runtime governance infrastructure · v3.1.0-shadow

Policy enforcement and observability
for autonomous AI agents in production.

A three-layer stack: governance node, event-sourced control plane, and agent operating system. Every agent action is verified, recorded, and reproducible.

Run Live Demo View Architecture →
12,847 policies enforced
342 agents governed
1,893 threats blocked
demo environment
platform architecture

Three layers. One infrastructure stack.

Each layer handles a distinct concern. Together they provide the complete runtime for safe, observable AI agent deployments.

layer 1

PrivateVault.ai

Governance Layer

Runtime policy enforcement, shadow verification, Merkle audit ledger, and KYC identity checks. Every agent action passes through before execution.

Policy Engine Shadow Mode Merkle Ledger KYC
Policy enforcement at runtime, before execution
Merkle audit ledger — immutable transaction record
Shadow mode — test stricter rules without prod impact
KYC & identity verification for all recipients
layer 2

LORK

Control Plane

Event-sourced runtime for AI agents. Deterministic scheduling, step-level replay, time-travel debugging, and full execution tracing.

Event Sourcing Replay Tracing Debugging
Event-sourced execution — every step recorded
Time-travel debugging — replay any run deterministically
Step-level latency and token telemetry
Directed graph execution visualization
layer 3

BotBook.dev

Agent Operating System

Agent lifecycle management: create, run, orchestrate. Trust scoring, verified identity, capability matching, and a registry of all agents and humans.

CLI Trust Scores Workflows Registry
Trust scoring — composite of completion, ratings, violations
Capability matching — highest-trust agent to any task
CLI-first — scriptable agent lifecycle management
Unified registry for agents and human members
decision integrity engine

Decision Firewall

Proactive Integrity Before Execution. The missing upstream layer in agentic AI governance that forces explicit assumption checks and testing before an agent is allowed to act.

Why Agentic Systems Fail

The Missing Upstream Layer

Agents make autonomous decisions based on unstable assumptions causing errors that result in financial loss or compliance risk.

Decisions based on unstable assumptions
Errors → financial loss, compliance risk
Current systems react after execution
No proactive upstream validation layer

Decision Integrity Engine

Pre-Execution Validation

Acts as a decision firewall inside the PrivateVault runtime. Evaluates assumptions, stress tests contexts, and outputs execution gates with explicit conditions.

Assumption extraction + confidence scoring
Context stress testing against edge cases
Stability scoring (0–1) and classification
Generates execution gates with conditions

Business Impact

The AI Firewall for Regulated Enterprises

Provides enterprise-grade controls, fintech-ready safeguards, cryptographic audit logs, and highly tunable parameters while achieving latency below 300ms.

Blocks unsound decisions pre-execution
Prevent financial losses before they occur
Increase trust & compliance with crypto audits
Tunable controls + strict human escalation

Integration Flow

User Intent → Intent Parser → DIE → Policy Engine → Execution → Audit Ledger

privatevault.ai

Shadow Verification Engine

Agents declare intent. The governance node returns [ALLOW] or [BLOCK] before any action executes. No agent acts without verification.

agent request
quick scenarios
governance response
// awaiting request

Submit an agent intent above to see the governance response from PrivateVault.ai

immutable audit ledger 0 entries
No transactions verified yet.
botbook.dev

Agent Operating System

Register agents and humans. Each membership gets a trust profile, LORK execution ID, and Vault governance identity. Match the highest-trust agents to any task.

agent registry
capability matching
financial_analysis anomaly_detection report_generation customer_support compliance
botbook cli
$ botbook init
lork

Time-Travel Debugging

Event-sourced runtime with deterministic replay. Every agent step is recorded, traced, and reproducible on demand.

execution timeline
deterministic replay
Press "Replay Run" to re-execute the event log
execution graph
agent performance
full pipeline demo

End-to-End In Action

Watch all three layers work together: create agents, execute workflows, verify governance, and inspect the execution trace.

Create Team
botbook.dev :8001
pending
Execute Workflow
sequential pipeline
pending
Governance Check
privatevault.ai :8000
pending
LORK Inspection
timeline + stats + graph
pending
Click "Run Full Pipeline Demo" to see all three layers in action
live console

Live Agent Execution

Execute agents in real-time through the full governance stack. Watch every SSE event as it flows through BotBook → PrivateVault → Gemini → LORK.

execute agent
presets — 3-tier governance
layer status
BotBook idle
PrivateVault idle
Gemini idle
LORK idle
event stream 0 events
Execute an agent above to stream real-time events through the full governance stack
shadow mode

Intent Drift Detection

Detect when an AI agent's actual payload diverges from its declared intent. Test stricter rules without impacting production.

0
Divergences Detected
$0
Risk Prevented
0
High Risk Events
intent drift simulation select an attack scenario
contact sales

Request a Private Demo

Speak with our enterprise solutions team to see PrivateVault in action.