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For AI & strategy advisors

Run stronger client assessments without rebuilding the process every time

You keep the client relationship, judgment, offer, and fee. Use Case Foundry turns client evidence, interviews, and operating context into a ranked roadmap the sponsor can question and fund, then prepares the best opportunities for a pilot.

Scope an advisor assessment See starting prices

The tension

Why advisory assessments stall

Pressure 1

Each engagement becomes a custom spreadsheet, workshop, and deck.

Pressure 2

Hours disappear into discovery prep and readout synthesis before a sponsor can challenge a real decision.

Pressure 3

Recommendation logic is hard to reuse across clients and teams.

Pressure 4

Generic AI ideas sound plausible until sponsors ask why this company can win.

Pressure 5

The engagement ends at a roadmap slide, with no path into implementation.

The decision

What advisors can standardize

Outcome 1

You own the client engagement while Use Case Foundry supplies reusable software and the hands-on help you choose.

Outcome 2

A reusable AI consulting assessment workflow grounded in client evidence.

Outcome 3

A pre-assessment from public evidence that seeds the first meeting with company context and, when needed, dated external pressure.

Outcome 4

Scored quick wins, strategic bets, prerequisites, and dropped generic ideas.

Outcome 5

Sponsor-ready language that explains the evidence, tradeoffs, and next discovery steps.

Outcome 6

A repeatable set of client materials: sourced brief, ranked roadmap, missing-evidence list, adoption plan, and pilot handoff package.

Outcome 7

Pilot-ready packages—agent design, simulation results, tests, and pilot plan—that clients can hand to their technical owner.

A concrete output

A consultant-ready engagement output

Start with workshop notes, process exports, and public context. The assessment turns them into a sourced brief, a ranked opportunity shortlist, a sponsor-ready roadmap, and, for the bets worth pursuing, a pilot handoff package that does not need to be rebuilt in slides.

What the engagement looks like

  1. Before kickoff — run a source-linked pre-assessment from the client URL, public evidence, and any provided documents.
  2. During discovery — use interviews to validate workflows, pains, data access, owners, and constraints instead of spending the session rebuilding basic context.
  3. After review — deliver a ranked roadmap, specific evidence gaps, and a pilot-ready handoff for ideas that pass the checks.

What the client receives

  • A sourced pre-assessment the sponsor can inspect.
  • A ranked roadmap with quick wins, strategic bets, prerequisites, and dropped generic ideas.
  • Written score reasons that explain why the order changed.
  • An adoption plan, agent design, simulation report, test suite, pilot plan, and clear production-handoff limits for the best opportunities.

Best fit

Boutique AI consultancies, transformation advisors, and independent operators who want a repeatable method without turning every client assessment into a new spreadsheet and deck.

Why the answer holds up

Keep the reasoning attached to the recommendation.

1

Public market scans produce sourced priority questions before discovery begins.

2

The report shows which of 101 opportunity patterns the current evidence supports and what to strengthen next.

3

Transparent scoring lets clients challenge assumptions instead of debating opinions.

4

One-page decision briefs turn selected ideas into clear material for sponsors and reviewers.

5

Fixed checks—not an AI model—decide whether an opportunity is ready for a pilot or engineering handoff.

6

Adoption planning and observe-only simulation turn a ranked decision into a safer route toward live work.

Related reading

Go deeper with resources

Review sample outputs, comparisons, and methodology pages to evaluate fit before a pilot.

Resource How you buy

Starting prices for the workshop, sprint, and pilot handoff — scoped for client proposals.

 Resource The Foundry Method

A six-step AI consulting framework that runs as a repeatable workflow.

 Resource Demand intelligence method

How dated public evidence becomes a focused discovery agenda.

 Resource Sample pre-assessment

See how company evidence and optional pressure context seed discovery.

 Resource vs consulting templates

Why structured assessment beats slide reuse alone.

 Resource Discovery interview guide

Prompts for gathering client evidence in workshops.

 Resource Sample roadmap output

See an ordered roadmap built from manufacturing evidence.

 Resource Agent deployment readiness

How opportunities become tested agent designs and handoff packages.

Other buyer paths

Explore related audience pages.

For investment and portfolio teams Investment and portfolio teams

Use Case Foundry helps investment and portfolio teams test whether a company can win with AI based on its assets, data, workflows, limits, and ability to deliver. The same assessment works across companies, with written reasons ready for investment memos and operating plans.

 For transformation teams Innovation & transformation teams

Use Case Foundry helps transformation teams compare opportunities using the same company evidence: workflows, data, problems, limits, practicality, advantage, and readiness. Ideas worth funding then move into clear packages for engineering.

 For functional leaders Functional leaders

Use Case Foundry helps finance, operations, revenue, support, and people leaders separate practical pilots from generic AI proposals—with approval rules, success measures, and starter code for ideas worth testing.

Next steps

Go deeper with resources

Starting prices for the workshop, sprint, and pilot handoff — scoped for client proposals.

How you buy Return home