Deploysense
Link to open source: https://github.com/heyabhiraj/Deploysense
DeploySense
AI that doesn't just tell engineers what went wrong — it investigates, acts, verifies and documents it.
DeploySense is an AI Engineering Operations Agent. It closes the loop from code change
to deployment to incident resolution:
Observe → Reason → Act → Verify → Document
It reasons across **GitHub, Jira, Netlify and Notion**. **Swytchcode** is the execution
layer: it owns authentication, input validation against each tool's schema, guard
policies, endpoint resolution, retry and timeout budgets, and idempotency headers.
The problem
A change moves through GitHub → Jira → Netlify → an incident → Notion. When something
breaks, an engineer has to open five tabs and reconstruct the story by hand: which PR
caused this, which ticket it belongs to, whether it has happened before, whether to roll
back. The work is repetitive, reactive, and always done under pressure.
Traditional automation answers this with `IF deployment fails THEN create ticket`. That
creates a ticket. It does not tell you *why*.
## What DeploySense does instead
```
Deployment failed
→ read the PR, the files, the commits, the Jira issue, the deploy error
→ search engineering memory for the same failure happening before
→ form a root-cause hypothesis, with confidence derived from corroborating facts
→ score risk, explaining every factor
→ plan a response, graded by policy
→ open the Jira incident and write the Notion report
→ stop, and ask a human before touching production
→ execute what was approved
→ re-read the provider to confirm it actually worked
→ write the outcome back to Jira and Notion
```
Three properties make this more than a chatbot wired to APIs:
