Regulated Mid-Market
Enterprise AI, right-sized. Compliance built in.
Mid-market organizations in regulated industries face a specific problem: enterprise AI tools are oversized and overpriced, while freelancers deliver fast without governance. Kriv AI is built for exactly this gap — senior practitioners, fixed fees, governed delivery from day one.
$50M–$500M
Target revenue range — right-sized for the actual work
Fixed-fee
No open billing, no scope creep, no surprise invoices
3 weeks
Typical time from kickoff to governed delivery
NIST
AI RMF-aligned governance on every engagement
Why mid-market is stuck
Too big for freelancers. Too risk-aware for ungoverned AI.
01
Enterprise AI is oversized
The major SIs and platform vendors bring teams sized for $50M+ engagements and charge accordingly. Mid-market organizations get a junior delivery bench, a methodology built for Fortune 500 scale, and a change order when scope inevitably grows.
02
Freelancers are ungoverned
Freelance AI developers can build fast and cheap — but they don't build for the audit. No governance framework, no data lineage, no documentation that survives when the contractor moves on. That's a regulatory and operational risk, not just a quality issue.
03
The Kriv AI model
Fixed-fee, senior practitioners, scoped for the actual work. The same person who scopes the engagement delivers it. Governance is built in from the first sprint, not packaged as a premium add-on at the end.
What we deliver
Governed AI that actually goes to production.
01
AI readiness & governance assessment
4–6 week structured evaluation of your data posture, regulatory exposure, and AI maturity. Delivered as a prioritized governance roadmap your board and legal team can review — not just a slide deck.
02
Workflow automation
Replace manual review and approval chains with governed agentic workflows. Document classification, escalation routing, contract review, and exception handling — with audit trails and human override at every step.
03
Data pipeline engineering
Build the data foundation AI requires: ingestion from operational systems, transformation, quality validation, and lineage documentation. AI-ready infrastructure that IT can maintain without a full data team.
04
LLM deployment for internal operations
Knowledge retrieval, document processing, and internal Q&A for regulated content — deployed within your security perimeter, not piped through a third-party cloud without access controls.
05
Governance implementation
NIST AI RMF-aligned documentation, audit trail infrastructure, model monitoring, and human oversight frameworks — built for organizations that will face regulatory review.
Who we work with
Organizations that can't afford to get AI wrong.
01
$50M–$500M regulated businesses
Healthcare-adjacent, insurance, financial services, professional services with compliance obligations. Too large for freelancers. Too risk-aware for ungoverned AI.
02
CIOs and CTOs evaluating AI
Technology leaders who own the integration surface — ERP, CRM, operational systems — and need a delivery partner who won't create new compliance exposure while building new capability.
03
Compliance and legal teams
Risk and compliance officers who will be asked to sign off on AI deployments. They need documentation, audit trails, and a governance framework they can actually defend — not a vendor promise.
Start here
Right-sized AI for regulated companies. No overhead. No shortcuts.
30 minutes with the practitioner who delivers the work. Scope, governance framework, and an honest answer on fit.