Govern every action your AI agents take.
personmemoryZero trust infrastructure, now carried into the agentic AI era.
Denovo verifies every request, inspects every payload in path, and records every decision as evidence. That same enforcement now extends to your AI agents, tracing what they and their tools are doing, keeping sensitive data inside the boundary you set, and deciding each consequential action before it runs.
What changed when agents joined the workforce.
Security for software that decides for itself.
Three observations shape how Denovo is built.
An agent is not an application
It sets its own sub-goals, starts other agents, picks tools nobody approved and rewrites its own memory, thousands of times an hour, with credentials a human handed it once.
Human-era controls assume a human
They assume a keyboard, a session, and an action a reviewer can read about tomorrow. None of that survives contact with autonomy.
Denovo was built for autonomy
Follow the execution as it unfolds, keep sensitive data inside the boundary you set, and judge each action before it reaches your infrastructure.
Three pillars for securing autonomous agents.
Denovo secures AI agents and the MCP servers they reach at the moment they act. Together the pillars take a security team from reading logs after the fact to stopping an action while it is still a request.
Agent Observability
Live visibility across your network, APIs and local endpoints. Denovo maps execution graphs and multi-step reasoning loops, where logging records only prompts and responses.
Explore Agent Observabilityarrow_forwardAgentic Data Security
Agents ingest wide context windows and touch file stores at machine speed. Denovo sanitizes what goes into models and what agents carry out of them.
Explore Agentic Data Securityarrow_forwardAgent Action Control
A deterministic gate inside the agent's execution loop. Each intended action is weighed against policy and allowed, blocked, or held for human approval before it runs.
Explore Agent Action Controlarrow_forwardOne policy core behind every enforcement point.
Agent, workload and user traffic passes through two points it cannot avoid. Both run the same policy and write to the same audit trail.
Every module on one enforcement path.
The AI safety module and the four controls beside it share one policy engine, one telemetry stream and one audit trail. Models, web, SaaS, identities and data are governed together.
AI Safety
Three pillars working on the same stream: tracing of every agent, sub-agent and tool; protection for the data they carry; and a verdict on each action before it runs.
Nothing is trusted by default.
Sitting on the network earns no access, and holding a credential proves nothing on its own. Every call is checked again, and no decision is inherited from an earlier one.
Identity before access
Every caller resolves to a verified identity. Users sign in against the Denovo user directory, or through your identity provider where you already run SSO, and agents, devices and workloads carry an identity of their own. Location on the network grants no access.
Scoped to the task
Access reaches only the models, apps, tools and data the task needs, for as long as it runs. Credentials delegated to an agent carry the limits of that task.
Decided per request
Policy is evaluated on every request. Identity, device posture, data sensitivity and destination are checked again each time, and access can be withdrawn mid-stream.
Inspected in path
Prompts, tool arguments, uploads and responses are read as they pass. A compromised account or agent is stopped at the chokepoint, before data leaves.
Recorded as evidence
Every allow, redact, limit and deny is written to an audit trail. Auditors read the record of what the system did.
Agents get the same verification
These principles were written for users and devices. Denovo carries them into agent execution: an agent is verified per call, scoped to its task, inspected in path and recorded, however it was credentialled.
See the AI safety modulearrow_forwardEnforcement wherever work happens.
Denovo carries the entire traffic and inspects it in path for network-level enforcement, and governs AI apps at the application layer. Deployment is agentless on both sides: managed devices are configured through MDM, and unmanaged devices reach corporate applications through a clientless portal.
Inside AI apps
Inspect and govern desktop and web AI assistants at the level of conversations, uploads and tool use.
Every connection in path
Denovo sits in the data path of all traffic. Encrypted traffic is inspected at the enforcement edge, the destination is identified at SNI, and unsanctioned connections stop before they complete.
Agentless, deployed by MDM
Nothing to install on the endpoint. Denovo arrives as managed configuration through MDM, so policy reaches every enrolled device. Denovo then protects the device from the internet.
Clientless portal access
No software, no browser extension, no certificate. Users open their own browser at your Denovo workspace address and sign in against the Denovo user directory, or through your own identity provider where you already run SSO. Denovo then protects your applications and data from the device.
Inside the enforcement loop.
Intercept
The call leaves the agent, the sub-agent or the user and reaches Denovo before anything downstream sees it.
Bring your whole estate under one policy.
Denovo verifies, inspects and decides on live traffic from users, devices, workloads and agents, across the models, tools, web, SaaS and data they reach. See it running on your own stack.