AI agents for technical research that produce usable artifacts
Run research agents that inspect papers, repositories, benchmarks, docs, and datasets, then create summaries, charts, and follow-up implementation tasks.
What agents can do in this workflow
Compare technical approaches
Agents can inspect docs, papers, and repos, then summarize tradeoffs in a format engineers can act on.
Create implementation follow-ups
Research findings can become tasks, specs, or experiments inside the same project.
Keep sources with the report
Generated files, charts, notes, and citations remain attached to the workspace for review and reuse.
Continue into the product, proof, and comparison pages
FAQ
What makes a technical research agent useful?
It should read sources, compare approaches, preserve evidence, produce files, and create implementation follow-ups rather than only summarize a prompt.
Can Computer Agents inspect repositories and docs?
Yes. Agents can work with files, browsers, cloud computers, and connected project resources.
Give the workflow a persistent agent workspace.
Computer Agents keeps plans, files, tasks, runs, cloud computers, integrations, and deliverables connected so work can continue after the first prompt.