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AI-first CRM built specifically for cannabis dispensaries — not a generic CRM reskin. Twilio and the carriers won't touch cannabis, so IPS built the telecom layer itself: an owned SMS/iMessage pipeline at $0 per message. AI drafts every campaign from real POS purchase history, a human approves every send, and revenue is measured at the register against a holdout control group. Multi-tenant, with every dispensary's data isolated at the PostgreSQL layer.

One week of sales research compressed into 8 minutes. A Lead Detective job fires 19 specialized scrapers in parallel — LinkedIn, SEC EDGAR, tech stack, Google News, Glassdoor, funding, job postings — and AI writes the executive dossier, account plan, and conversation guide in prose. Then a second, independent model fact-checks every material claim with fresh web search before a rep ever sees it: every claim graded High / Medium / Low confidence, anything unprovable labeled unverified. Enterprise pricing: $75K/year — an 85–200x cost advantage over human research.

Congressional corruption prediction engine. GovGreed ingests eleven federal disclosure systems that don't know about each other — STOCK Act trades, Congress.gov bills, FEC campaign money, Senate LDA lobbying, SEC EDGAR, OGE executive disclosures, USASpending contracts, and market data — and cross-references them into one 233-million-record graph. The bill-investability ML model runs entirely inside PostgreSQL: no Python service, no model files. Validated at a 5.4x lift on held-out congressional sessions.

AI-native operating system for construction contractors, where California labor law is a design requirement — not a reporting afterthought. Crews clock in from a mobile app with GPS-verified selfie capture, pay accurate to the minute with zero rounding. Every clock event runs through deterministic labor-law rules, then an AI reviewer that cites the actual Labor Code section and drafts the worker message in English and Spanish. The governing law of the architecture: AI is advisor, not actor — every AI-initiated write waits for human approval, applies transactionally, and can be undone.

The only publicly available UFC analytics platform combining a proprietary fight database, a 4-dimensional rating engine, a 5-model stacked ML ensemble, and LLM-generated fight narratives. IPS built and owns the entire stack — data pipeline, ratings engine, ML training infrastructure, prediction API, and the consumer-facing website. 67.6% prediction accuracy on the held-out test set — published, with the full methodology, limitations and all.