Insurance companies process thousands of claims daily — property damage, medical bills, liability disputes. AI can accelerate adjudication, flag fraud, and reduce cycle times. The challenge: policyholder data includes medical records, financial details, and personally identifiable information that must never leak.
AKIOS solves this with the Security Cage: an ephemeral, sandboxed runtime where AI processes claims under strict, code-defined policies.
The Problem
Claims processing is a bottleneck. Manual adjudication is slow, inconsistent, and expensive. AI can evaluate a claim in seconds — but connecting a model to policyholder data creates a new risk vector. Medical records, SSNs, policy numbers, and financial details are all at stake. A data breach doesn't just mean regulatory fines — it means class-action lawsuits and lost customer trust.
AKIOS lets you deploy AI on claims data without exposing any policyholder identifiers.
The Regulatory Landscape
US insurance companies face a unique regulatory stack:
| Regulation | Scope | How AKIOS Enforces It |
|---|---|---|
| State Insurance Regulations | Each state has its own data protection and claims handling requirements (NAIC Model Laws as baseline) | Policy templates per state ensure the cage enforces jurisdiction-specific rules. |
| HIPAA | Health insurance claims involve PHI — same protections as core healthcare systems | Medical record identifiers redacted before AI processing. Zero PHI exposure. |
| NAIC Model Audit Rule | Insurers must maintain auditable records of all automated decision-making affecting policyholders | Merkle-chained audit trail — every classification cryptographically signed and immutable. |
| FCRA | When AI uses credit-related data for underwriting, adverse action requirements apply | Complete decision provenance exported per claim. Adverse action explanations included in output. |
| CCPA / State Privacy | Consumer data rights — access, deletion, opt-out of automated decision-making | All PII redacted before AI processing. Audit trail proves no personal data retained by model. |
AKIOS enforces these at the runtime level — the AI agent never operates outside the compliance boundary.
The Concept: Policy as Code
AKIOS introduces the concept of a "Security Cage" — an ephemeral, sandboxed runtime environment where data is processed under strict, code-defined policies. For insurance, the key feature is per-state policy templates: compliance rules can be configured per jurisdiction, ensuring the AI respects state-specific claims handling requirements.
The Workflow: Automated Claims Adjudication
| Step | What Happens | Security Control |
|---|---|---|
| 1. Ingestion | Batch of new claims loaded into the Security Cage | SSNs, policy numbers, and medical IDs redacted before AI sees them. |
| 2. Redaction | Policyholder identifiers stripped and replaced with tokens | 50+ PII patterns including medical codes, financial accounts, addresses replaced. |
| 3. AI Analysis | LLM evaluates claims against policy terms — damage assessment, coverage verification, medical necessity | Budget capped ($0.30/claim), network isolated, no persistent storage. |
| 4. Classification | Claims classified as approve, deny, or escalate with confidence scores and rule citations | AI cannot authorize payments. All approvals require human confirmation. |
| 5. Audit | Every inference, data access, and output cryptographically signed | State regulators can verify the complete decision path for any claim. |
Architecture
graph LR
CMS["Claims Mgmt\nSystem"] -->|"claim files\n(encrypted)"| FS["filesystem agent\nbatch ingest"]
subgraph CAGE["AKIOS Security Cage"]
FS --> PII["Redaction Engine\n«SSN» «POLICY» «MEDICAL» «CC»"]
PII --> LLM["llm agent\nclaims triage"]
LLM --> TE["tool_executor\nadjudication rules"]
TE --> VALID["Output Validation\nno payment auth"]
VALID --> MERKLE["Merkle Chain\nSHA-256 signed"]
MERKLE --> COST["Cost Kill-Switch\n$0.30 / claim"]
end
COST -->|"classifications\n(redacted)"| Queue["Decision Queue\nAdjuster Dashboard"]
Queue --> Adjuster["Claims\nAdjuster"]
MERKLE -->|"audit export\n(immutable)"| Compliance["NAIC Audit Trail"]
Compliance --> DOI["State Dept of\nInsurance"]
Policy Configuration
The entire compliance posture is defined in a single YAML file:
# insurance-claims-policy.yml
security:
sandbox: strict
network: isolated
allowed_endpoints: [] # zero network access
pii_redaction:
enabled: true
patterns: [ssn, policy_number, medical_record, credit_card, address, dob]
mode: aggressive
budget:
max_cost_per_run: 0.30
currency: USD
audit:
merkle_chain: true
export_format: jsonl
retention_days: 2555 # 7 years — NAIC record retention
constraints:
payment_authorization: disabled # AI cannot approve payments
human_review: required_for_denials
What the Claims Adjuster Sees
At the end of the workflow, the claims adjuster receives a structured report:
| Field | Value |
|---|---|
| Claim ID | CLM-2026-0210-****5847 |
| Classification | ⚠️ Escalate — Coverage ambiguity detected |
| Analysis | Water damage claim cites "sudden and accidental" but description indicates gradual seepage over 3 months |
| Policy Reference | Section 4.2.1 — Exclusion for gradual deterioration |
| Fraud Indicators | None detected (0.12 risk score) |
| Confidence | 89% |
| Audit Hash | d8f2a1...c47b |
| Policyholder Data Exposed | ❌ None — all PII redacted before analysis |
No SSNs. No policy numbers. No medical details. Just adjudication intelligence with a cryptographic proof chain.
Why It Matters
- Zero Data Exposure: SSNs, medical records, and policy details are redacted before AI processing. Even if the model is compromised, there's nothing to leak.
- State-Level Compliance: Policy templates can be configured per state, ensuring the AI respects jurisdiction-specific claims handling rules.
- Fraud Detection: The sandbox can cross-reference claims patterns without exposing individual policyholder data across claims.
- Auditable Decisions: Every classification includes a cryptographic proof chain. State insurance commissioners can trace exactly how a decision was made.
- No Unauthorized Payments: Hard-coded constraints prevent the AI from authorizing any payments. All financial actions require human confirmation.
Try It Yourself
pip install akios
akios init my-project
akios run templates/batch_processing.yml
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