Make your AI agents stateful and intelligent.
Observability, memory, and auto-PRs for AI agents.
Works with
telemetry · flowing through your agent topology
Trace.
Every LLM call, tool call, handoff, span — captured with cognitive signals other tracers miss.
Remember.
Past failures and accepted fixes recalled before the next decision. The brain compounds.
Fix.
When something breaks, AgentDog drafts the PR. You review and merge.
Plugs into the agents you already build.
Auto-instruments every popular framework. JS, Python, and Go SDKs. One line to install — your existing code keeps shipping.
JS / TS
npm install @agentdog/sdk
Python
pip install agentdog
Go
go get github.com/agentdog/go
Auto-instruments
Routes to your tools
Slack
alerts + digests
Linear
issue creation
GitHub
fix PRs
alert routing
MCP
memory + ops
Every run sharpens the next.
Each dot is a memory your agents distilled from production.
Hover one to see what they learned.
Watch every run. Remember every fix. Ship the next one for you.
One closed loop, four steps. Trace what your agents do, give them a memory of what went wrong, and let AgentDog open the PR when the fix is obvious.
Trace every call.
Every LLM call, tool call, handoff, and reasoning step — captured with the cognitive signals other tracers miss.
Agents stop repeating mistakes.
Past failures and accepted fixes are recalled before the next decision. The brain compounds across every run.
Your context, everywhere.
Personal memory that travels across Claude Code, Cursor, Codex, Zed, and JetBrains. Save once, recall everywhere.
Fixes arrive as pull requests.
When something breaks in production, AgentDog opens a PR with the fix and the test plan. You review and merge.
Questions engineers ask.
One init() call auto-instruments your AI agents — every LLM call, tool call, handoff, and reasoning step. Detectors flag failures, the brain remembers them, and when something breaks AgentDog drafts the pull request. End-to-end loop, not just a dashboard.
Three B2B tiers — Startup, Growth, Enterprise. Per-seat plus a trace allowance, anchored to team size. Exact pricing publishes at GA. No free individual tier — this is a team product.
Telemetry, memories, and PR drafts in our managed cloud. Encrypted at rest and in transit with industry-standard algorithms; per-tenant isolation at the database level. Storing the actual prompt and completion content is opt-in per agent — off by default.
Custom agents are fully supported through our JS, Python, and Go SDKs. If your setup is unusual, get in touch — we'll work with you to make it fit.
Never. We draft pull requests against a branch you control. A human always reviews and merges. Auto-merge is intentionally not on the roadmap until customer demand outweighs the risk.
Nobody else is building agents that learn from their own production. Observability tools hand the data to your engineers — you stay in the loop forever, fielding the same incident twice. AgentDog hands the data to the agent. Past failures, accepted fixes, and recurring patterns flow into the agent's own context before its next decision, so it self-corrects. Six months in, your agent has caught and fixed things a fresh install never could — and your team has stopped doing the same triage twice.
Our mission
Make AI agents stateful and intelligent — so they stop acting like the black boxes they are today.
Ship reliable agents.
Join the waitlist.