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Chapter 1
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Right now, this system is already thinking
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Before you touched anything, it pulled real Chicago building-permit data, measured demand, checked your bench, and began flagging roles that need attention. This isn't theoretical — open your browser network tab and watch the fetches land.
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Chapter 3
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Where your own data would live
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The system stores data in labeled catalogs. Purple pills = synthetic stand-ins you'd swap for your real ATS/CRM/call-log exports. Blue pills = data the system generates about itself (playbooks, audit trails). Nothing else in the pipeline changes — only the source.
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+ The swap path. workers_500k → your ATS export (same schema shape). candidates → your CRM. call_log → your phone system's CDR. timesheets → your payroll export. Once ingested, every behavior you see on the dashboard applies to your real data. No re-training. No replatform.
Powered by Lakehouse — Hybrid SQL + Vector Search across 500,000 embedded worker profiles
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Chapter 4
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Watch the system rank candidates in real time
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This takes the most recent Chicago permit, derives the staffing need, pulls ranked candidates from the 500K bench, and shows you why each one ranked. Everything below loaded in about 3 seconds against the live system.
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Chapter 5
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Every action compounds — the CRM-killer
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A CRM stores. This system compounds. Every successful fill, every no-show, every phone call becomes a re-ranking signal on the next query. Below is the live playbook memory state. The number grows as the app gets used.
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Chapter 6
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Try it yourself
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Type any staffing question. The system picks the right search path (smart-parse, semantic discovery, analytics), shows what it understood, and returns ranked results with memory signal.
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