Where AI actually pays off

I spent years building strategy and analytics for enterprises — McKinsey, private equity, insurance, automotive, travel. Then AI changed the economics: what used to need a big team and a big budget now needs a clear use case, an API, and someone who can actually build it.

But most of it fails — MIT puts GenAI project failure around 95%*, almost always the wrong use case or no honest ROI. My job is the opposite: cut through the hype, find where AI genuinely pays off in your business, prove the return, then build the working software myself — not another deck.

Want proof? The Portfolio has live, clickable tools I've built — an FP&A revenue forecaster, a document-extraction engine, a private-equity market-scan — plus my own AI products with real users. Don't take my word for it; click one.

Book a free discovery call → See the portfolio →
10+ tools built
3 AI products live
Ph.D. business admin

What I do

One person across the whole arc — from process analysis to production. See how I work →

  • 01

    AI & Data Strategy

    Where AI genuinely pays off, sequenced into a plan you can act on. The ex-McKinsey lens — business case, priorities, risk — before a line of code gets written.

    • AI audit & maturity read
    • Prioritised opportunity roadmap
    • Exec-level AI advisory
  • 02

    AI Opportunity Audit

    A fast maturity read and prioritised opportunity map — fixed scope, honest verdict. The free 30-minute entry point.

    • Data & workflow review
    • Prioritised opportunity map
    • Clear next steps
  • 03

    Data & FP&A Analytics

    Forecasting, driver and revenue analysis, financial planning that holds up — from data engineering to the model.

    • Revenue & driver forecasting
    • Planning & scenario models
    • Data engineering to model
  • 04

    AI Build & Automation

    I don't just advise. LLM workflows, document and data extraction, custom tools — designed, built and deployed.

    • LLM workflows & agents
    • Document & data extraction
    • Custom tools, in production

You don't have to

  • Wait months for a strategy deck while nothing ships
  • Stitch together five specialists who blame each other
  • Pay for advice, then go find someone to build it
  • Bet on a use case nobody proved would pay

Instead, you could

  • Get an honest read in a free 30-min audit, a working prototype in days
  • Work with one person across the whole arc — process to production
  • Have whoever picks the use case also build and ship it
  • Only build what the ROI case actually justifies

Tools I've shipped

Not slides — working software you can click. A few here; the rest are in the Portfolio.

See all in the Portfolio →

* MIT NANDA — The GenAI Divide: State of AI in Business (2025). ~95% of enterprise GenAI pilots showed no measurable P&L impact. Source ↗