Sentry Seer AI ✓

Seer is an AI debugger offered by Sentry. It harnesses the Sentry context - including elements like errors, traces, logs, replays, and commit history - to flag breaking changes in software, automatically discern the root cause of production issues, and propose fixes for elements that might have been overlooked.

Seer's functionalities cover every stage of the development cycle. In the development phase, Seer can be used to debug issues as soon as they arise, reducing the likelihood of flaws reaching the production environment.

During code reviews, Seer uses AI to automatically scan Pull Requests for potential mistakes that might cause significant problems in the production phase, such as security vulnerabilities, errors, and major performance bottlenecks.

It cross-references potential bugs in your PR against actual production issues to ensure the relevance of its reviews. Locating the root cause of problems in live software environment can be a significant pain point.

Seer tackles this by analyzing all available issue context, utilizing all the data at Sentry's disposal like stack traces, event history, logs, replays, traces, and profiles to locate the cause of an issue.

It can also propose a fix, leaving the ultimate choice to apply the patch to the developer. Seer also operates across different programming languages and frameworks and can be used with diverse, distributed systems.

Privacy is a priority for Seer; it does not use the data from your application, including error information and source code, to train AI models.