AI agent development services that end in your environment.
We design, build, and supervise AI agents that do defined jobs inside your business — deployed in your cloud environment, owned by you.
Official services partner of the platforms defining AI
NVIDIA
Anthropic
Every growth plan ends in a hiring plan.
From operators we have sat with: the president of a PE-backed manufacturer — seven ERPs across the business units, a growth mandate from the sponsor, and a back office that only scales by hiring.
SG&A grows as fast as revenue
Every new business unit adds the same back-office roles. The margin story the sponsor underwrote gets thinner each quarter, and hiring is the only lever anyone pulls.
Seven ERPs, one manual roll-up
Each business unit keeps its own books in its own system. The consolidated view is assembled by hand before every board meeting, and nobody fully trusts it.
Pencil-and-paper holdouts
Processes that never made it into any system — order intake, shop-floor logs, approvals — get re-keyed, chased, and checked by hand, every day.
The next hire is always the plan
Every workflow fix ends in a requisition. The org chart grows because nothing else absorbs the work — and the AI workers vendors demo never survive security review.
The org chart of bots
A vendor demoed named chatbots instead of new hires — AI staff on an org chart, until someone asked who supervises them and where they run.
Headcount is the most expensive way to scale.
What the manual scaling plan looks like inside a PE-backed manufacturer today. Your numbers will differ — the first week of an engagement puts figures on yours before anything gets built.
From an anonymized engagement — a PE-backed capital-equipment manufacturer
Hire an AI employee before you hire the person.
Agentic AI implementation starts with the role, not the model: pick one job, encode its rules, put the agent to work under supervision, then earn the second role on the first one’s numbers.
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Pick one role. Shadow the work.
We sit with the team doing the job today — order entry, report assembly, data re-keyed between systems — and write down the rules it actually runs on.
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Build the agent in your environment
Built against your systems and your rules, deployed in your cloud environment. No seat licenses, no vendor data model — the agent and the IP are yours.
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Supervised, with your feedback loop
The agent runs human-in-the-loop: routine work flows through, exceptions route to your people, and we stay on supervision as the rules evolve.
Agentic AI consulting should end in a working agent, not a subscription.
Off-the-shelf bot subscriptions rent you a seat in someone else’s product: generic rules, their roadmap, their cloud. When you cancel, the capability leaves with the subscription.
We are an AI implementation services firm: our team builds the agent against your rules, deploys it in your cloud environment, and hands over the IP. You own the machine.
Led by Peter Enestrom.
Asked by the unofficial AI person.
The straight answers, before you book anything.
Software that does a defined job end-to-end — reading the order inbox, assembling the weekly report, chasing the approval — following your rules and escalating what it cannot settle. AI employees and digital workers are the same idea in staffing language: a named seat on the org chart that does the work instead of a new hire.
A subscription rents generic digital employees in the vendor’s cloud, on the vendor’s roadmap, priced per seat — cancel, and the capability leaves. Building with us means the agent runs your rules in your environment, and the IP stays with you. Buy when the work is generic; build when the rules are yours.
We do, with your feedback loop. Every agent runs with a human in the loop: routine work flows through, exceptions route to your people with the reason attached, and we stay on supervision after launch — watching accuracy, tuning rules, and expanding scope only when the numbers hold.
In your environment — your Azure tenant or the cloud you already run — inside your security perimeter, against your data. You own the agent and every encoded rule. There is no per-seat license and no dependency on us to keep it running.
A fixed-fee sprint scoped to one role. We shadow the people doing the job today, write down the rules, build the agent in your environment, and put it to work under supervision — a working agent in weeks, not quarters. The next role is a separate decision, made on the first one’s numbers.
Start with one workflow.
Tell us where your team loses hours. We will come back with a straight answer on whether AI can help, what it would take, and what it would pay.