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AI Opportunity Audit

Know where AI will pay —before you build.

A two-week, fixed-price diagnostic of one part of your operation: every automation candidate mapped, scored on ROI and feasibility, and given an honest verdict — plus a build-ready plan for the winner. A paid diagnosis, not a disguised sales exercise.

The audit, at a glance
Duration
Exactly two weeks
Commercial
Fixed price, agreed before kickoff
Team
Principal-led, senior only
Scope
One bounded business area
Implementation credit
If we move to implementation together within 45 days, 100% of the audit fee is credited toward the build.
Why an audit

Three questions stall every AI budget.

The audit answers the first with evidence — and tells you exactly which of the other two you’ll face next.

Q1

Where will it pay?

You can see the operational drag — manual work, delays, stalled experiments — but can’t yet rank the opportunities or defend the economics to a board.

Q2

Can we ship it?

A use case looks promising, but feasibility, data readiness, integration effort, and production risk are still guesses rather than evidence.

Q3

Who will own it?

Consequential technical decisions are queued up with no senior AI owner — or the owner wants an experienced second set of eyes before committing.

Honest by design

Every candidate leaves with a verdict.

Five outcomes are on the table — and the last two are the reason the audit is worth paying for. No vendor selling you a build will say them.

  • Build it
  • Prototype first
  • Re-scope it
  • Don’t build yet
  • Use simpler software, not AI
What you get

You keep every artifact.

Written for the budget owner and the build team alike — and portable: any competent team could execute the plan.

01

Executive decision memo

One page: the recommendation, expected value, key assumptions, and the immediate decision required. Written for the budget owner, not the engineers.

02

Current-state workflow map

Systems, handoffs, decision points, manual effort, delay, and failure modes — with real volumes attached, so the baseline is observable rather than anecdotal.

03

Ranked opportunity portfolio

3–5 candidates scored on estimated annual value, implementation range, time to value, technical feasibility, data readiness, adoption risk, and confidence.

04

Editable ROI model

Assumptions and sensitivity ranges you can stress-test yourself — not a single optimistic headline number.

05

A verdict on every candidate

Build it · Prototype first · Re-scope it · Don’t build yet · Use simpler software, not AI. The honest outcomes are what make this a diagnosis, not a sales exercise.

06

Build-ready plan for the leading candidate

Target workflow, proposed user experience, architecture sketch, data and integration requirements, human-review controls, evaluation approach, team shape, timeline, cost range, and acceptance criteria.

07

Final working session

60 minutes with the decision-makers — focused on the decision, not a slide walkthrough.

Your side of the effort

Most stakeholders contribute 30–45 minutes. The executive sponsor typically spends two to three hours across the two weeks. Eventum does the analysis.

How it runs

Ten working days, marked out.

Bounded by design: a hard finish line is what turns analysis into a decision.

  1. Days 1–2

    Kickoff + interviews

    Agree the audited area, success criteria, and evidence sources. Schedule short stakeholder interviews.

  2. Days 3–6

    Workflow + data review

    Map the current state and test whether the key assumptions are actually observable in your systems.

  3. Days 7–9

    ROI + feasibility

    Rank the candidates by value, technical feasibility, data readiness, and adoption risk — with confidence levels attached.

  4. Day 10

    Decision readout

    Select the leading candidate and leave with a build-ready pilot plan your team can execute — with us or without us.

Fit check

Built for operators, scoped on purpose.

Four things make an audit worth running — and six things it deliberately is not.

It’s a fit when

  • You can point at real operational pain — specific workflows, not “we should do something with AI.”
  • A budget owner is involved, or one call away.
  • A meaningful build budget is plausible if the case is proven.
  • You’ll give us stakeholder access and read-only visibility into the relevant systems.

Deliberately not included

  • Production implementation or code
  • Write access to production systems
  • Vendor procurement or contract negotiation
  • A company-wide AI strategy
  • A second, unrelated business area
  • Unlimited follow-up consulting after the readout
Proof of results

Analysis by the people who ship.

The people running your audit are the people who build — the plan you get is one we’d be willing to execute ourselves.

View all case studies
50%+lower model error in a production computer-vision workload
70%lower infra cost in an ML platform
40%faster ML development cycle after MLOps and data changes
4 mofrom concept to a launched generative-AI product
FAQ

Fair questions,straight answers.

  • A free assessment has to end in a pitch — that’s what pays for it. A paid diagnosis can afford honest verdicts, including “don’t build yet” and “use simpler software, not AI.” You’re paying for an answer you can defend, not a proposal.

Two weeks from now, you could know.

A 15-minute scoping call is enough to agree the area and the kickoff date — and if we build together within 45 days, the audit effectively costs nothing.

Book a scoping callWe’ll recommend the fastest credible path — even when it isn’t us.