Give Your AI Agents Runtime Authority.
Permission is not Authority.
InvisibleAct is the runtime authority and enforcement layer that controls what AI agents can do before sensitive tools execute.
How InvisibleAct Enforces Runtime Authority
Sitting as an intelligent gateway between autonomous agents and enterprise infrastructure, InvisibleAct validates every tool execution against real-time policies before any payload touches downstream systems.
AI Agent Workflow
An LLM agent or autonomous workflow formulates an intent to trigger an external API, execute a database mutation, or access sensitive records.
Authorization Request
Before the tool executes, the agent invokes the InvisibleAct check endpoint with full runtime telemetry: action, tool name, financial amounts, parameters, and session history.
InvisibleAct Engine
The engine evaluates policies, real-time risk scores, historical agent trust, and sequence trajectory to determine whether the requested action is compliant.
Enforcement Decision
A deterministic tri-state verdict is rendered: ALLOW directly to execution, REVIEW for human approval, or BLOCK for immediate containment.
Gated Tool Execution
Allowed actions execute against target tools. Blocked actions fail closed. Downstream infrastructure remains shielded against rogue or compromised behaviors.
Auditable Security Decision Trail
Every request, evaluation metric, policy match, and final outcome is recorded in an auditable security decision trail for visibility and governance.
Engineered for High-Stakes Agent Autonomy
Deploy autonomous agents into production with confidence. InvisibleAct prevents accidents, exploits, and runaway tool calls across enterprise environments.
Autonomous Payment & Refund Caps
An e-commerce support agent can instantly issue refunds up to $150. Any transaction above $150 automatically triggers a human review before Stripe API execution.
Customer PII & Health Record Protection
Agents accessing CRM or internal data lakes are restricted from broad table exports or unauthorized queries containing unredacted customer identities.
Destructive Cloud & Database Ops
Prevent DevOps and SRE agents from running drop, delete, or terminate commands against production infrastructure, even if prompt-injected.
Multi-Turn Trajectory Guardrails
In complex autonomous chains, detect when an agent deviates from its declared mission parameters or attempts rapid repeated tool invocation.
Sensitive Tool Call Enforcement
Ensure agents only access pre-approved external tools. Enforce strict parameter type checking, destination domain filtering, and rate limits.
Real-Time Human Escalate Queues
Review execution parameters in real time via Web Dashboard and REST API. Slack and Microsoft Teams notification webhooks coming soon.
Works With Any Agent Architecture
Integrate InvisibleAct in minutes through standard HTTP endpoints. Add runtime authority checks into your existing workflow engines and agent frameworks.
LangChain
Native integrations are coming.
Connect through HTTP today.CrewAI
Native integrations are coming.
Connect through HTTP today.n8n
Native integrations are coming.
Connect through HTTP today.Model Context Protocol
Native integrations are coming.
Connect through HTTP today.Custom Agents
Universal HTTP agent integration.
Connect through HTTP today.One Simple API Call.
Absolute Runtime Authority.
Incorporate runtime verification in minutes. Before executing any critical tool or payment API, submit the action payload to /check and inspect the deterministic decision.
- Standardized JSON request/response schema
- Real-time risk scoring and cryptographic request ID
- Fail-closed security behavior by default
- Seamless integration into any backend or agent loop
# Check authorization before executing tool
curl -X POST https://api.invisibleact.com/check \
-H "Authorization: Bearer ia_sec_live_94f8a2" \
-H "Content-Type: application/json" \
-d '{
"agent": "refund_autopilot",
"vendor": "openai",
"action": "issue_customer_refund",
"amount": 150.00,
"tool": "stripe_payments_api",
"data_access": "customer_financial_records",
"session_id": "sess_9824_agent_run"
}'Built for Stringent Security & Governance
Defense-in-depth architecture designed for high-assurance production workloads.
Runtime Enforcement
Deterministic interception occurs before network sockets or API calls execute. No passive monitoring — active real-time gating.
Tenant Isolation
Strict multi-tenant cryptographic partitioning ensures your organizational policies, agent configurations, and telemetry never cross tenant boundaries.
Authentication & RBAC
Granular API key management with role-based access control, scoping specific permissions to designated agents, environments, and teams.
Auditable Security Decision Trail
Every authorization check produces an auditable security record containing agent identity, decision reasoning, risk calculations, and timestamps.
Human-in-the-Loop Approvals
Configurable human escalation paths ensure that actions exceeding risk or financial thresholds require dual authorization before completion.
Fail-Closed Behavior
If an unknown error, network timeout, or policy ambiguity occurs, InvisibleAct automatically fails closed, preventing unverified operations.
Real-Time Runtime Decisioning
High-throughput rule engine evaluates complex policy matrices in real time before tool execution without introducing perceptible lag to agent interactions.
Real-Time Risk Scoring
Continuous agent trust scoring recalibrates dynamically based on historical behavior, error rates, and prompt injection signals.
Runtime Authority & Enforcement Layer for AI Agents
We help organizations govern autonomous agent behavior in real time — before execution occurs.
Why InvisibleAct Exists
InvisibleAct is building a Runtime Authority & Enforcement Layer for AI Agents. We help organizations control what AI agents are actually authorized to do at runtime — across actions, tools, data, state, trajectory, delegated authority, and risk.
Building toward safer, more accountable, and more trusted AI agent deployment across real-world business environments.
Meet the Founder
Building InvisibleAct to make AI agents safer, more accountable, and more trustworthy in real-world businesses.
I’m building InvisibleAct to help businesses safely adopt AI agents with real-time authority, policy and risk control.
InvisibleAct focuses on a simple principle:
The goal is to give organizations greater control over what an AI agent is actually authorized to do at runtime — based on identity, actions, tools, data, context, risk, state and delegated authority.
Give Your AI Agents Runtime Authority
Shield your sensitive tools, enforce financial boundaries, and deploy autonomous workflows without fear of catastrophic agent actions.