Bontology

Use case · AI & automation

Know what to automate before you build the agent.

Most automation projects stall on the business side, not the technical one. Bontology maps the work, the systems, and the dollar-ranked problems first, so you automate the things that actually pay back.

Why automation projects stall

The tool is rarely the problem. Teams point an agent at a process nobody has actually mapped, and the gap between how work is assumed to run and how it really runs shows up after the build, not before.

Fig. 1 · start from the work

Start from the work, not the tool

Bontology captures the real activities, the handoffs, and the exceptions, from the people who do the work every day. That is what a build team actually needs before it scopes an agent.

Real activities, not assumptions

Interviews capture what people actually do, including the workarounds and the manual steps nobody put in a process diagram.

Exceptions kept, not smoothed over

The cases that break a happy-path automation are the same cases stakeholders mention first. Bontology flags them instead of averaging them away.

Fig. 2 · rank by dollars

Rank by dollars, not by hype

Every candidate gets priced from what the interviews captured: hours, incidence, and loaded rate. Here is one issue, walked all the way to its ROI.

Fig. 2 · the Hartwell OCR chainSample model: Hartwell Fabrication Co. (fictional)
  1. issue$38,700/yr · manual re-entryestimated
  2. problem$112,400/yr · exposure · intake re-entry✓ verified
  3. solution$86,300/yr · OCR intake · estimated benefit✓ verified
  4. outcome4.2x ROI · 7-month paybackCERTIFIED

$86,300/yr is estimated recoverable capacity, not booked savings: the number the fix is expected to free up, confirmed only once a consultant certifies it.

See the exceptions before they break the automation

The exception queue that reconciles the model doubles as your pre-flight check: every low-confidence or conflicting case is sitting there, adjudicated, before an automation team ever touches the process.

The same queue that keeps requirements honest keeps automation scope honest too. Read the full mechanics on how it works.

Fig. 3 · the readiness view

A readiness view you can act on

Every candidate lands in one of three states: ready now, needs process work first, or Unpriced because the rates or frequency are not in yet. Nothing is guessed into a dollar figure it has not earned.

OCR intake + validationReady now
Approval routing rulesEstimated
Cycle-count automationUnpriced

“Unpriced” is not a gap in the product: it is the model refusing to invent a number it cannot support yet.

Hand the build team a real spec

Once a candidate is ranked and verified, its requirement and user story are already generated, with acceptance criteria and a line back to the interview evidence that justified it. Your automation team scopes against reality, not a guess.

Find out what is actually worth automating.

A short conversation, then a guided assessment on a scenario like yours.