Autonomous AI Agents for the Enterprise

It means software that may take a named set of actions without a person in every turn, under scoped tools, after an eval suite holds, with a human fallback still in place. It does not mean unsupervised, and it does not mean the vendor owns the system.

Not as a first ship, and not on irreversible actions. Start at shadow or confirm-on-write. Raise the level when missed-escalation and unsafe-action rates hold on live traffic. We do not sell unsupervised as a target.

Four practical levels: read-only, shadow (proposes, does not write), confirm-on-write, scoped auto-write. Each level has a metric bar, a sample size, and a named signer. Promotion is a permission change plus tests.

Agentic describes the loop (plan, act, check). Autonomy describes how much of that loop may run without a person. This page is the gating, evaluation, and ownership model. The agentic page is the loop architecture. Most programmes need both; they are not the same decision.

Four weeks is the standard for one workflow at an agreed starting level: discovery, environments, shadow-mode pilot, handover. Raising a level later is a measured promotion, not another four-week clock.

Yours, and you. Deployment is in your cloud against your identity and data stores. Weights, datasets, eval suite, and runbooks are yours at handover. There is no lock-in that requires us to keep it running.

The action is stopped or rolled back if the tool allows it; the case goes to the human queue with the trace; the failure is added to the eval suite so the same miss is caught automatically. Online monitors sample live traffic so a silent model update shows up on a dashboard, not in a customer complaint.

You do, directly to your provider, at your rates. We are model-agnostic and add no token markup. Routing and caching are tuned so cheaper models run where they still win at the autonomy level you granted.