Noetis Compliance · Business engine
Compliance Evidence Mapping Engine
Maps internal evidence to a selected, versioned framework.
Answers: "Can an engine map our internal evidence to a framework we supply?" For compliance and audit teams.
Does not certify compliance or replace an auditor. It needs the framework version you supply.
Available today
ImplementedImplemented: runs on the shared runtime with supplied material. One bounded development check on 2026-10-12 took 130.1s with 16 model calls and ended "incomplete". That is a development signal, not an evaluation. Customer access is by approved account.
What you send
- Question
- Supplied text material
- Text material up to 150,000 characters per run
What comes back
- Requirements to controls matrix with evidence and gaps.
- Findings with the located quote and a support status from claim review
- Release status: released, incomplete with reasons, or failed
- Executed roles, usage and measured cost
Sample
Authored illustration. Written by Encevra to show the workflow. Not customer data and not a recorded model output.
Assess our access control evidence against the selected control.
Control AC-2: accounts reviewed quarterly; leavers removed within 24 hours. Evidence: Q1 review sign-off dated 3 Apr. No Q2 review found. HR leaver list: 4 leavers in May. Directory export (1 Jun): 2 of the 4 leavers still active.
- Requirements mapped to the supplied controls, with quoted evidence
- Requirements with no matching evidence listed as gaps
- Evidence that is dated or ambiguous flagged for review
The real response shape is documented in the API reference.
How the workflow operates
Each role is a responsibility in the workflow, served by a third party language model. More roles are not automatically better; depth and routing decide which run.
Built with
Models this engine uses: OpenAI (GPT), Anthropic (Claude), Kimi (Kimi (Moonshot AI)). Specialists run on OpenAI models and the claim review and final brief on Anthropic models. If a provider has a temporary failure, the step can fall back to an OpenAI model, and the run records that.
Scope Analyst
Identify entities, activities and framework boundaries.
Requirements Mapper
Decompose supplied authoritative requirements.
Control Mapper
Match requirements to documented controls.
Evidence Reviewer
Assess whether evidence supports the claimed controls.
Gap Analyst
Identify missing or insufficient controls.
Remediation Planner
Prioritize corrective work and owners.
Evidence and deployment
Evidence
This engine reads the text you send in the request. Each released finding carries the exact quote and its character span in that text, located mechanically before release. Quotes that cannot be located are labelled Insufficient evidence and never shown as source verified. Interpretation is reviewed as a separate step, and gaps such as a missing clause describe what was searched instead of citing text that is not there.
Deployment
Runs on Encevra hosted infrastructure using the third party models listed above. Every model call and fallback is checked against the deployment policy first. Private cloud and air-gapped deployment are planned; discuss deployment requirements.
What it does not handle
- Certification or legal compliance claims based only on an engine report
- Uses only supplied material. No freshness guarantee beyond the documents provided.
- Required for every output during trials.
How to integrate
Send "engine": "compliance" with your question and material from your server. Keys stay server side.
How to evaluate it
No published result for this workflow yet. Build a small answer key from your own work and compare against a strong single model baseline. See the evaluation checklist and method.
Cost and rights: pricing and licensing. Showing outputs to your own customers needs a written agreement.
Related engines
- Contract Review API for NDA and Vendor Agreements
- Security Design Review Engine
- Employee Policy Review Engine
Content reviewed 2026-10-12 by the Encevra engine team. Engine version 0.1.0 on noetis-core-1.