A large institution runs AI everywhere, coding assistants in engineering, copilots across the workforce. Every AI-influenced decision is captured, so internal AI adoption stays evidenced and defensible.
The situation
A large institution has AI throughout the business, coding assistants in engineering, copilots across the workforce, automated services making calls every day. Leadership needs internal AI adoption to stay evidenced and defensible without slowing teams down. Aegis Trace captures the AI-influenced decisions made by the firm's own systems and API-mediated copilots, giving governance, risk and audit a single trail across the business.
The regulations
- EU AI Act
- ISO/IEC 42001
- NIST AI RMF
- SOC 2
- Internal AI policy
The evidence
AI-influenced decisions across the business are captured at the source.
POST /v1/decisions
{
"decision": "approve_change",
"system": "engineering-copilot",
"actor": "ai-assistant",
"regime": "EU_AI_ACT",
"context": { "domain": "code_review", "risk_tier": "limited" }
}A governance-grade record, not a log line.
{
"certificate_id": "crt_gov_b903",
"status": "sealed",
"decision": "approve_change",
"regime": "EU_AI_ACT",
"issued_at": "2026-03-14T09:21:07Z",
"inputs_hash": "sha256:3f8a…c1d2",
"model": { "name": "decision-engine", "version": "4.2.1" },
"signature": {
"alg": "ed25519",
"value": "MEUCIQD…Qz9w",
"anchored": "rfc3161"
}
}What the regulator receives
An organisation-wide trail of AI-influenced decisions, scoped to the firm’s own AI systems and copilots, so internal adoption is evidenced and defensible. The claim is "AI-influenced decisions across the business," not every keystroke.