ARA CommonsResearch infrastructure
The infrastructure for computational research
ARA Commons runs your experiments, recovers the ones that fail, and ties every result to the code and data behind it.
What the platform does
Four layers that every serious research team ends up building by hand. We provide them as one platform, on your own machines or cloud.
Scheduling
Start one run or a large batch with a few clicks or commands. The platform places each run on a machine that is free.
Fault recovery
Notice when a run fails, record why, and restart it automatically or flag it for the researcher, instead of finding out days later.
Checkpointing
Outputs are saved along the way, so work is not lost when something breaks and a run can continue from where it stopped.
Provenance
Each result is stored with the exact code and data that produced it, so it can be checked without running the experiment again.
Who uses it
Research groups at universities and R&D teams at companies, including machine-learning teams, whose experiments are the most compute-intensive. The day-to-day users are researchers and engineers. The platform works with any kind of experiment: it only needs the work to be started, monitored and recorded reliably.
How it is offered
Commercial software under a subscription, as a cloud service or installed on your own servers. Because jobs are scheduled efficiently and repeated work is reduced, teams also spend less on computing time and energy.
Published research
The platform builds on published papers, public benchmarks and open-source code from our team.
The Last Human-Written Paper: Agent-Native Research Artifacts
A structured format that packages a result with its code, evidence and full experiment history, so it can be run and checked.
Open-Endedness Bench: Measuring Epistemic Process from Agent Records
A benchmark that measures how an investigation unfolded by reading the complete record of its steps.
The Greatness of Science Cannot Be Planned: Agentic Auto-Research is Fuzz Testing
Treats open-ended exploration like fuzz testing: track what is new and what has not yet been tried.
See the platform in action
Open the demo console and click through a sample project: inspect a run, restart a failed one, compare results.
Open the demo