Run a repeatable AI assessment without rebuilding the deck every time.
Use Case Foundry turns client evidence, interviews, and operating context into a ranked AI roadmap your sponsor can challenge, trust, and fund — then into pilot-ready agent packages and starter code clients can act on.
Why advisory assessments stall
The common failure mode is not a lack of AI ideas. It is a lack of company-specific evidence for choosing which ideas deserve attention.
- Each engagement becomes a custom spreadsheet, workshop, and deck.
- Recommendation logic is hard to reuse across clients and teams.
- Generic AI ideas sound plausible until sponsors ask why this company can win.
- The engagement ends at a roadmap slide, with no path into implementation.
What advisors can standardize
Use Case Foundry keeps the conversation grounded in workflows, data, pains, constraints, feasibility, moat, and evidence quality.
A reusable AI consulting assessment workflow grounded in client evidence.
A discovery brief from public evidence that seeds the first meeting with dated customer and market pressure.
Scored quick wins, strategic bets, prerequisites, and dropped generic ideas.
Sponsor-ready language that explains the evidence, tradeoffs, and next discovery steps.
Pilot-ready agent packages — blueprint, eval suite, pilot plan — clients can hand to their technical owner.
A client-ready roadmap instead of a brainstorm
Start with workshop notes, process exports, and public context. The assessment turns them into an opportunity shortlist with evidence gaps, first experiments, and decision-ready writeups — and, for the bets worth pursuing, a deployment-readiness package.
Pilot the grounded workflow
Start where pain, data access, and human review make the first experiment credible.
Invest where the company has advantage
Prioritize candidates backed by proprietary data, scarce expertise, or reusable abstractions.
Close what changes the decision
Turn missing facts into interviews, metadata checks, redacted samples, or instrumentation work.
Why the recommendations are easier to defend
The method makes the reasoning inspectable before budget, pilots, or diligence decisions depend on it.
Demand-chain scans turn public customer, regulator, and market evidence into reviewable mandate hypotheses before discovery begins.
Operator coverage shows which of 52 opportunity patterns fired and what evidence would unlock more.
Transparent scoring lets clients challenge assumptions instead of debating opinions.
Dossiers turn selected bets into one-pagers for sponsors and reviewers.
Deterministic readiness gates — not the LLM — decide whether an opportunity is ready for a pilot or production handoff.
Built for sensitive evidence work
Use public pages, notes, metadata, aggregates, redacted samples, or controlled LLM endpoints. Human reviewers decide which facts enter the model.
Private discovery without forcing raw records into the workflow
Auto-map and evidence extraction propose changes, but scoring only changes after a reviewer accepts the facts.
Go deeper with resources
Review sample outputs, comparisons, and methodology pages to evaluate fit before a pilot.
The Foundry Method
A six-step AI consulting framework that runs as a repeatable workflow.
Demand intelligence method
How dated public evidence becomes a focused discovery agenda.
Sample discovery brief
See how public signals become a sourced discovery agenda.
vs consulting templates
Why structured assessment beats slide reuse alone.
Discovery interview guide
Prompts for gathering client evidence in workshops.
Sample roadmap output
See a sequenced roadmap from manufacturing evidence.
Agent deployment readiness
How opportunities become gated agent blueprints and handoff packages.
Build an AI roadmap you can defend
Use a sample company now, or reach out to discuss the assessment workflow for your team.