Siliconex AI · GovernAI Platform
GovernAI
The Purpose Built AI Governance Platform
Trusted · Transparent · Accountable
• The Urgency
Why AI Governance And Why Now
The regulatory window is compressing. Health systems that act now build governance infrastructure once those that wait will face emergency remediation at 3× the cost.
1
Regulatory Pressure is Real
47 states introduced 250+ AI bills in 2025 alone. 33 became law across 21 states. The compliance surface is three dimensional: FDA, CMS, and state law simultaneously.
2
Systems Are Unprepared
Manage 30+ AI models on ad-hoc spreadsheets. Standing up proper governance costs $1–2M per system. The vast majority of AI has never been reviewed by any regulator.
3
The Stakes Are Existential
A misdiagnosis, a biased triage algorithm, or a data breach can destroy a health system’s reputation and finances. AI governance is now a patient safety, legal liability, and accreditation issue.
The GovernAI Architecture
A 4-Layer Governance Framework
GovernAI maps every regulation, standard, and accreditation requirement into a single unified compliance architecture so your team governs once, not four times.
Layer 01
Hard Compliance Federal Regulatory
- FDA SaMD / AI-ML Framework + PCCPs
- ONC HTI-1 Final Rule (algorithm transparency)
- CMS Prior Authorization AI Guardrails
- Washington SB 5395 (PA denial reporting)
Layer 02
Accreditation-Linked Industry Self-Governance
- Joint Commission + CHAI RUAIH (7 elements)
- CHAI Best Practice Guides for PA & Medicaid
- No Fully Automated Denials standard
- Voluntary AI Certification Program (2026)
Layer 03
Operational Layer Technical Standards
- NIST AI RMF (Govern / Map / Measure / Manage)
- ISO/IEC 42001 — AI Management System
- Good Machine Learning Practices (GMLP)
- 3-year certification cycle support
Layer 04
The Baseline — Data & Privacy Compliance
- HIPAA / HITECH — PHI in AI pipelines
- HITRUST CSF — security certification layer
- HHS 2025 AI Strategic Plan
- FHIR-aligned data provenance
AI Transformation Journey
We help organizations streamline operations, improve compliance and accelerate decision making through a structured AI implementation framework.
Assessment & Discovery
Understand needs, challenges and opportunities.
Data & Clinical Intelligence
Collect and structure data for AI readiness.
Workflow & Compliance
Analyze workflows, regulations and compliance requirements.
Monitoring & Optimization
Continuously monitor and improve AI performance.
• The Urgency
AI Governance
The regulatory window is compressing. Health systems that act now build governance infrastructure once those that wait will face emergency remediation at 3× the cost.
AI Model Registry
Catalogue every AI system with risk tier, FDA status, PCCP scope, clinical domain, and responsible owner — one source of truth.
Bias & Fairness Auditing
Demographic parity, equalized odds, and calibration with healthcare-specific fairness benchmarks calibrated to known disparities.
Drift & Performance Monitor
Subgroup-level drift detection with clinical outcome feedback loops — not just aggregate accuracy. Real alerts, not vanity metrics.
Regulatory Compliance Mapper
Auto-map controls to FDA, ONC HTI-1, CMS, Joint Commission RUAIH, NIST RMF, and ISO 42001 maintained as regulations evolve.
Data Lineage & Governance
PHI flow tracking, consent documentation, FHIR-aligned data provenance, and jurisdiction mapping fully HIPAA/HITECH.
Human Oversight Framework
Escalation pathways, confidence thresholds, clinician override capture enforcing that AI assists humans, never replaces them on high-stakes determinations.
Incident Management
Structured adverse event capture, root-cause workflows, and FDA post-market surveillance reporting built on PSO-channel.
Impact Assessment Workflows
Templated bias, fairness, and clinical safety assessments version-controlled to model versions audit-ready at any time.
Transparency Reporting
Model cards for regulators, plain-language AI notices for patients and clinical staff satisfying ONC HTI-1 disclosure mandates automatically.
• Compliance Coverage
State-Level Regulatory Landscape
GovernAI’s regulatory mapper tracks and auto-updates to each state’s evolving requirements so your compliance posture moves with the law, not behind it.
| STATE | LAW / EFFECTIVE DATE | SCOPE | PRIORITY |
|---|---|---|---|
| Texas | TRAIGA (eff. Jan 2026) | Broad AI governance, mental health chatbot protocols, adversarial testing defense | HIGH |
| California | TFAIA (eff. Jan 2026) | Transparency in frontier AI, chatbot disclosure, prohibition on AI impersonating licensed professionals | HIGH |
| Washington | SB 5395 (2026) | Prohibits AI-only PA denials; requires licensed clinician for adverse determinations; AI denial reporting | HIGH |
| Maryland | HB 1563 (eff. Jun 2026) | Novel disclosure requirements for health insurers using AI in coverage determinations | MED |
| Colorado | ADAI (eff. Jun 2026) | Reasonable care to prevent algorithmic discrimination in high-risk AI affecting healthcare access | MED |
| Utah | AI Disclosure Law | Clear disclosure required when licensed professionals use AI during patient-facing services | MED |
•Competitive Moat
Why GovernAI Wins Against Horizontal Tools
FDA SaMD risk tiers, EU AI Act Annex III, and clinical domain classification — out of the box on day one. Horizontal tools require weeks of custom configuration.
Auto-mapping to FDA, ONC, CMS, CHAI, NIST, and ISO maintained as regulations evolve. No manual update cycle, no compliance drift.
Calibrated to known clinical disparities: pulse oximetry bias, pain assessment inequity, maternal mortality gaps. No generic fairness proxies.
FDA post-market reports, Joint Commission evidence packages, and ISO 42001 audit-ready documentation generated automatically from governance activities.
Tracks PHI provenance through AI pipelines using healthcare interoperability standards — the only governance platform built natively on healthcare data infrastructure.