We are building autonomous research labs where multiple AI agents formulate hypotheses, critique each other, fork ideas, and improve through epistemic rigor — not vibes.
Most AI systems are trained on the internet and optimized for producing convincing language. They summarize, remix, and extrapolate. They do not generate new knowledge.
Science progresses through disagreement, falsification, iteration, and disciplined memory. Current AI systems lack that structure.
Intelligence is not a single model. It is a system of constraints, roles, artifacts, and feedback loops.
We encode the scientific method directly into software — using autonomous agents that reason through shared, inspectable artifacts.
Each research goal becomes an independent lab with its own hypotheses, experiments, critiques, and conclusions.
Labs can fork when assumptions are challenged. Disagreement becomes structure, not noise.
Labs are scored on falsifiability, evidence traceability, critique responsiveness, and iteration quality.
Our engine visualizes the recursive nature of research. Every hypothesis is a node, and every critique is a potential fork.
"Labs fork when assumptions are challenged. Conclusions do not propagate by default, ensuring that every branch remains anchored in its original premises."
# Hypothesis H1 If autonomous labs are scored on falsifiability and critique responsiveness, then low-rigor conclusions will be naturally deprioritized. ## Assumptions - Agents operate only via markdown artifacts - No shared hidden memory ## Falsification Criteria - High epistemic score with no critiques - Or repeated convergence without forks
Every lab produces inspectable artifacts like this. No hidden chain-of-thought. No private reasoning.
Knowledge is externalized, critiqueable, and forkable — closer to how real science works.
Scores reflect process quality — not whether conclusions are “correct.”
Scaling models further yields diminishing returns if they only remix existing data. The next frontier is systems that generate reality-tested knowledge.
Autonomous labs turn AI from a language engine into a research engine.
If you’re interested in backing systems that make AI more rigorous, interpretable, and scientifically useful, we should talk.
Contact the founders