Know what you're buying, before the price is locked in.
Independent technical due diligence for deal teams. I read the code, assess the team, and test the AI claims. You get a costed verdict your investment committee can act on.
Scoped to the stage the deal is at
Four ways in, depending on how far along you are. A quick screen before you commit resource, a targeted audit of the AI story, a full review for signing, or an ongoing technical voice for the portfolio. Every engagement is fixed fee, agreed in writing before any work starts.
AI Usage Audit
Nearly every target now claims AI makes its engineering faster, or that AI is the product. Very few buyers can test either claim. I look at what AI shipped, whether anyone reviewed it, the debt accumulating underneath, and how much of the moat is a thin layer over someone else's model.
Red Flag Screen
A fast early check before you go too far into a deal, or just want a second opinion on a codebase. Flags anything that could be a serious problem.
Full Technical Due Diligence
The full review for deals approaching signing. Everything below, costed and prioritised, in a report your investment committee can read on its own, without someone translating it for them first.
Technical Advisor, On Call
A fixed block of hours each month for a fund, a board, or a portfolio company that wants an experienced engineering voice on call, without rescoping an engagement every time a question comes up.
Hands on Senior Engineering Leader
I'm David Goodman. I've spent 20+ years in software engineering, the last 9 years leading teams of up to 50 engineers across fintech, cybersecurity and enterprise SaaS, from American Express through to scale ups and startups moving at a very different pace.
Goodman Diligence is new. I'm not. I've built the systems and run the teams that get evaluated in diligence like this, and I'll be the one on your investment committee call telling you what I found. Most technical due diligence still comes from a firm that's never shipped a line of code. Mine doesn't.
I've also led AI transformation at real organisational scale. Rolling out Claude Code and agentic development workflows, automated PR reviews and coding standards across whole engineering, data engineering and data science functions. I've had to make that work across hundreds of engineers, so I can tell fairly quickly when it's real and when it's just a slide.
First degree in Artificial Intelligence, back in 2006, before it was fashionable, with an MSc in Information Technology since.
Connect on LinkedInEvery angle I check
Every finding comes with a severity, an estimate of what it costs to fix and how long it takes, and whether it's a pre close condition or a year one budget line, so it drops straight into the model or the price conversation.
Code quality
Is it well written, easy to change safely, properly tested, and not full of duplication.
Technical debt
The shortcuts that were taken, and what they'll cost to unwind.
AI
Code shipped by AI tools without proper review, and whether the team's AI story holds up, or is mostly marketing.
Architecture
Whether the system, and the data behind it, is built to grow or just built to survive today.
Security
How secrets and access are handled, and what happens if something goes wrong.
Team
How the team is set up, and how dependent it is on any one person.
Four steps, start to report
Get in touch
Company, stage, and timeline.
Agree scope
Fixed before anything starts.
Review
Codebase, team, and systems.
Report + call
A clear verdict, walked through.
Scope, fee and delivery date are fixed in writing before any work begins, so there is no open ended meter running and nothing lands after your deadline. Every engagement is covered by NDA (happy to sign yours, or use mine) and by professional indemnity insurance. Codebase and company data are reviewed under strict confidentiality and never retained beyond the engagement.
Built for decisions where being wrong is expensive
The fee is a rounding error against the deal. Finding out after completion is not.
Private Equity
Costed findings you can take into the price discussion, put in the SPA, or use to walk away. Buy side or vendor side, mid market deals and bolt ons.
Venture Capital
Find out whether the engineering story, and the AI story in particular, matches the repository before the term sheet becomes a wire.
Corporate Acquirers
Catch what is expensive to fix after close, and understand what integrating it into your own estate will really take, while it is still the seller's problem.
Founders Preparing to Raise or Sell
See what a buyer's diligence will find, while there's still time to fix it or frame it.
Got a deal on the clock, or one coming up?
Based in the UK, working on deals wherever they are. Replies within one business day.