AI Agents

An AI agent purpose-built for your industry that runs autonomously on domain-specific workflows.

PROBLEM

What is true now, what must be true, and what bounds the work

GATE OPENS WHEN
  • One workflow runs many times a week and follows the same shape each time
  • Its decisions are real but bounded, and someone could write the rules down
  • The systems it touches expose APIs, not only screens
  • Occasional errors are recoverable, and you would rather escalate than guess
GATE HOLDS WHEN
  • Every case is different and the judgement is the product
  • Volume is low enough that a person clears it in minutes a week
  • Nobody can state the acceptance criteria for a correct outcome

CONSTRAINTS

  • A workflow owner who can adjudicate edge cases

    Without itThe decision boundary cannot be agreed, so the agent has no rule to follow at the margin

  • API access to the systems in the loop

    Without itIntegration stops at the screen, and the agent can read a case but never complete one

  • A sample of real past cases, including the awkward ones

    Without itThe validation harness has nothing to prove correctness against before go-live

PRESENT STATE

  • The workflow as it runs today, intake to completion, timed across twenty real cases

    EstablishesThe baseline duration, and the number of coordination touches each case costs

  • The cases your team escalates, reworks, or argues about

    EstablishesWhere judgement genuinely sits, and where it is habit that can be written down

  • Each system the workflow touches, and what it actually exposes

    EstablishesWhich steps can be completed by API and which currently end at a screen

  • What goes wrong today, and what it costs to undo

    EstablishesThe reversal surface the agent has to stay inside to be safe to run

TARGET STATE

  • The decisions the agent may take alone, and the ones it must route

    Agreed whenThe owner has signed the boundary, including the confidence threshold at each edge

  • What a correct outcome looks like for this workflow

    Agreed whenAcceptance criteria are written down and pass when replayed over past cases

  • The escalation paths, and what context travels with them

    Agreed whenEach path has a named recipient and has been walked with a real awkward case

  • The reversal procedure for an action taken in error

    Agreed whenEvery write the agent can perform has a documented, tested way back

SUCCESS INVARIANTS

What would have to be observable for this to have worked

IDCriterionVerified byPasses when
SC1The standard path completes without a person keying itTouch count and throughput on the standard path, measured against the pre-build baselineCases on the standard path complete without a person touching them, and every case that routes out is counted against a stated exception rate
SC2The agent's authority is written down and ownedReview of the signed decision boundary against the cases it governsThe decision boundary exists in writing with a confidence threshold at each edge, and the named owner has signed it
SC3Correctness is a test rather than an opinionReplay of the acceptance criteria over the agreed set of past casesThe acceptance criteria replay green over the agreed set of past cases, and a regression names the case it failed on

Done stateAll three criteria hold on live cases, with the exception rate inside the range the boundary declares.

DECONSTRUCT

How the distance was cut, and what each part advances

Cut byWhat the workflow is missing: pace on the path it already knows, a written boundary at its edges, a test for what it produces. Ordered so each part removes a dependency the next one would otherwise inherit.

  • D1The standard path is fully describable, and still runs at the speed of a person keying it

    Completes whenAutomating intake to completion on that path, with every non-standard case routed rather than guessed at

    AdvancesSC1

  • D2The rules at the margin live in people's heads, so nobody can say what the agent may decide alone

    Completes whenWriting the decision boundary down with a confidence threshold at each edge, and having the owner sign it

    AdvancesSC2

  • D3Correctness is judged case by case, after the fact, by whoever is asked

    Completes whenAcceptance criteria replayed over real past cases, so correctness is a test rather than an opinion

    AdvancesSC3

PRIORITISE

Which part runs first, and the function that decided it

Ranked by(impact x verifiability x urgency) / max(cost, 1), highest first.

PartFactorsScoreWhy it ranks here
D15 x 5 x 4 / 250The path is already describable, so this is the largest gain available without deciding anything new.
D25 x 4 x 4 / 240The boundary is what lets the automated path refuse a case rather than guess at it, so it follows immediately.
D34 x 5 x 3 / 230Acceptance criteria are only writable once the path and its edges are settled, and they gate go-live rather than build.

NEXT STEP

Think AI Agents is the right fit?

Describe the workflow and the decisions it turns on, and receive a proposal with next steps within 24 hours.

Not ready to commit to a build?

Run the AI Automation Audit Agent first. It returns a build-ready system design for the workflow you describe, alongside modelled savings, a payback range, ranked opportunities, and a sequenced build plan.

The run takes about a minute and costs nothing.