AI Governance · Enterprise Runtime Control

The Runtime Control Plane
for Enterprise AI

VyriAI AMCP sits in the hot path between your users and AI systems — enforcing governance policies in real-time, controlling what AI can remember, access, and say, with cryptographic audit-grade proof.

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1,900+
Requests/sec sustained
<500ms
p95 policy latency
100%
Governance coverage
11+
Languages blocked
The $100M Problem

Real losses from uncontrolled AI

Without a governance layer, every AI deployment is a liability waiting to surface.

$100M+
Samsung IP Leak
Engineers pasted proprietary source code directly into ChatGPT. Three separate incidents exposed semiconductor designs, internal meeting notes, and confidential test sequences — in just 20 days.
$15.6M
OpenAI GDPR Fine
Regulators fined OpenAI for uncontrolled data processing. Every enterprise using AI without a governance layer faces the same exposure — inadequate data subject controls and audit trails.
Weekly
AI Data Breaches
Healthcare, finance, and legal sectors report new AI-related data incidents every week. No governance layer means no enforcement, no audit trail, and no defensible compliance posture.
Platform

Runtime governance, not just observability

Traditional tools log what happened. VyriAI AMCP enforces what can happen — in real-time, with zero AI bypass.

  • ✓
    Fail-closed by default — policies are enforced even when the system is degraded. No SLO breach = no governance gaps.
  • ✓
    Cryptographic audit trail — SHA-256 hash chains on every decision. Tamper-evident logs for compliance auditors.
  • ✓
    One-click compliance export — SOC2 and GDPR evidence packages generated on demand, signed and ready for auditors.
  • ✓
    Explainability API — "Why did AI say this?" — full decision trace, memory used, policies applied, with trace_id per response.
Request Flow
👤
User Request
Any AI query from your employees
↓
🛡️
VyriAI AMCP Proxy
Intercept · trace_id · auth check
↓
⚖️
Policy Engine
Risk scoring · fail-closed · redact
↓
🔍
Content Scanner
40+ patterns · source code · PII · secrets
↓
🧠
LLM (OpenAI / Anthropic / Gemini)
Only approved requests reach the model
↓
📋
Audit Log + Response
Hash chain · evidence · trace_id returned
Capabilities

Enterprise-grade governance
out of the box

Every feature ships with audit trails, multi-tenant isolation, and cryptographic proof — ready for enterprise procurement.

🚫
Source Code Blocking
Detects and blocks 11+ programming languages (JS, Python, Java, C/C++, Go, Rust, and more) from being sent to AI systems. Prevents IP leaks before they happen.
🔐
Confidential Data Redaction
40+ regex patterns detect trade secrets, internal-only content, meeting notes, hardware specs, and PII — auto-redacted in real-time before the LLM sees it.
⛓️
Cryptographic Audit Trail
SHA-256 hash chains on every decision. Each event links to the previous, creating a tamper-evident chain that compliance auditors can independently verify.
🏢
Multi-Tenant Isolation
Row-Level Security at the PostgreSQL level ensures tenant data is fully isolated. JWT-scoped tokens prevent cross-tenant data access at every layer.
🔴
Fail-Closed Policy Engine
When SLOs degrade, the system automatically denies high-risk operations. Governance doesn't fail open. Automatically recovers once SLOs normalize.
📦
One-Click Compliance Export
SOC2 and GDPR evidence packages generated on demand — JSON, CSV, or ZIP with PII filtering, tamper-proof signatures, and complete decision audit trail.
💡
Explainability API
/v1/explain/{trace_id} — every AI response includes a full decision timeline: which memories were used, which policies fired, and why the output was shaped the way it was.
🧠
Memory Lifecycle Control
Create, retrieve, search, and purge AI memories with confidence scoring. Control what the AI retains per tenant, per agent — with lifecycle policies and retention rules.
📊
SLO Monitoring
Real-time tracking of latency and error rates. p95, p99 dashboards with automatic enforcement triggers — governance that self-monitors and self-protects.
🔑
Secrets Management
Native integration with AWS KMS and HashiCorp Vault for key management. Environment variable fallback for dev environments. Zero plaintext secrets at rest.
🌐
Multi-LLM Proxy
Single governance layer for OpenAI, Anthropic, and Google Gemini. Switch providers without changing policies. One control plane, any AI backend.
☸️
Private Deployment
Full Kubernetes manifests for on-premises or private cloud deployment. Docker Compose for rapid POC. Your data never leaves your infrastructure.
🕵️
Stealth Mode
Invisible governance. AI systems and users have no indication that a control plane is active. Policy enforcement is silent — blocks appear as natural AI behavior, not governance errors.
Stealth Mode

