The agentic AI platform
Agents, workflows and digital coworkers — composed in days, then run inside a governance loop they can’t step outside. Build in Studio, govern in Shield. One runtime, one audit trail.
Governing AI agents is not an access-control problem.It is a records problem.
The gap
Agents are already reading production data, calling tools and acting on their own. The controls meant to govern them live somewhere else — in logs, dashboards and spreadsheets, assembled after the fact.
between what organisations believe they can prove and what they can actually produce when someone asks.
Deployed ahead of control
Every team is wiring AI into real systems. Adoption is running years ahead of any policy, approval or audit.
Ungoverned by default
Most agents run with no policy check, no autonomy limit and a trail scattered across systems. Nobody can even list the agents that were never registered.
Judged on evidence
Regulators no longer accept a policy document. They ask for operational evidence — reproducible, not hopefully-complete.
Platform
Studio · build + run
Agents, Xens and workflows — bound to your knowledge, your tools and any LLM. Or describe what you need and the platform composes it with you.
Renewal Sweep
Renewals desk · 1,240 contracts in scope
Shield · govern + observe
Policy, autonomy limits, human approvals and a full audit trail on every action — plus discovery of the AI nobody registered.
How it works
aXentic isn’t a governance add-on you point at your agents. It’s the runtime they’re built on and run inside.
Compose it in Studio from your knowledge, your tools and your rules — or describe what you need and let the platform assemble it.
It runs on a durable, replayable runtime — reaching your systems and any LLM, across Teams, Slack, email or your own app.
Before anything happens it’s checked against your policy and autonomy limits — or it holds for a human.
Every decision is bound to the record it touched and written to one append-only audit trail — so you can re-derive it later, not just retrieve a log entry.
Capabilities
Three on each side of the runtime, and every one of them is something you can demonstrate rather than claim.
Bring your own agent
An agent from another framework registers here and runs under the same policy, autonomy ceiling and audit trail as one composed in Studio.
Tools and systems
Your own tools over MCP and governed connectors to your systems — each one scoped to the agent allowed to use it, not opened to every agent at once.
Workflows as code
Durable and replayable: a run survives a restart, and any past run can be replayed step by step under the definition that produced it.
Mid-run re-gate
If the facts change part-way through a task, the action is re-judged before it lands — not flagged afterwards.
Classification inheritance
Anything derived from sensitive data stays sensitive — without anyone having to re-tag it downstream.
Runtime obligations
Your obligations execute as part of the work, and record themselves as they do.
Xens
Humans built the tools. Now the tools have colleagues — persona-driven digital workers that carry memory across sessions and live where your teams already work.
Identity
A name, a role and a voice. Your people talk to a colleague — not a text box.
Memory
It remembers prior decisions and carries context across sessions.
Presence
One identity across Teams, Slack, Telegram and email — and it can join a live meeting, listen and speak back.
Control
Every Xen runs at an autonomy level you set, with approvals, obligations and a full audit trail.
Enterprise
For the CIO
A governed production agent composed with you — instead of a six-to-twelve-month build.
For the CFO
Build, govern, retrieve, audit and observe in one runtime — and retire the pile of point tools.
For IT
Cloud, on-prem or fully air-gapped — the whole platform runs where your data already lives.
For compliance
Hard tenant isolation, single sign-on with the identity you already run, and one firm rule: your data never trains anyone else’s model.
For the CISO
Every action policy-checked, autonomy-bounded and on one auditable trail — plus discovery of the agents nobody registered.
For the board
Every action carries an owner, the policy version that judged it and reproducible evidence — so “what was it allowed to do, and who said so” has an answer before anyone asks.
For the CTO
LLM-agnostic across every major provider, bring-your-own-agent, your own tools over MCP, and workflows that are portable code — not a canvas you can only export as a screenshot.
For the head of AI
Every agent registered, versioned and owned, with an autonomy level and an approval path — so a proof of concept can actually graduate instead of stalling at review.
Talk to us
Bring one of your workflows. We’ll build it, govern it end to end, and show you the audit trail you’d hand a regulator — on your own use case, not a demo script.
Or email us directly
info@axenticlabs.ai