Autonomous workers, with guardrails and a record of what they did.
We build AI workers that run process-bound workflows continuously or on demand — the kind of work a person currently does by moving data between screens.
The useful application of AI in a client's operation is rarely conversational. It is the process-bound work in the middle: reading a document and extracting what matters, deciding which of four paths a case takes, reconciling two records that disagree, drafting the response a person then approves. That work has rules, it happens constantly, and it currently occupies people who could be doing something else.
We build workers that own those processes end to end. Each one has a defined scope, explicit permissions, a guardrail set that constrains what it may do, and an audit trail that records every action and the reasoning behind it — because in a regulated client's operation, an automation nobody can inspect is a liability rather than an asset.
Where it fits a partner's delivery
Clients are asking every agency and consultancy what their AI plan is. This is a way to answer with delivered work rather than a point of view.
How we engage
Find a process worth automating
We look for work that is high-frequency, rule-bound, and currently manual, with a measurable cost. Processes that are none of those things make poor first candidates regardless of how interesting they sound.
Define the boundary before the build
What the worker may do, what it may access, what it must escalate, and what constitutes a correct outcome. This is written down and agreed with whoever carries the risk — usually before anything is built.
Build, instrument, and evaluate
The worker is built against the client's real systems with logging and audit from the first run. We evaluate against held-back cases and measure accuracy and escalation rate before autonomy widens.
Run it in the open
Deployment starts with a human approving every action, then loosens as the record justifies it. Monitoring, alerting, and periodic review carry on afterwards under a managed agreement if you want them.
Platforms we automate against
A named practice page for each platform partners resell, implement, and inherit.