Execution, not ideas.
We build embedded AI solutions for regulated industries - engineered to run in production, integrated with the systems your business already depends on.
Areas of focus
AI projects fail more than they succeed.
We build the ones that ship.
Life Sciences
Embedded AI for regulated life sciences workflows - built to survive contact with validated systems.
5 practice areas · 17 use cases
Private Equity
AI capability built once and deployed across the portfolio, templated for how PE operating teams actually work.
6 practice areas · 17 use cases
Legal
AI embedded into the matter - document workflows and firm knowledge, built for matter-level economics.
3 practice areas · 10 use cases
Logistics
AI built into freight operations and trade documentation, designed to fit the systems and crews already in place.
4 practice areas · 10 use cases
Approach
Readiness → Build → Operate.
A sequenced engagement model. A paid readiness phase de-risks the build phase. A build phase delivers a working solution at one part of the business. An operate phase keeps it working - owned by you, or run by us, depending on the engagement.
How we workSelected work
What we've built.
- Case study Read
Agentic recruitment and candidate sourcing platform
A live, LangGraph-orchestrated multi-agent platform that turns a hiring need into a ranked shortlist across four talent sources, with one-click human approval.
- Case study Read
Multi-agent competitive intelligence platform for life sciences
A multi-agent platform in active client use that turns competitor, regulatory, and clinical signals into a single structured, ranked digest.
- Working prototype Read
RAG-based legal intake and AML/KYC assessment platform
A RAG-based intake platform that scores new matters against current AML/KYC requirements, grounds every flag in cited evidence, and preserves a traceable record of each decision.
FAQ
Direct answers.
Short answers to the questions buyers and search engines ask.
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What does Genitive.AI do?
- We build embedded AI solutions for regulated industries - life sciences, private equity, legal, and logistics. Embedded means the solution integrates with the systems your business already depends on, not a standalone tool the team has to remember to open.
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What industries do you work in?
- Four areas of focus: life sciences (deepest prototype coverage, building toward a domain platform), private equity (fund-level build-and-run thesis), legal (litigation workflows, knowledge management), and logistics (freight operations, trade documentation).
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What does "embedded AI" mean?
- AI that lives inside the systems your operators already use - CRM, DMS, TMS, data warehouse, case management - at the point of decision. Not a separate portal, not a sandbox demo. Harder to build, but it survives contact with the business.
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How does an engagement work?
- A four-stage sequence: Readiness (a paid 4-6 week data and process audit), Build (the first working solution at one part of the business), Operate (client-owned or Genitive-operated, depending on the engagement), Expand (template the playbook). Each stage funds the next.
Talk to us about your first use case.
The fastest way to know whether an embedded AI solution fits is a 30-minute conversation. No deck, no pitch - we will ask about your operational reality and tell you honestly whether we are the right fit.
Start a conversation