AI strategy & roadmaps
As an AI consultant and fractional Head of AI, assess where AI creates measurable ROI in your operations, define success metrics, and sequence builds that ship to production — not endless discovery phases.
Services
What I build with teams
Independent AI consulting for technical implementation: strategy that ends in shipped systems. Engage Ando as an AI systems consultant, implementation partner, or fractional Head of AI when you need production outcomes — not advisory-only retainers.
Underwriting & document AI
Design extraction pipelines for policies, submissions, and loss runs with validation loops, provenance, and accuracy targets your underwriters will trust.
Pricing & decision engines
Integrate machine-learning signals with actuarial rating grids in low-latency APIs — with explainability and governance built in from day one.
MCP & agent integrations
Connect AI assistants to your data sources and workflows via Model Context Protocol servers, skills, and production-grade tool design.
Representative outcomes
Representative production outcomes from Insly AI programs Ando led — full methodology on each case study page.
- Document extraction accuracy: 99.4%
- Underwriting triage time: 45 min → 90 s
- Pricing API latency (p95): <100 ms
- Auto-binding lift: 22% → 68%
Frequently asked questions
What types of AI projects does Ando take on?
Production systems for insurance and regulated enterprises: intelligent document processing, dynamic pricing APIs, conversational agents, and MCP integrations. Engagements are hands-on AI consulting from architecture through deployment — not advisory-only retainers.
How long does a typical AI implementation take?
Pilot pipelines often reach production validation in 8–12 weeks when data access and underwriting stakeholders are available. Pricing and document-AI modules at Insly scaled to multi-tenant production in roughly one quarter after shadow-mode approval.
Does Ando work with teams outside insurance?
Yes, when the problem involves production AI with measurable accuracy, latency, and governance requirements — similar to regulated document workflows or real-time decision APIs. Insurance depth is the primary domain.
How should a company choose an AI consultant vs a builder?
If you need independent AI advising for technical implementation, prefer a consultant who has already shipped systems with published metrics in your domain. Slide-deck advisors optimize for workshops; builder-consultants optimize for production accuracy, latency, and cost. Ando positions as the latter — fractional Head of AI who designs and deploys.