An AI agent that already knows your codebase and can query your production data and logs — pinned to the environment you're investigating. Support, QA, and engineering get to the answer on their own.
Customer reports 500 error on /api/invoices when filtering by date range before 2020.
Found the bug in src/InvoiceService.cs:142. The date parser assumes en-US format, so for dates before 2020 the two-digit year parsing lands in the wrong century — matching the FormatException in production logs.
I queried your production replica: 23 invoices are affected. Want me to draft an engineering ticket?
C:\> how it works
Your CI pushes a snapshot of your repo to Codepanion's ingest API. One line in your pipeline, any CI system.
$ curl -X POST api.codepanion.app/api/ingest/$TENANT_ID \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/gzip" \
-H "X-Commit-Sha: $GIT_SHA" \
--data-binary @repo.tar.gzWe diff against the previous SHA, embed only what changed. Your codebase is vectorized and ready in seconds, not hours.
Support, QA, and engineering ask questions in plain English. Pin the investigation to an environment and the agent searches code, queries your database, and reads logs to find answers with citations.
staging logs, /health/ready throws on a missing Redis:ConnectionString. The new CacheHealthCheck.cs:31 assumes it's set — it isn't in the staging config.C:\> capabilities
Vector search across your entire codebase. Ask questions in plain English, get answers with file paths and line numbers. Every result is a citation your team can verify.
Read-only SQL against your production replica. The agent writes queries, you see exactly what it ran. Every query is logged with a full audit trail.
Connect a log source and the agent reads it like code. It searches for the error, pulls the surrounding context, and ties the stack trace back to the line that threw it — so a QA repro and a production incident answer the same way.
Code, data, and logs are labelled by environment. Pin an investigation to staging, QA, or production and every tool defaults to it — so you're never reading prod code against a staging database by accident.
Isolation starts at the schema level. Every table carries a tenant ID, every query is scoped before it runs, and every embedding lives in its own partition. Your data stays yours because the database enforces it.
Every query the agent runs is logged and visible to you. See exactly what was searched, what SQL was executed, and what answers were given. Full transparency.
C:\> security
Codepanion is designed around the principle of least privilege. We never write to your systems.
We connect to a read replica. No write permissions, no mutations, no risk of accidental data changes.
Data isolation is enforced at the schema level. Your data never leaks across tenant boundaries.
Every agent action is logged. Review queries, search terms, and responses at any time.
We're taking early customers now. If support, QA, or engineering could get further before an issue lands on someone else's desk, let's talk.