Governance that's
completely invisible

Traditional governance tools announce themselves — blocked requests return "POLICY VIOLATION" errors that users can learn to route around. VyriAI Stealth Mode is different.

🤫
Zero governance footprint No headers, no error codes, no indicators. The AI appears to respond naturally. Users and AI models have no signal that governance is enforced.
🛡️
Silent block → natural decline Blocked source code or confidential data triggers a natural-sounding AI refusal — not a governance error. Users can't identify what tripped the policy.
📋
Full audit trail, zero visibility to subject While enforcement is invisible to users and AI, every decision is still cryptographically logged. You have the proof; they don't know you have it.
⚡
Hot-toggle via API — no restart Enable or disable Stealth Mode in real-time via the policy API. Switch between visible and silent enforcement without redeploying the service.
See Stealth Mode in Demo →
Stealth Mode · Request Flow
👤
User pastes source code into chat
Python function definition detected
visible
↓
🕵️
VyriAI AMCP intercepts silently
Policy fires: SOURCE_CODE_DETECTED · risk 0.80
hidden
↓
⚖️
Policy engine: deny + rewrite
Decision logged to immutable audit chain
silent log
↓
🤖
AI responds naturally
"I can help with code concepts, but can't process code directly."
enforced
↓
👤
User sees a normal AI response
No "BLOCKED" message. No policy trace. No governance signal.
unaware
AUDIT LOG (invisible to user)
trace_id: ae4f92c1-...
decision: deny
reason: SOURCE_CODE_DETECTED
risk_score: 0.80
stealth: true
hash: sha256:7f3d9a...
Architecture

Built for enterprise scale

Microservices-ready architecture with separation of concerns — auth, policy, evidence, and memory managed independently.

👤 Users / Apps
Any AI client
↓
🌐 API Gateway
Port 80 · Auth · Routing
↓
🔑 Auth Service
Port 8001 · JWT · RLS
⟷
🛡️ LLM Proxy
Policy · Scan · Audit
⟷
⚖️ Policy Service
Port 8002 · Risk · Fail-closed
↓
🧠 Memory Service
CRUD · Confidence · Lifecycle
⟷
📋 Evidence Service
Port 8003 · SOC2 · GDPR
⟷
🤖 LLM Clients
OpenAI · Anthropic · Gemini
↓
🐘 PostgreSQL 14
RLS · Hash chains · Alembic
+
⚡ Redis
Cache · Sessions
+
📨 Kafka
Immutable event stream
Compliance

Audit-ready from day one

VyriAI AMCP was designed with compliance as a first-class requirement — not bolted on after the fact.

⏳ 75% Complete · Certification in 4 weeks
SOC2 Type 1
Trust Services Criteria fully mapped with evidence packages automated and ready for auditor review.
  • Access controls with JWT + Row-Level Security
  • Change management via Alembic migrations
  • Availability monitoring with SLO tracking
  • Data classification via content scanner
  • Incident response and escalation paths
  • Encryption at rest (AES-256) and in transit (TLS)
  • One-click evidence package generation
✓ Ready
GDPR
Data subject rights enforced at the control plane layer — not dependent on individual AI providers.
  • PII detection and real-time filtering
  • Data subject access request handling
  • Right to erasure — memory purge API
  • Data processing audit trail
  • Consent management via policy engine
  • Privacy-by-default policy configuration
✓ Ready
HIPAA
Enhanced audit controls for healthcare AI deployments — PHI detection baked into the content scanner.
  • PHI and PII detection patterns
  • Enhanced audit trails for healthcare data
  • Access logging with role-based controls
  • Encryption controls at rest and in transit
  • Breach notification audit trail
  • Business Associate Agreement (BAA) ready
Performance

Enterprise load, zero governance gaps

Load-tested on April 8, 2026 — 1,900+ RPS with 100% governance coverage at every concurrency level.

