Mile42

A working pilot on your process.

What is the one process you would fix first?

The one everyone works around, or the one eating your team’s time for output that barely needs judgment. Name it. Whether it is a good Phase Zero is usually clear within one conversation.

What frustrates people most?
Everyone knows it is slow, and quietly works around it.
What takes the most of your team’s time?
Manual effort for output that barely needs judgment.
Where does quality slip?
Work that gets redone, or testing that is manual and skipped under pressure.
Which step needs the least judgment?
The one you already suspect a machine could carry.
Start with Phase Zero

Name a process. See it working. Map what comes next.

A roadmap and a demo are the usual answers to an AI question, and both end up on a shelf. We build a working solution on one process you name, in about a month, for a fixed fee.

You name the workflow. We assess the readiness around it, build something that runs on it, and hand you a sequenced roadmap for what comes after the proof. One engagement, fixed scope.

  1. 01
    IdentifyThe process you named, its baseline today, who owns it, and what good looks like.
  2. 02
    AnalyzeWhat surrounds it. Whether the knowledge is findable, the data usable, and the systems actionable.
  3. 03
    PilotA working solution on your process, running beside production and measured against that baseline.
  4. 04
    RoadmapA sequenced map of what comes next, with an implementation estimate specific enough to execute.

Fixed scope, and every stage produces something you keep whether or not you continue.

Four shapes it can take.

One named process, small enough to finish. The right one is usually already obvious to the people doing the work.

Run agents on a live backlog

Carve off part of a real backlog, run agents on it beside your team, and compare the result against your baseline.

Automate one business process

Take one process end to end, with your people reviewing what the agents produce.

Migrate a slice off a legacy platform

Move one real piece, with agents doing the heavy lifting, before you commit to the whole replatform.

Find and fix what is underperforming

Agents analyze a live surface, find what is weak, and fix it with review before it ships.

How we build it

The build starts and ends with your people in charge.

A build run by agents under your people, in parallel to production and measured against the baseline from stage one.

  1. Name the outcome

    The metric and the baseline, before any tool. Without this, there is no way to prove value.

    Plan

  2. Give context

    The rules, the edge cases, what good looks like. Without this, a generic tool nobody adopts.

    Build

  3. Review the work

    Judgment on what the agent produced. Without this, quality drifts.

    Validate

  4. Approve to land

    Agreed up front, so nothing waits on a decision and working software never sits frozen.

    Deploy

AI work rarely stalls on the technology. It stalls at the four handoffs above, which is why each one has an owner.

Nothing in production is touched.

It runs beside production, and it is reversible on day one.

Measured on your own baseline.

Something working on your own process, judged against the number you already report, with no vendor benchmark in between.

The pilot is the first increment.

What ships is the first piece of the real system, and the governance around it outlives the pilot.

See where it sits in the client journeySee the engagement model

What it costs, and what you keep.

Duration
Typically about a month.
Fee
Fixed, agreed before we start. Typically between $10k and $30k depending on the process.
Scope
One named process, the four stages above, and nothing that is not written down first.
What you keep
The baseline, the working pilot, and the roadmap, whether or not you continue.
What comes next
Your call. The roadmap is written so an engineering engagement can pick it up, and so can your own team.
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