$200
or 3 sessions for $500 (save $100)
You're an investor looking at a robotics or AI deal and you need a technical gut check. You've read the pitch deck, maybe had a call with the founders, but you don't have the domain expertise to know if the tech is real, if the team can execute, or if the timeline makes sense.
I've been on both sides of this conversation. I've built the technology that gets evaluated, led the teams that get assessed, and made the architectural decisions that investors should be asking about. I can help you ask better questions and interpret the answers.
Common situations:
Is the technology real or vaporware? Can it work at the scale they're claiming? What are the hard unsolved problems vs. the engineering work that just takes time and money?
Does this team have the right skills to build what they're proposing? Where are the gaps? What hires do they need to make, and how hard will those hires be?
Is the system architected to scale, or will it need a complete rewrite at 10x? Common shortcuts that become expensive later. Red flags in technical architecture.
Where are the real risks? Hardware vs. software risks. Regulatory risks. Supply chain risks. What could go wrong that the founders might not be telling you about.
How does their approach compare to others in the space? Is their moat real or imaginary? What would it take for a well-funded competitor to replicate what they've built?
I'll help you build a list of specific technical questions that will reveal how deep the team's understanding really goes. The answers (and non-answers) tell you a lot.
We'd dig into what "10x" actually means, whether their demo translates to real warehouse conditions, what the hardware BOM looks like, and whether the software stack can handle the edge cases that warehouse environments throw at you.
We'd evaluate the data moat (is their training data actually proprietary?), whether their model generalizes beyond the demo scenarios, what the deployment looks like on-site, and how defensible their position really is against well-funded incumbents.
We'd assess whether the research translates to a product, what the regulatory timeline looks like, whether they need hardware experience they don't have, and what the realistic path from prototype to production looks like.
Due diligence is often a multi-stage process. A typical 3-session arc:
All 3 sessions must be used within 2 months.