Software that improves.
Intelligence that learns.
Build, ship, learn from real usage, and improve. All in one connected platform.
Explorer
The problem
Your tools don’t share what they know.
The error is in one tool, the trace in another, the code in a third and the customer impact in a fourth. Every person, and every agent, rebuilds that picture by hand before anything gets fixed. Most of what a release could teach you is lost between them.
The loop
Every release teaches the next one.
- 01BuildYour team and coding agents
- 02TestQA agents on web and mobile
- 03ShipCI builds what changed
- 04ObserveErrors, traces, infrastructure
- 05UnderstandWhat customers actually did
- 06LearnYour team decides what to change
- 07ImproveAgents make it, people approve it
- In the product today
- People decide, agents assist
- Research
See it work
One turn of the loop.
Checkout errors climb. The trace shows the payment gateway failing and being retried.
Use it today
Start with what you need.
Research
AI that gets better with experience.
Today’s AI is a few large, general models that are expensive to run and the same for everyone. We are researching efficient, specialized models that learn from the work they do, and could become intelligence that belongs to a person or an organization.
Why trust us
Real software, shipping every week.
We built the stack underneath
Our own build system, remote cache, hosted Git and a server for every branch. When something is slow, we can fix it at the bottom.
How builds workReasonOS ships ReasonOS
Our own code is built, tested, reviewed and released on the platform, with our own agents working in it.
Read the changelogResearch with a technical record
Each result lists its objective, method, baseline, limitations and how to reproduce it.
Inspect the resultsLatest releases
All releasesProduction
Infrastructure monitoring
See hosts, clusters, nodes, workloads, pods and volumes next to your traces and logs, with built-in alerts such as a disk filling up.
Production
Agent traces
Follow each model call, tool call and its cost in a coding agent’s run, in the AI section of Observe.
Production
Observe and Understand
Logs, metrics, traces and errors in Observe. Product analytics, session replay, feature flags and experiments in Understand.
Enterprise
AI agents under your control.
Single sign-on
SAML or OIDC through your identity provider. Two-factor is on by default.
Custom roles
Allow and deny rules for people, teams and service accounts.
Audit log
Every sign-in, push, merge, permission and secret change, with who did it.
Agents under your rules
Agents get the same permissions, required checks and reviews as people.