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Automatic discovery, reviewed truth

Automated AI opportunity discovery that shows its evidence

Start with a URL, documents, a spreadsheet, consent-first workflow signals, or a guided Pain Discovery Studio session. Use Case Foundry drafts the company evidence map and candidate opportunities; people decide what counts.

What this establishes

The decision in view.

Principle 1

Build a first company map from its website and documents.

Principle 2

Scan dated public demand signals before the first interview.

Principle 3

Draft real workflows through opt-in, local-first workstation capture.

Principle 4

Use Pain Discovery Studio when operators cannot give a clean pain inventory.

Principle 5

Keep every machine-drafted fact behind human review.

What automatic means here

Many automated assessments make a questionnaire faster. Use Case Foundry automates the expensive work around the questionnaire: finding evidence, structuring it, testing it against evidence-backed plays, identifying gaps, and rerunning the ranking as the evidence improves.

Four discovery engines that remove blank-page work

1. Website and document auto-map

Provide a company URL, annual report, proposal, process note, CSV, spreadsheet, or document folder. Foundry extracts supported offerings, segments, projects, workflows, pains, skills, assets, and constraints into a structured draft.

2. Outside-in public-evidence scan

Foundry scans dated sources from customers, sales channels, competitors, suppliers, regulators, hiring pages, investors, and industry publications. It produces a discovery brief with possible business priorities and links to every source before management interviews begin. Public signals never become verified company facts on their own.

Optional workstation capture drafts recurring workflows, system touchpoints, and bottlenecks from local activity metadata. It records no screenshots, keystrokes, or file contents; raw activity stays local and only redacted summaries enter review.

4. Pain Discovery Studio

When an open-ended interview stalls, Pain Discovery Studio turns the saved company map into a guided interview workspace. Choose complementary interview techniques, draft possible workflow problems, validate one target, and add only reviewed problems back into the company evidence. Suggestions stay separate from facts until a person accepts them.

Automatic evidence, not automatic truth

Automatic extraction and discovery create suggestions. A person reviews what enters the company map. Fixed checks compare accepted facts with a broad library of opportunity patterns, while written reasons explain the value, practicality, and company advantage behind the order. This makes automation useful without allowing a plausible AI answer to silently become strategy.

From discovery to an actionable result

The output is more than a readiness score. It is a ranked set of quick wins, larger bets, required preparation, dropped generic ideas, and specific evidence gaps—plus agent designs, tests, pilot plans, and starter code for selected opportunities.

Questions buyers ask

Resolve the practical concerns.

What is automated AI opportunity discovery?

Automated AI opportunity discovery uses software to gather and structure company evidence, identify candidate AI use cases, score them, and expose missing proof. Strong systems retain sources and human review instead of treating generated claims as facts.

Can Use Case Foundry start from only a company website?

Yes. A URL can produce an initial public-evidence brief and a draft company map. Internal interviews and records are still needed to validate private workflows, pain, data access, ownership, and constraints.

Does automatic discovery remove the need for consultants or subject-matter experts?

No. It reduces blank-page research and repetitive structuring so experts can focus on validation, tradeoffs, and the evidence gaps that materially affect the decision.

Does the system accept AI-generated facts automatically?

No. Machine-drafted facts and suggestions wait for review. A person decides what becomes part of the company evidence.

Next steps

Go deeper with resources

See how accepted evidence becomes ranked opportunities.