Case Ledger is a curated library of hundreds of real-world AI use cases with verified ROI data, pre-built automation agents, reference implementations, design constructs and workflows. Search by industry or problem - powered by semantic search and GraphRAG. Find your use case, validate it, see who else has done it, understand the problem and the solution, copy the workflow/agent/automation and deploy.
The problem that started Case Ledger was embarrassingly simple: every time someone asked "where should we actually use AI in our business?", the best answers were buried in vendor case studies, paywalled research, or scattered across Reddit threads. Nobody had built a single place where you could search by your actual problem, see what ROI looked like in practice, and then actually get the thing you needed to deploy it.
I'd watched too many organisations spin up AI pilots that went nowhere - not because AI doesn't work, but because they picked the wrong use case, couldn't justify it to the board, or had no starting point for implementation. The information existed. It just wasn't organised, verified, or actionable.
Case Ledger started as a curated library - industry, function, complexity, ROI benchmarks. But it quickly became obvious that a directory without deployable solutions was just another list. So we added the marketplace layer: pre-built automation agents, workflow files, and reference implementations that contributors can sell and buyers can download and run in hours.
The semantic search was the piece I was most excited about. Instead of keyword matching, it traverses a knowledge graph of use cases, industries, tools, and outcomes - so searching "reduce finance team admin" surfaces invoice automation, AP reconciliation, and expense agents even if none of those words appeared in your query. That's the experience that makes the difference between a directory and a tool that actually helps you decide.
We're in founding release now - 250 spots, lifetime access, one-time price. Would love to hear from anyone who's been burned by AI pilots that went nowhere, or who builds automations for clients and wants a library of proven starting points.
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