Empower to control AI
Devctrl is the gateway between your AI agents and the tools they use. Define rules once, enforce them on every call, and keep a full audit trail — without slowing your agents down.
Why Devctrl
Compliance. Efficiency. Governance.
Whether you're building with AI agents today or planning to — Devctrl gives your team the control layer to move fast without breaking trust.
For developers
Ship policies like code.
- Author and manage policies with an expressive, easy-to-learn syntax — no waiting on security reviews to move forward.
- Connect and control any external or internal AI system through a single gateway, with zero agent-side code changes.
- Ship policy updates with version control, diffs, and instant rollback — just like you ship code.
For agents
Autonomy inside the guardrails.
- Increase agent autonomy through task-scoped access — agents get exactly the permissions their current work requires, nothing more.
- Let agents collaborate safely with other agents and services without risking policy violations or privilege escalation.
- Every action is evaluated in real time — agents can move fast because the guardrails are built into the gateway, not bolted on after.
For the business
Adopt compliant AI.
- Companies in finance, healthcare, and government can adopt AI agents without compromising on compliance requirements.
- Scale your agent fleet from one to hundreds without policy drift — every agent, every tenant, same rules enforced consistently.
- Full audit trail at the task level means you can prove compliance to any auditor, for any decision, at any time.
The Problem
AI agents don't act like humans
They make thousands of decisions a minute, chain tools together, and escalate privileges in ways traditional access control was never built to handle.
Over-privileged by default
Static roles hand agents sweeping permissions they rarely need — one compromised credential, one bad prompt, and the blast radius is your whole stack.
No task awareness
Traditional access control can't tell whether a call makes sense for what the agent is working on right now. Actions keep getting green-lit that shouldn't.
Policy drift
Hand-maintained rules rot. Different teams grant different exceptions, no one owns the policy layer, and your security posture erodes every week.
The Solution
One gateway. Every agent. Every decision, policy-checked.
Drop Devctrl in front of any MCP server. Your agents keep calling tools the way they already do — Devctrl handles identity, policy, and audit in between.
Built-in Policy Engine
Validate every operation against your policies in real time at the gateway.
Access Control
Isolate access across users, teams, and environments with scoped credentials for every agent.
Audit & Observability
A searchable record of everything your agents do.
Task-Based Access Control
Same agent. Different tasks.
Devctrl knows what your agent is working on and grants only the access that task actually needs. The same agent gets exactly the access each task needs, and nothing that outlives it.
Platform
Everything you need to govern AI
Policy Engine
Write your policies once. Enforce them across every agent and action consistently.
Identity Gateway
Issue scoped credentials to agents. Rotate, revoke, and audit identities from a single control plane.
Audit & Trace
Every request, every decision, every denial — logged.
Task-scoped access
Scope access to what the agent is actually doing right now.
Drop-in gateway
Works with any MCP-compatible agent. No rewrites required.
Real-time Monitoring
Live dashboards for policy violations, latency, and agent behavior across your entire fleet.
Policies & Releases
Release and track policies safely
Review every policy change, simulate it against real traffic, and roll back in one click.
Expressive rules
Policies read like plain English and have full access to request context, identities, and limits — without wrestling with syntax.
Diffs before you deploy
Visually see what rules were added, removed, or changed before enforcing them on production traffic.
2 || (account.overdraftProtection
3 && account.overdraftLimit >= transaction.withdrawal - account.balance)
2 request.tool.name == "finance_wallet",
How it works
Five steps to policy-compliant AI
From zero to governed in an afternoon — with the tools your team already uses.
Connect your MCPs
Point Devctrl at existing MCP servers or register new ones.
Issue identities
Provision scoped credentials for each agent.
Define tasks
Describe the work your agents need to perform.
Write policy
Write rules in CEL, task scoped or global.
Ship and observe
Deploy, monitor, iterate — every trace and denial visible from a single dashboard.
Observability
Trace every decision.
Understand every denial.
Follow every task from request to resolution. See which policies fired, why an action was denied, and get the context you need to debug.
1{ 2 "values": { 3 "transport_fee": 100 4 }, 5 "schoolId": "ce43369b-bbc4-4ee0..." 6 "scopeType": "student" 7}
Allow condition not met
1{ 2 "task": { 3 "name": "allot-bus-to-student", 4 "labels": { 5 "min-transport-fee": 200 6 }, 7 "context": { 8 "school_id": "ce43369b-bbc4..." 9 } 10 } 11}
Take control of your AI
Join the private beta. We onboard every team personally.