Research with a rigorous method.
One applied programme, Reliable Enterprise Autonomy, being established with four tracks. Each track has a question, a first experiment and an output. The programme is funded from a fixed monthly budget, reviewed each month.
Why we are building it
Every engagement produces questions the field has not answered: when does a verifier reduce false completion, which memory designs resist poisoning, when is a checkpoint worth its cost, when does a smaller model suffice. We will run the experiments, publish the method and the limits, and bring the results back into delivery. Research is how the Systems unit's toolkit improves; it is not a separate business.
Later tracks, with entry conditions
- Post-training and reinforcement learning
- begins only when legitimate training data exists, a held-out benchmark is defined and a no-training baseline is in place.
- Physical AI and robotics
- begins only with a domain partner, a safety specialist, legitimate operational access and a funded experiment. Starts in simulation.
- Multimodal and voice
- begins with a customer use case, with benchmarks only on permitted data.
- Frontier pretraining
- not planned.
Publication standard
Every published result includes its question, baselines, data provenance, repeat counts, uncertainty, negative results and limitations. Each report is reviewed by someone who did not build the system. Negative results are published. A report that reproduces known engineering practice is labelled an engineering report, not research.
Evaluation standard →Work with the programme
We run experiments on customer workflows only with written permission and on permitted data. If you have a workflow and a question, write to research@chainfore.com.
Research collaboration →