Agents API

All 8 ReguNav agents are exposed as deterministic, replayable HTTP endpoints. Same input + same dictionary version + same rule set = same output, every time.

Why deterministic?

Compliance is a regulator-defensible domain. "The model said so" is not a defense. Every agent decision can be replayed byte-for-byte with the input, dictionary version, and rule set used. ReguNav stores all three in the audit-trail.

Endpoints

Path	Description
POST /v1/agents/classifier	Annex III + GPAI risk classification — deterministic, replayable
POST /v1/agents/framework-mapper	Crosswalk a control to every framework that requires it
POST /v1/agents/evidence-compiler	Match uploaded artifacts to controls with confidence scoring
POST /v1/agents/fria	Auto-fill FRIA forms; escalate fields requiring human judgment
POST /v1/agents/incident-reporter	Generate Art 73 serious-incident reports + routing targets
POST /v1/agents/training-curator	Curate Article 4 AI literacy training plan by user role
POST /v1/agents/conformity-guide	Walk through Annex VI / VII conformity assessment paths
POST /v1/agents/gpai-docs	Generate Annex XI / XII technical documentation for GPAI models

Example: Classifier

curl -X POST https://api.regunav.com/v1/agents/classifier \
  -H "Authorization: Bearer $REGUNAV_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "aiSystem": {
      "name": "Loan Origination Classifier",
      "purpose": "Predicts approval likelihood for retail loans",
      "providerKind": "first_party",
      "intendedUsers": ["loan officers"]
    },
    "jurisdiction": "EU",
    "applicableFrameworks": ["eu-ai-act", "iso-42001"]
  }'

# Response (deterministic for same input)
{
  "riskLevel": "high",
  "rationale": "Annex III §5(a) — credit scoring of natural persons.",
  "applicableClauses": ["Art 6(2)", "Art 9", "Art 10", "Art 11", "Art 14"],
  "dictionaryVersion": "eu-ai-act@2024.12.1",
  "decisionId": "dec_01HX..."
}

Replay an earlier decision

curl https://api.regunav.com/v1/agents/decisions/dec_01HX...

Returns the original input, dictionary version, rule set, output, and a hash of all four — proving the decision was reproducible.

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