Labelbox
Environments for training AI and agents that handle recurring engineering work
- SI Score
- 70/100
- Pricing
- Not confirmed
- Free plan
- Not confirmed
- Sign-up required
- Not confirmed
Ask SI about Labelbox
Answers use saved listing facts and recorded sources.Homepage screenshot
What it does
Labelbox builds environments that frontier AI labs train on, and runs agents that engineering and research teams hand recurring work to. Agents start on schedules, alerts, commits and API calls, then work in the background on code, infrastructure and experiments. Every run is graded, and graded sessions leave memories, notes and skills for the next session.
Labelbox is aimed at teams that keep doing the same AI and engineering work over and over. Its Recursion agents pick up jobs from tools like GitHub, Jira, Slack, PagerDuty and BigQuery, then deliver tested pull requests, incident drafts, postmortems or cost fixes. The site shows concrete examples such as a regression traced to its cause by a coordinator and five specialists, and a grader agent scoring the outcome. A careful reader should note that the homepage is heavy on agent scenarios and light on setup details, pricing and how data is handled, so those points need checking before a team commits.
- Agents start from real triggers like alerts, commits and schedules
- Every run is graded and feeds memories into later sessions
- Concrete examples across engineering, infra, security and ML research
- No pricing information on the homepage
- Setup, data handling and limits are not explained in the text
- Most detail is about agent scenarios rather than the training environments