Figment reads the world's signals and finds the opportunities worth building. The Foundry turns them into products — and the best into companies. One loop, operator-funded, approaching full autonomy.
A topic that shows up across several sources at once counts as a stronger signal than a search spike alone.
26 feeds read daily · 8 more ready to switch on. Hover or tap a category.
See a trend in Tokyo before it lands in San Francisco. Figment follows each trend across 65 countries, learns the usual routes and the days between stops, and predicts where it goes next.
A hop is a new week the trend broke out somewhere new (interest 50+ out of 100).
Growth that holds week over week, in more than one country.
Each product line pitches ideas that fit what it already does.
Every idea is scored on how much of our platform it reuses.
A reviewer flags the mediocre ones, so only the strongest survive.
Insurance stayed one of the steadiest searches of 2026: US searches for car insurance quotes rose about a quarter from winter, and “insurance denial” peaked in May. PoliSays reads home and auto policies section by section in plain language, quoting every clause.

Daily scans across search, news, papers, filings, launches and social — in 65 countries.
Scout agents pitch ideas per product line; a skeptic agent kills the mediocre ones.
Figment writes a buildable blueprint mapped to tech the studio already owns.
The Foundry assembles product, ops, marketing and support from shared agents.
Live on a real domain in weeks, measured against the thesis that started it.
Echo feeds real results back into Figment's reviewer, so every launch sharpens the next pick.
Once a company is live, its users keep shaping it. In a client's implementation of our Agent Studio, a user records a thought. A relay of our agents takes it from voice note to a live update, with no tickets and no hand-offs.
Most tools cover one piece: feedback, tickets or code. This runs from the spoken note to the live change.
The person who asked hears back in the app, and every exchange is kept.
Results flow back to Athena, our learning engine, which shapes future plans.
Longer if the next sprint is already full.
Built, tested and deployed.
"The save button is hard to find on my phone. Could it stay at the bottom?"
"Done. The save button now stays at the bottom of the screen. Thanks for the note."
A user records a voice note about the product, right inside the app.
The note is transcribed and sorted into bug, new feature or usability.
Everest, trained on many hours of product and UX teaching, shapes the request into a spec. It lands on the task board with test steps.
A skeptic pushes back before anything is built: is this the right fix?
The change is designed and built, then checked against the spec.
Every change is scanned for security issues before it ships.
It goes live, and the user gets a plain-language note in the app saying it's done.
What worked and what broke becomes a rule, so the next request goes faster.
The flow is shown as designed. Live counts of requests and time to ship will appear here once we track them.
A thesis that survives scrutiny gets built the same week.
Each company starts on tooling the studio already runs in production.
Outcomes train the reviewer; the hit rate is designed to rise over time.
AI venture studios are now a real category. Here's what only this loop does.
Most studio tools stop at a plan or a pitch. We take ideas to live products and registered companies.
Waves follows one trend country to country and predicts where it lands next. We haven't seen anyone else do this.
CallOrPut, PetConnect and AlienSquad are registered companies, PoliSays is forming, and every studio product is live on a real domain.
Ideas are ranked by how much of our own platform they reuse, not by generic market size.
First Seen logs when each signal appeared, so results can be checked against the date we spotted it.
Not a single US source: search, news, research, launches and social across 65 countries.