Old data acts like an anchor on system performance. When you are processing thousands of commits, Jira tickets, and CI runs every day, the raw data adds up quickly.
Solidmatics is built to give leaders a clear, plain-language read on whether their engineering team is actually producing value. To do that, our AI layer ingests a massive amount of workflow history. Holding onto the raw, bloated payloads of a 180-day-old continuous integration run does not help you understand what your team shipped yesterday.
We just released an automated background purging system to keep our infrastructure lean and your daily reports fast. 🧹
Shedding the dead weight
Code repositories and project management tools generate an enormous amount of noise. We analyze it, extract the meaning, and then the raw material becomes obsolete. We implemented a scheduled system that silently drops this stale data during off-peak hours.
Here is what the system handles behind the scenes:
- CI data and raw payloads: We now automatically null out heavy payload columns, like raw patch files from pull requests, after 90 days. The historical record remains intact, but the massive files disappear.
- Stale chat transcripts: Our AI agent threads and chat transcripts are now purged after 30 days of inactivity. If a conversation is over, we stop storing the raw tokens.
- Off-peak scheduling: All of this runs silently in the background when server loads are lowest, ensuring zero impact on the delivery of your morning reports. âš¡
Speed and clarity
You do not need a massive archive of old code payloads. You need to know if your team is on track today. 📊
By dropping the dead weight, we ensure our database queries stay incredibly fast. The insights and historical performance metrics you rely on remain completely untouched. We simply remove the raw data that no longer serves a purpose.
The result is a sharper, faster AI layer that delivers the truth about your engineering output, exactly when you need it. 🚀