Inside your cloud
Agents that do the work.
Deployed inside your own environment, grounded on your own documents, with guardrails around your risk and safety data. Real work, not a chatbot bolted on the side.
Every agent runs the same closed loop: triggered by an event, grounded in your data, checked against your rules, and logged end to end.
An event fires: a new record, a message, or a schedule.
It pulls the context it needs from your warehouse and systems.
It plans the steps and decides what needs to happen.
It runs the tools: draft, update, reconcile, notify.
Sensitive actions pause for a human to sign off.
Every step is recorded, then it waits for the next trigger.
We scope the job, ground the agent in your data, wrap it in guardrails your IT team can sign off on, and deploy it where the work happens.
Built in your own cloud, so your data never leaves your security boundary. We go deepest in Azure and Copilot, and work across other stacks too.
Agents act on your warehouse and operational systems, not a generic model guessing.
Every action is scoped, logged, and, where it matters, held for a human to sign off.
Triage, drafting, reconciliation, follow-up: the repetitive work that never gets done on time.
We pick one repetitive job worth automating and define done.
We connect the agent to your data so it acts on fact, not vibes.
We scope permissions, log every action and add approvals.
It goes live in Teams, Slack and the tools your team already uses.
People often arrive wanting AI: expensive, complicated, board-level AI. Just as often, the job is better served by a machine learning model, or by plain automation. We do all three, and we will tell you honestly which one fits, which is cheapest to run, and which is safest to put into production.
Rules and workflows that simply run. The cheapest, most predictable option when the logic is already known.
A model that learns the pattern when the rules are too complex to write by hand. See machine learning ↗
Reasoning, language and action across systems, when the work genuinely needs judgement and context.
We start with the lightest thing that solves the problem, not the most impressive. And we are not locked to one vendor or one model: deepest in Microsoft and Copilot for enterprise, but able to build on any stack, with whatever AI fits.
Deepest in the Microsoft stack and Copilot for enterprise. Not locked to it, we build on whatever you run, with whatever model fits.
Deployed inside your own environment, grounded on your own documents, with guardrails around your risk and safety data. Real work, not a chatbot bolted on the side.
The work that used to wait for someone to get to it, now triaged, drafted and ready for a decision before the shift even starts.
