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Discovery hub

Arrive at discovery with useful questions to test.

Combine dated public signals, reviewed operating evidence, and guided problem interviews so workshops focus on the gaps that can actually change a decision.

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Build the evidence base

Gather signals, identify supported opportunities, and preserve human control over what becomes truth.

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.

 Demand intelligence methodology Know what the market may demand before the first workshop

Use Case Foundry builds a view from public sources, keeps every suggested priority open to review, and uses it to sharpen discovery without letting public evidence invent AI projects.

 AI use case identification Identify the AI use cases your company has evidence to win

Use Case Foundry compares company facts with a broad library of tested opportunity patterns, explains every score, filters generic ideas, and shows what must happen before a roadmap decision.

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Use people where judgment matters

Prepare the workshop, use Pain Discovery Studio when direct pain-listing fails, and turn missing proof into focused questions.

AI discovery workshop Do the blank-page work before the AI discovery workshop

Start with an automatic company and market scan. When people cannot give a clear list of problems, use Pain Discovery Studio. Enter the workshop with sourced questions, draft priorities, and the specific evidence gaps that need human judgment.

 Pain Discovery Studio When 'what are your pain points?' is the wrong question

Pain Discovery Studio helps a facilitator uncover hidden operational problems from a saved company map. It guides the interview, helps validate one target, and adds only reviewed findings back into the company evidence.

 Template AI discovery interview guide

Use these prompts to gather the evidence needed to choose and rank AI opportunities.

 Sample public-evidence brief Know what customers may demand before the first workshop

This Meridian Fab example shows dated public signals, what they may mean for the business, how they compare with known company strengths, and the questions the first interviews should answer.

 End-to-end walkthrough From a dated public signal to a funded agent package

Follow one Meridian Fab market signal through internal validation, a small and visible change in priority, and the checks required before engineering receives a build package.

Next steps

Turn reviewed evidence into a ranked decision.

The method separates quick wins, larger bets, required preparation, and evidence gaps before delivery starts.

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