Scenario Concurrent Users Total Requests Sustained RPS p95 Latency Success Rate
Light Load 10 100 1,841 RPS 48ms 100%
Medium Load 50 500 1,935 RPS 245ms 100%
Heavy Load 100 1,000 1,927 RPS 491ms 100%
Scalability 200 1,000 1,977 RPS 482ms 100%
99.95%
Policy availability SLO target
<120ms
Decision latency overhead (text flows)
<300ms
p99 audit write latency
AES-256
Encryption at rest + TLS 1.3 in transit
Roadmap

From demo to production

A phased path from working POC to full enterprise deployment — with honest timelines.

✅
Phase 0 — Now
Demo Ready — TODAY
Available now
  • Source code blocking (11+ languages) — working
  • Confidential data redaction — working
  • Cryptographic audit trail with hash chain — working
  • Multi-tenant isolation (RLS) — working
  • Evidence export (SOC2/GDPR packages) — working
  • 1,900+ RPS load tested with 100% success rate
  • Docker Compose deployment for rapid POC
✅
Phase 1 — Completed
Enterprise POC Ready
Done
  • VyriAI console UI fully rebranded and polished
  • Memory CRUD — full create, list, edit (PATCH), delete API shipped
  • Policy hot-reload — live toggle via API, zero restart needed
  • Stealth Mode — silent governance, hot-toggleable
  • Policy Store — versioned, thread-safe, env + file config
  • Source code block, PII redact, confidential block all hot-configurable
⚙️
Phase 2 — 4–6 Weeks
Production MVP
4–6 weeks
  • Full microservice separation (Auth / Policy / Evidence / Memory)
  • mTLS inter-service communication
  • Incident replay from immutable audit logs
  • Performance optimization: caching + DB query tuning
  • Kubernetes auto-scaling configuration
  • SOC2 Type 1 certification (audit execution)
🏆
Phase 3 — 8–12 Weeks
Enterprise Production Ready
8–12 weeks
  • BYOK — Bring Your Own Key (customer-managed encryption)
  • Graph database integration for complex memory queries
  • SOC2 Type 2 preparation begins
  • SIEM integration (Splunk, Elastic, Datadog)
  • Enterprise SLA (99.99% uptime commitment)
  • Automated compliance questionnaire responses
Pricing

Simple, transparent pricing

All tiers include multi-tenant isolation, cryptographic audit trails, and real-time policy enforcement.

Starter
$2,500 / month
For small teams evaluating AI governance. Up to 3 tenants, 500K requests/month.
  • Source code blocking
  • Confidential data redaction
  • Cryptographic audit trail
  • 3 tenants
  • 500K requests/month
  • Email support
  • SOC2 evidence export
  • BYOK encryption
  • Dedicated CSM
Get Started
Most Popular
Enterprise
$12,000 / month
For teams deploying AI at scale. Unlimited tenants, 5M requests/month, full compliance package.
  • Everything in Starter
  • Unlimited tenants
  • 5M requests/month
  • SOC2 evidence export (one-click)
  • GDPR & HIPAA compliance pack
  • SLO monitoring + alerting
  • Kubernetes deployment support
  • Priority support (4h SLA)
  • BYOK encryption
Book Demo
Enterprise+
Custom
For regulated industries (healthcare, finance, government). On-premises, BYOK, dedicated infrastructure.
  • Everything in Enterprise
  • On-premises or private cloud
  • BYOK (customer-managed keys)
  • Unlimited requests
  • SOC2 Type 2 + HIPAA BAA
  • SIEM integration
  • Dedicated Customer Success Manager
  • 1h SLA, 24/7 support
Contact Sales
Get Started

Stop hoping AI behaves.
Enforce it.

Join enterprise teams using VyriAI AMCP to prevent IP leaks, pass compliance audits, and prove AI governance with cryptographic evidence — in real-time.

⚡ Book a Live Demo Contact Sales
📧 Demo
demo@vyriai.com
🌐 Web
vyriai.com
💼 LinkedIn
linkedin.com/company/vyriai
🐦 Twitter
@vyriai