Enterprise security. Compliance-ready architecture.
SynTraktX™ is built with audit-first principles, enterprise-grade security controls, alignment to the most rigorous compliance frameworks in regulated industries, and decision records an independent reviewer can check.
Tamper-Evident Audit Trail
Every action logged with cryptographic hash chain integrity verification. Detect any modification, deletion, or reordering. Signed checkpoints anchor the chain head at points in time.
Decision Attestation
Every governed decision is sealed over the model versions, parameter vector, and configuration version that produced it. A verification endpoint re-derives the seal and confirms the match.
Governance Replay
Any historical decision can be reconstructed with the actor, trust, engagement, and causal context that surrounded it, and rendered as a structured incident report.
Agent Governance Surface
AI agents reach SynTraktX through a curated Model Context Protocol server limited to proposal submission, decision checks, history queries, and trust scores. Admin, key management, and infrastructure endpoints are not exposed.
API Key Lifecycle Management
Database-backed key management with secure hashing, rotation, revocation, and expiry tracking.
Role-Based Access Control
Multi-tenant isolation with per-key roles, timing-safe authentication, and tenant boundary enforcement.
Rate Limiting & DDoS Protection
Per-IP rate limiting with sliding window, automatic Retry-After headers, and health endpoint exemptions.
Encryption at Rest
Application-level column encryption for sensitive data fields with symmetric key management.
PHI Boundary Enforcement
HIPAA-compliant data boundary enforcement strips, hashes, or redacts protected health information at all persistence points.
Built for the frameworks that matter
Information Security, Access Control, Change Management, Incident Response, BC/DR, Data Classification, Risk Assessment, Vendor Management, Acceptable Use, Security Training
Security Rule mapping with remediation roadmap for covered entities and business associates
Comprehensive AIMS framework with 24/24 controls applicable, covering AI policy, impact assessment, model documentation, and human oversight. Evidence packages are generated per control from live governance data
Progressive trust architecture maps to EU AI Act risk tiers. Article 14 human-oversight transparency reports and Colorado AI Act disclosures are generated from live decision records
Built to be checked by someone who is not us
The AI industry's governance debate has narrowed to one question: can an outside party verify what a system did, or only read what its operator reports? In September 2026, leading frontier AI developers committed publicly to embedded independent evaluators with continuous access to evidence and the right to publish their findings. California's Transparency in Frontier Artificial Intelligence Act, in effect since January 2026, requires frontier developers to report the extent of third-party evaluator involvement before deploying a model, with New York's RAISE Act following in 2027.
Those laws bind frontier developers. The expectation they set, that an operator's own report is not enough, reaches every regulated enterprise that deploys AI in consequential decisions. SynTraktX was designed for that standard at the level of the individual decision. Every governed decision is sealed the moment it is made, the audit chain is anchored by signed checkpoints, any decision can be replayed with its full context, and read-scoped roles let an auditor examine the record without the ability to alter it.
AI Governance Documentation
AI Governance Policy
Documented governance principles: earned trust, human oversight, transparency, fairness, and adversarial integrity. AI systems must demonstrate reliability before receiving automation authority.
Human Oversight Framework
Five-stage trust progression from observation to full autonomy. Humans retain decision authority at every governance boundary. Oversight scales inversely with demonstrated trust.
AI Impact Assessment
Proactive risk assessment across all AI systems and eight industry verticals. Evaluates autonomy levels, bias risk, privacy impact, safety implications, and data protection.
AI Model Documentation
Three core ML models fully documented with intended use, training methodology, performance characteristics, known limitations, fairness considerations, and failure modes.
Controls Implementation
24 of 24 ISO 42001 Annex A controls applicable. 16 implemented, 6 in progress, 2 planned. Full Statement of Applicability maintained with implementation references.