Execution is cheap. Claude Code builds an MVP in a weekend. The scarce resource is knowing which MVP is worth building. Project Red Car gives you a battle-tested research methodology that finds newly-viable B2B opportunities by scanning for the intersection of real pain, urgency drivers, and AI capability unlocks.
You probably can't answer that - because you weren't looking. The same thing happens with opportunities. Once you know the pattern to look for, you start seeing them everywhere.
Right now, in industries you've never thought about, people are describing painful workflows they repeat every week. Regulations are forcing change. AI costs just dropped below the threshold that makes a solution viable. The opportunity is sitting there - you just don't know to look for it yet.
Project Red Car puts it on your radar.
Every opportunity gets the same treatment - three-signal validation, then five kill checks. Most ideas die. The ones that survive are worth building.
QuickPrice already offers the near-identical product. ServiceM8 has full AI quoting live. Jobber shipped AI quote drafting in 2024.
eco-Landlord, backed by DESNZ (government), offers essentially the same tool - for free. Can't compete with government-funded.
Lawhive raised €50M Series B (Google Ventures). Luminance has 1,000+ enterprise customers. Robin AI collapsed despite $10M ARR - cautionary unit economics.
Microsoft Copilot native in Teams. Google Gemini native in Meet. Otter, Circleback, Granola, Fireflies all well-funded. Platform incumbents already shipping.
Planda offers AI planning insights from 10M+ records. Government hired Google Cloud for £6.9M to build AI planning tools. Multiple competitors active.
Real people describing frustration with specific workflows. Forum posts, Reddit threads, app reviews. Not hypothetical. Scored 0.0-1.0.
Something external making the problem impossible to keep ignoring. A regulation deadline, rising costs, labour shortages, tighter competition, higher customer expectations. Not hypothetical - measurable today.
Something that became possible in the last 12-18 months. Model cost dropped, new API launched, structured output became reliable. The "why now."
Then five kill checks: platform dependency, incumbent AI roadmap (last 6 months), moat timeline (18mo minimum), test data availability, and distribution access. Most ideas die here.
Fill in your profile. Get a personalised opportunity research prompt with the full methodology, stress tests, and validation checks. Paste it into Claude deep research. Get results in 10 minutes.
Every week we scan sectors, validate signals, and go deep on the survivors. Choose the level of intelligence you need.