Sit with the real work.
The documented process is not the job. I watch the work as it actually runs, including the exceptions that live in one person's head.
How AI enters a company
The person who puts AI into real company work.
Everyone can buy the same models. The edge is where the intelligence lands inside your real work: which workflow, which decisions, who approves. That deployment work is the job. I sit with the work, model only the judgment steps, and install a system your people run.
Models are cheap now, and every competitor can buy the same ones. The difference is what happens inside one company: which workflow gets the intelligence, who decides, and what the people actually run. That is the deployment work, and it is specific to your business.
Four moves, in order: learn the real work, model only what needs judgment, keep a person at every decision, and build on what you already run.
The documented process is not the job. I watch the work as it actually runs, including the exceptions that live in one person's head.
Most of the system is deterministic: rules, checks, and records. Only the steps that need judgment get a model.
The system drafts and prepares. A named person reviews and approves before anything leaves or writes to a record.
No forced migration. The system lives inside the software you already use and writes results back to it.
Paid map → one live workflow → the loop
The paid map collects the real steps, the exceptions, and the systems, then says where AI belongs. One live workflow runs end to end, with a person approving every consequential step. Then the loop: observe, correct, and expand to the next bottleneck.
Revenue, risk, and cost. Every workflow is measured against those three buckets and nothing else. If the work does not move one of them, it does not run. The system traces every step; no silent agent.
Bring one task that repeats, gets handed off, or depends on one person. The first conversation tests fit before any build.
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Workflow brief
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