AI opportunity map
Identify the workflows where AI can reduce cost, accelerate revenue, improve service quality, or unlock a new product surface.
AI Strategy
Use AI where it creates leverage, not theater.
I help companies separate useful AI from expensive noise. The work starts by finding the workflow, data, and decision points where AI can improve speed, quality, margin, or customer experience.
Trust signals
- Business-first AI opportunity mapping before tool selection.
- Hands-on full-stack background for evaluating what can actually ship.
- Governance, risk, and production ownership included from the start.
LLM product design
Design agentic workflows, context systems, evaluation loops, and user experience patterns that can survive real usage.
Production readiness
Review data access, privacy, vendor risk, monitoring, cost, failure modes, and human-in-the-loop controls.
Before
Tool-first pilots
No evaluation loop
Unclear owner for risk
After
Workflow-first roadmap
Measurable quality gates
Governed rollout path
Leverage graph
What improves when the circuit is clear
Feasibility78%
Governance84%
ROI Signal72%
Common Failure
AI pilots fail when nobody owns the circuit.
A model demo is not a business system. The real work is connecting data, workflows, interfaces, permissions, review, and measurable outcomes.
Scenario map
AI pilots fail when nobody owns the circuit.
AI tools adopted by departments without a shared operating model
Prompt demos that never become reliable production workflows
No clear evaluation loop for quality, risk, or ROI
Vendor choices made before internal process and data readiness are understood
How We Work
From AI idea to deployable workflow.
We map the business process, design the AI-assisted flow, identify constraints, and then decide what should be automated, augmented, or left human.
Scenario map
From AI idea to deployable workflow.
Workflow and data inventory
Use-case scoring by value, risk, feasibility, and speed
Prototype scope for internal tools, agents, or customer-facing AI
Implementation plan with governance, testing, and rollout ownership
Motion Study
See the AI operating model in motion.
This short Remotion sequence visualizes the difference between an AI demo and an AI system: workflow mapping, data and context routing, evaluation, governance, and a production handoff the business can operate.
Map where AI enters the workflow
Route context before choosing tools
Evaluate quality before scaling usage
Wrap the system with governance and ownership
Next step
Ready to diagnose the circuit?
Bring one messy problem to the diagnostic. We will turn it into a map, a priority sequence, and a next move.
Seed-stage Founders
Series A CTOs
Product-led Teams
Scaling Startups
Technical Co-founders