"find me a warehouse worker available today near Nashville" now:
- Parses: role=warehouse, city=Nashville, available=true
- Builds SQL: role LIKE '%warehouse%' AND city='Nashville' AND availability>0.5
- Returns: 12 Nashville warehouse workers with ZIP codes, availability %,
reliability %, skills, certs, and archetype
- Shows understanding tags so user sees what the system parsed
- 414ms, 12 records — not a generic search, a targeted answer
Recognizes 20 role keywords, 40+ cities, 10 states, availability/reliability
signals from natural language. Falls through to vector search for anything
the parser doesn't catch.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New page at /lakehouse/console — a $200/hr consultant's intelligence product:
Morning Brief (auto-loads in ~120ms across 500K profiles):
- Workforce Pulse: total, reliable %, elite %, archetype breakdown
- Geographic Bench: state-by-state reliable % with weakest-state alert
- Comeback Watch: 15K improving workers who crossed 80% reliability
- Risk Watch: 5K erratic + 5K silent workers flagged automatically
- Ready & Waiting: available + reliable workers to call first
- Role Supply: 20 roles with supply/available/reliability
Conversational Chat with 5 intelligent routes:
- "Find someone like [Name] but in OH" → vector similarity search
- "Who could handle industrial electrical work?" → semantic role discovery
(finds workers for roles that DON'T EXIST in the database)
- "What if we lose our top 5 forklift operators?" → scenario analysis
with risk rating, bench depth, state-by-state breakdown
- "Which workers should we stop placing?" → risk flagging
- Default: hybrid SQL+vector search with LLM summary
Every response shows: query steps, records scanned, response time.
Transparency kills the "AI is making it up" argument.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
