AuditCore is a cryptographically auditable decision engine that makes every automated decision fully traceable, tamper-evident, and explainable — built for the regulated industries that can't afford black boxes.
Every decision flows through a deterministic pipeline. Each stage produces auditable artifacts — and the entire chain is cryptographically sealed.
We don't sell an AI model. We sell the infrastructure that makes any AI model safe for regulated decisions. Choose how much autonomy the AI gets — every tier produces the same cryptographic audit trail.
Human drives, AI assists. Fill in structured forms — the AI enriches reasoning, flags risks, and strengthens confidence scoring. You stay in full control.
Human provides, AI interprets. Paste unstructured documents — the AI extracts structured fields, maps them to your schema, and feeds the decision pipeline. You review before commit.
AI drives, Human approves. A conversational agent gathers information through guided dialogue, proposes a decision, and waits for your sign-off. Full audit trail of every exchange.
Every AI recommendation passes through deterministic compliance rules. The AI can suggest — the rules engine enforces. No exceptions, no overrides.
Swap between OpenAI, Ollama, or any LLM without losing compliance guarantees. Hot-swap at runtime — zero downtime, zero data loss. Your rules survive any model change.
Adjust thresholds, rules, and escalation policies per customer without model retraining. Policy changes are instant, versioned, and audited — configuration, not computation.
Traditional AI systems are opaque. Ours is transparent by design, cryptographically verifiable, and built to satisfy the toughest regulators.
Every decision record is SHA-256 hashed and chain-linked to the previous record. Alter a single byte and the chain breaks — instantly detectable, mathematically provable.
Every outcome includes a human-readable reasoning chain, evidence breakdown, rule-by-rule compliance results, and a weighted confidence score. No black boxes.
Pure Python standard library. No NumPy, no TensorFlow, no third-party packages. Deploys anywhere Python runs — no supply-chain risk, no license liabilities.
Adjust risk thresholds, escalation policies, and compliance limits at runtime. Rules rebuild live — no redeployment, no downtime, full version history.
Counterfactual simulation shows exactly how changing any input affects the outcome. Decision-makers see the sensitivity of every factor before committing.
Exportable audit trails with chain verification, tamper simulation, and per-record integrity proofs. Built for SOX, ECOA, HIPAA, and Solvency II compliance.
Three production-ready domains with domain-specific rules, risk models, and compliance frameworks — extensible to any industry.
Auditable treatment recommendations with patient safety guardrails, drug interaction checks, and informed consent verification.
Transparent claim processing with fraud detection, coverage validation, and regulatory-compliant decision records.
Fair-lending-compliant loan decisions with configurable DTI, LTV, and credit thresholds — ECOA non-discrimination built in.
Every design decision prioritizes auditability, determinism, and regulatory defensibility.
Same input → same decision → same hash. No randomness, no drift, no model retraining surprises. Every outcome is reproducible.
Confidence scores combine evidence strength (35%), reasoning clarity (25%), and rule compliance (40%) — transparent, auditable weighting.
Low-confidence decisions automatically escalate to human reviewers. Configurable thresholds per risk tier — critical cases always get human oversight.
Comprehensive test suite covering every pipeline stage, domain, edge case, and integrity verification path. No untested code paths in production.
Built-in tamper simulation proves the chain catches alterations. One-click restoration re-seals the chain — demonstrate integrity to any auditor.
Add new domains, custom rules, or evidence sources without modifying core pipeline. Plugin architecture scales from startup to enterprise.