Enterprise AI agent lifecycle
The control plane for enterprise AI agents.
Bring every agent under one governed lifecycle, from first deployment to a production fleet. Scale without losing sight of what your agents do.
Trusted by enterprises running AI agents in production.
Governed agents
Across your production fleet
Pilot to production
With oversight at every stage
Action traceability
Recorded against agent and policy
You have more agents than anyone can account for.
It starts as productivity. Then it becomes a question nobody can answer.
What each agent is allowed to do.
What it actually did last week.
Who approved it reaching production.
Let teams move and lose sight. Or lock everything down and never leave the demo.
What we hear in these rooms.
Every team has built their own agents, on their own stacks. I couldn't hand you a list of what's actually running if you asked me today.
I can write the policy. What I can't do is prove, after the fact, that every agent actually followed it.
An agent has credentials and it takes real actions. If one does something it shouldn't, I need to know before it's a headline, not after.
We have forty pilots and three things in production. The board doesn't want more demos. It wants the ones that work, running safely.
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One control plane, from first agent to production fleet.
Policy, history and oversight travel with every agent, from first deployment to production.
Onboard
Register agents across your frameworks in one place. Bring the agents you know about, and those you do not yet, into a shared inventory.
Govern
Set policies, guardrails and approval gates once. Apply them to every agent before it acts, with human approval where it matters.
Operate
Run agents in production with human oversight where it matters. Keep a complete record of every action, with context ready for review.
Optimise
See what each agent costs, how it performs and where it drifts. Use that evidence to improve your fleet without starting over.
Swipe sideways to see the full dashboard.
What's actually under the hood.
The detail your platform and risk teams will ask about, in one place.
Frameworks & models
Different stacks. One governed fleet.
Connect agents across frameworks, model providers and standard tool and context protocols.
Connect agents built across common frameworks and orchestration tools. Connect to model providers and support standard tool and context protocols, so agent oversight can live in one place across the stack.
Governance & policy
Rules before action. People at the gates.
Apply guardrails before an agent acts. Define access by role, permissions by action and approvals where people need to decide.
Apply policy guardrails before an agent acts. Use role-based access and action-level permissions to define what each agent can do. Route actions requiring human judgement through approval workflows.
Observability
Follow every action. Understand the cost.
Trace agent decisions and tool calls. Track tokens and costs, detect drift and anomalies, and query the audit trail.
Trace agent actions, decisions and tool calls. Track tokens and costs, review drift and anomalies, and query the audit trail to understand what happened and why.
Security & oversight
Your environment. Defined oversight.
Keep deployment, access and data residency under control, with audit logging and oversight shaped around your organisation.
Use self-hosted or in-your-environment deployment options, with role-based access, audit logging and data residency controls to support your organisation's oversight requirements.
Client stories
Governed agents in practice.
No agent reaches production on its own.
Your team approves each promotion. Nothing goes live unwatched.
Human approval at every gate.
01 / Register
Bring the agent into view.
Bring the agent under Evolis, whatever it was built with.
02 / Define policy
Set the boundaries.
Set what the agent is allowed to do, and what needs a human.
03 / Sandbox
Test before production.
Run the agent against real scenarios with no production access.
04 / Promote with approval
A person makes the call.
A person signs off before the agent touches production.
05 / Operate and review
Keep oversight continuous.
Run with full audit, and review continuously.
Knowing which agents to trust first.
Decide which agents belong in production, what oversight they need, and how to govern them as the number grows. Rensora's advisory teams work with your AI and risk leaders, then stay to deliver.
Talk to our advisory team
More on running agents in production.
White paper
What governed agent operations actually require.
The controls a pilot never needs and production always does.
Read the white paper
Use case
From pilot to production without losing oversight.
The path most teams skip, and what it costs them.
Explore the use case
Blog
Why most agents never make it out of the pilot.
The oversight gap that stalls agent programmes.
Read the article
Your agents are multiplying either way. The oversight is the choice.
Getting an agent to work is no longer the hard part. Keeping a fleet of them governed while they scale is.
