From AI decision to compliance evidence. In every regulated context.
Aegis Trace provides complete decision provenance for every regulated industry where AI systems influence outcomes that must be evidenced. The same API, the same certificate format, the same tamper-proof audit trail.
A wealth manager's AI recommends selling a position. The FCA asks why.
The situation
A client's portfolio is reviewed by an AI-assisted suitability engine. It recommends reducing exposure to a fund based on risk profile, market conditions, and client objectives. Six months later, the FCA requests evidence that the recommendation was suitable under Consumer Duty. Without Aegis Trace, the firm has application logs. With Aegis Trace, they have a signed certificate with complete decision provenance.
The regulations
{
"agent_id": "suitability-engine-v3",
"decision_type": "portfolio_recommendation",
"input_hash": "sha256:a3f8c1d...",
"output": {
"action": "REDUCE_EXPOSURE",
"fund": "GB00B3X7QG63",
"rationale": "Risk profile mismatch, client objective: capital preservation"
},
"regulatory_context": ["FCA_PS22_3", "CONSUMER_DUTY"],
"client_ref": "[REDACTED-BY-PRESIDIO]"
}{
"certificate_id": "AT-2026-03-22-f8a3c1d",
"verdict": "PASS",
"confidence": 0.9847,
"hmac_signature": "a3f8c1d9e2b4f...",
"pii_redacted": true,
"regulatory_refs": ["FCA PS22/3", "Consumer Duty"],
"sealed_at": "2026-03-22T11:53:52Z",
"retention_until": "2033-03-22T00:00:00Z"
}A clinical decision support system flags a drug interaction. The MHRA needs the audit trail.
{
"agent_id": "clinical-dss-v2",
"decision_type": "drug_interaction_flag",
"input_hash": "sha256:b7e2a9f...",
"output": {
"flag": "INTERACTION_WARNING",
"severity": "HIGH",
"drug_pair": "[REDACTED]",
"recommendation": "REVIEW_BEFORE_PRESCRIBING"
},
"regulatory_context": ["MHRA_AI", "EU_MDR"],
"patient_ref": "[REDACTED-BY-PRESIDIO]"
}{
"certificate_id": "AT-2026-03-14-c9d2e8f",
"verdict": "PASS",
"oversight_required": true,
"pii_redacted": true,
"regulatory_refs": ["MHRA AI Guidance", "EU MDR Art.61"],
"sealed_at": "2026-03-14T09:22:11Z",
"retention_until": "2036-03-14T00:00:00Z"
}The situation
An AI system assists a clinician by flagging a potential drug interaction based on a patient's prescription history. The recommendation influences the prescribing decision. Under MHRA AI regulations and the EU MDR, the hospital must demonstrate the AI's recommendation was within validated parameters and was appropriately overseen. Aegis Trace provides complete decision provenance for every clinical AI output.
The regulations
An underwriting model declines a policy. The applicant requests an explanation under GDPR Art.22.
The situation
An automated underwriting model assesses a commercial insurance application and returns a decline decision. Under GDPR Article 22 and FCA ICOBS, the applicant has the right to request a meaningful explanation of the automated decision. The insurer must produce a record of what the model assessed, what it decided, and on what basis. Aegis Trace captures the full decision provenance automatically.
The regulations
{
"agent_id": "underwriting-model-v4",
"decision_type": "policy_assessment",
"input_hash": "sha256:d4c1b8e...",
"output": {
"decision": "DECLINE",
"risk_score": 0.847,
"primary_factors": ["claims_history", "sector_risk"],
"explanation_ref": "EXP-2026-03-11-449"
},
"regulatory_context": ["GDPR_ART22", "FCA_ICOBS"],
"applicant_ref": "[REDACTED-BY-PRESIDIO]"
}{
"certificate_id": "AT-2026-03-11-d4c1b8e",
"verdict": "PASS",
"explanation_available": true,
"pii_redacted": true,
"regulatory_refs": ["GDPR Art.22", "FCA ICOBS", "Solvency II"],
"sealed_at": "2026-03-11T14:07:33Z",
"retention_until": "2033-03-11T00:00:00Z"
}Your AI credit model declined a mortgage application. The borrower appeals.
{
"agent_id": "credit-scoring-v2",
"decision_type": "mortgage_assessment",
"input_hash": "sha256:e7f3b2a...",
"output": {
"decision": "DECLINE",
"risk_score": 0.782,
"primary_factors": [
"debt_to_income_ratio",
"employment_tenure"
],
"explanation_ref": "EXP-2026-04-02-891"
},
"regulatory_context": ["FCA_CONC", "GDPR_ART22"],
"applicant_ref": "[REDACTED-BY-PRESIDIO]"
}{
"certificate_id": "AT-2026-04-02-e7f3b2a",
"verdict": "PASS",
"explanation_available": true,
"pii_redacted": true,
"regulatory_refs": ["FCA CONC", "GDPR Art.22"],
"sealed_at": "2026-04-02T10:18:44Z",
"retention_until": "2033-04-02T00:00:00Z"
}The situation
An AI-assisted credit scoring model evaluates a mortgage application and returns a decline. Under FCA CONC and GDPR Article 22, the firm must provide a meaningful explanation of the automated decision and demonstrate the assessment was fair. Without Aegis Trace, the firm has model logs scattered across systems. With Aegis Trace, there is a single, signed decision record with complete provenance.
The regulations
Your trading algorithm executed a series of orders during market volatility. The FCA requests a reconstruction.
The situation
An algorithmic trading system made autonomous decisions during a period of market stress. Under MiFID II and FCA SYSC 9, the firm must be able to reconstruct the decision chain: what data the model consumed, what signals it acted on, and what orders it placed. Aegis Trace provides a sealed, time-stamped record for every execution decision, with complete decision provenance from market input to order output.
The regulations
{
"agent_id": "algo-trading-v7",
"decision_type": "execution_order",
"input_hash": "sha256:f9a2c7d...",
"output": {
"action": "SELL",
"instrument": "GBPUSD",
"quantity": 500000,
"signal_strength": 0.91,
"market_condition": "HIGH_VOLATILITY"
},
"regulatory_context": ["MIFID_II", "FCA_SYSC_9"],
"execution_ref": "ORD-2026-04-07-1142"
}{
"certificate_id": "AT-2026-04-07-f9a2c7d",
"verdict": "PASS",
"pii_redacted": false,
"regulatory_refs": ["MiFID II", "FCA SYSC 9", "MAR"],
"sealed_at": "2026-04-07T11:42:08Z",
"retention_until": "2033-04-07T00:00:00Z"
}The regulation changes. The requirement does not.
Tell us your regulatory context.
We will confirm whether Aegis Trace covers your specific requirements and provide relevant technical documentation.