Research and analysis, automated — by the person who builds it

I have spent twenty years working with numbers and sources. At McKinsey I worked in corporate finance and equity research; later came commercial due diligence and strategy projects; since 2016 I have been freelance, doing FP&A and data analytics for technology, insurance and automotive companies. Then AI changed what is worth doing: 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 work on

Working together always starts the same way: a free 30-minute opportunity audit, then the plan, then the build. I do all of it myself — from the first conversation to the software that keeps running. See how I work →

  • 01

    Financial Analysis & FP&A

    Forecasts, revenue and driver analysis, planning that holds up — from building the data foundation to the finished model. I automate the calculations and reviews a finance team otherwise does by hand.

    • Forecast revenue from its main drivers
    • Build planning and scenario models
    • Prepare the data, develop the model
  • 02

    Knowledge from Documents

    What sits in the building but nobody can find: contracts, reports, minutes, old project folders. I make your documents searchable and build an AI that answers questions about them and names the source for every answer.

    • Open up documents and make them searchable
    • Answer questions about your own documents
    • Back every answer with its source
  • 03

    Research & Market Analysis

    I automate the research: competitor landscapes, company profiles, continuous market monitoring — with a source cited for every claim. The methods come from commercial due diligence and equity research, turned into software.

    • Automate the research behind a commercial due diligence
    • Monitor market and competitors continuously
    • Back every answer with its source
  • 04

    Processes & Automation

    The recurring steps someone still does by hand today: reading documents, merging data, checking results. I don't just advise — I build the thing and hand it over ready to run.

    • Build LLM workflows and agents
    • Extract data from documents
    • Develop custom software and put it into operation

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 ↗