From problem to grounded concept — in 5 days.
Every night, the system sources and structures thousands of patents and scientific papers around your problem — the reading a research team would need weeks to do.
Each morning you spend a few focused hours on the only part that needs you: deciding what's relevant, what transfers, and what's worth building.
Classic sprints fill a whiteboard with guesses. We begin in real prior art: proven mechanisms from your field and from other industries. You react to what's been engineered, not to an empty room.
Same time-boxed rhythm you know. But every idea on the wall traces back to a real source — a patent figure, a claim, a mechanism proven somewhere else. When you present it, the evidence is already attached.
A fixed rhythm: you judge by day, the system does the heavy knowledge-work overnight — so each morning there's fresh, structured material waiting.
AI decides.
AI drives. You decide.
AI-driven doesn't mean AI does everything. It means the AI does the driving — the reading, the sifting, the drafting — while you stay in the driver's seat for every decision that matters. Not a robotaxi for ideas. A car you steer.
The AI can read a hundred thousand patents. It can't tell you which future is worth building. That's the part that stays yours — start to finish.
The problem worth solving, the question worth asking. The machine never picks the goal — it only helps you reach it.
Which sources, which directions, which ideas earn a second look. Your engineering judgment steers every turn.
Whether a concept is good enough to build is your call — never the model's. The machine proposes; you dispose.
Between those three points — the AI does the driving.
People do all the reading, searching and drafting. Thorough, but slow — and bounded by how much one team can hold in its head.
Weeks · manpowerThe machine does the groundwork at machine scale; you make every call that carries judgment. Fast and accountable.
Days · you in controlHand over the wheel, trust the black box, hope the output holds up. No traceability, no accountability, no one to stand behind it.
Fast · but driverlessUp to three worked concepts — each embedded in a rich context package of scientific papers and patents, plus a roadmap of next steps. So your development team can pick it up and continue, seamlessly, inside their own structures. The concepts themselves come in three honest kinds:
Potentially protectable — a genuinely new combination worth an FTO look and a patent conversation.
Proven elsewhere, unused by you. The most valuable find — build better and cheaper, today.
With the evidence for why. Knowing what doesn't work — and why — is part of the value.
And the next step. Your team continues straight from the concepts — and the natural follow-on is to connect them to your internal development environment and your own data (CAD drawings, material data, costs), turning the concept into a product. The sprint itself ends, by design, at a decision-ready concept — not at FTO clearance, simulation, or a prototype.
For our design sprints we combine our own tools with the best available AI models. The edge isn't any single model — it's our orchestration and analysis layer, and the fact that your confidential data never leaves your house.
Data Stays Home. The sprint processes public data only — the output is grounded concepts. Context and results are then handed over into the customer's closed systems, where the actual product development continues with the internal data.
Bring one real engineering problem. Five days later, walk away with up to three grounded concepts, the context package, and a roadmap.
No risk: start with a short call — problem, scope, price, confidentiality (NDA). Then you decide. · Pricing on request · Pilots underway, references on request.