No production access is required. The diagnostic qualifies evidence sufficiency before a larger build or recurring engagement.

What the team receives

The output is built to support an internal decision: stop, broaden the sample, or design a managed evidence gate.

Diagnostic summary

  • Schema fit
  • Evidence decision counts
  • Reason-code distribution

Examples

  • 15 to 30 sanitized rows
  • Supported vs weak evidence
  • Missing-context cases

Next step

  • Gate placement recommendation
  • Risk and stop-condition summary
  • Expansion path if justified