ventures, [r]ethought.
Seasoned operators obsessed with problems worth solving.
AI gives us speed. Experience gives us judgment.
Tech execution is no longer the hard part. AI solved that.
The bottleneck is now knowing what to build and having the grit to sell it. We talk to customers before we write a line of code. We kill what isn't working before anyone gets attached. We do things that don't scale until we find the signal worth scaling.
Every company we build is AI-native from Day 0. Not AI as a feature. AI as the foundation. And every venture makes the next one sharper.
from signal to scale.
Four phases. Each earns the right to the next. Most ideas don't survive phase three, and that's how the studio gets smarter.
AI absorbs market signals at a pace no analyst team can match: competitors, regulation shifts, pricing patterns, user sentiment. It surfaces connections humans would miss. But seeing a pattern isn't the same as choosing a battle. Operators decide where timing, pain, and capability intersect. That's taste, not data.
The gap between "I wonder if..." and "let's find out" used to be weeks. Now it's hours. AI generates code, scaffolds experiments, and builds testable prototypes while operators own the architecture and the question behind it. Don't polish. Get it in front of real people and see what happens.
This is the most human phase. Manual onboarding. Hand-written emails. Sitting across from a customer and hearing what they're not saying. AI synthesises the signals (clusters objections, spots patterns in feedback) but humans feel the signal first. No dashboards. Just conversations that change the product.
The studio's edge is optionality. Validated pull gets capital, team, and infrastructure. Everything else gets killed fast, before sunk-cost thinking sets in. Every shutdown feeds learnings back into the engine: reusable code, customer research, operational playbooks. Nothing is wasted. The next venture starts from a higher baseline.
obsessed with a problem worth solving?
Talk to ussmall crew. compounding output.
Headcount is not a proxy for ambition. We run AI agents across every stage of the venture lifecycle: research, prototyping, validation, distribution. We keep a tight crew of operators focused on the decisions machines can't make.
AI handles throughput. Humans handle judgment. The result: ventures that get our full commitment, each compounding what we know. Constraints sharpen us. Speed compounds.
what we're building.
We go deep, not wide. Every venture gets our full conviction, until the market tells us otherwise.
deetech.ai
AI-powered deepfake detection and forensic media analysis engineered for real-world insurance claims.
voxie.ai
AI qualitative research at scale. Runs hundreds of video, voice, and chat interviews simultaneously. The depth of a 1:1 conversation, the reach of a survey.
who's behind this.
Mind, heart, and soul in every venture we build.
PhD candidate in AI. Spent a decade in strategy consulting, analytics, and M&A before building [r]think. Now obsessed with turning operator judgment into scalable products.
We're looking for someone who knows their industry cold and has the commercial grit to sell before the product is polished. Deep sector expertise, a nose for real pain points, and the endurance to grind through early revenue. You've closed deals, not just decks.
Featured articles
Why We Built deetech: Insurance Has A Deepfake Problem
The industry processes billions of images a year on the assumption that photos don't lie. Generative AI has broken that assumption.
Read article
Built For Fire Season
The AI correction is coming. Venture studios were designed for exactly this moment: disciplined iteration, lean teams, and the ability to commit fully when the signal is clear.
Read article
Why We Are Building A Venture Studio
After years building service businesses and helping corporates launch startups, AI opened the window. The studio model is how we walk through it.
Read article