Launched this week

Tetriz Engg Intelligence + Connectors

Launched this week

Connect coding sessions to PRs, issues, quality, and ROI

33 followers

Connect coding sessions to PRs, issues, quality, and ROI

33 followers

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Open-source engineering intelligence across GitHub, Jira, and 7 more tools. Understand work complexity, spot likely sources of bugs, and compare AI-assisted work with the rest. Connect coding sessions to delivery and measure ROI with quality factored in.

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Launch tags:Open Source•Developer Tools•Artificial Intelligence

Launch Team / Built With

Maker

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Hey Product Hunt, Your engineering tools record a lot of what happens. Understanding why work takes longer, where bugs come from, or whether AI is helping still takes a lot of digging. You end up piecing together PRs, issues, reviews, and coding sessions to answer questions about your own team. We’re open-sourcing 2 repos to make that easier: Tetriz Connectors brings in engineering data from GitHub, Jira, and 7 more tools. It handles the collection layer that engineering analysis depends on. Tetriz Engineering Intelligence uses that data to understand what your team delivers: work type and complexity relative to your repo, changes that likely introduced bugs, and work moving across branches without counting it twice. It also helps assess where your team gets stuck across the AI development lifecycle. Connecting coding sessions adds another layer. You can trace sessions to the PRs they helped produce and the issues those PRs delivered, with evidence for each match. That lets you compare AI-assisted work with the rest and factor quality into ROI. Our earlier releases helped teams understand sessions (https://www.producthunt.com/prod...) and improve agent setup (https://www.producthunt.com/prod... ). These help you see whether those improvements carry through to delivery, and decide where to focus next. Both repos are MIT-licensed. You can inspect the code, examine how the measurements work, and build on them. What engineering question would you want to answer first with your own data? Engineering Intelligence :https://github.com/tetriz-ai/tet... Connectors : https://github.com/tetriz-ai/tet...

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1d ago

The problem is real, another version can be figuring out the time estimation. After AI, the time estimate, and ROI estimate is kind of broken. a task which used to take 5 days to finish, now can be finished in 30 minutes with AI but testing, revewing parts can take huge time. also a task which usually took developer to finish 5 minutes(as he had full context), now can take a day to finalising, understanding, testing, etc.

so question is how accurately does it do this.

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1d ago

Maker

@rajendra_prajapat We have done a lot of iterations precisely to get these metrics & estimates as accurate as possible and cover many of the real world scenarios that are not captured by simple computations. We relied on actual software development work done by our team as well as a bunch of design partner organisations spanning diverse domains and team sizes to define and tweak the logic for these metrics. Won't claim it is perfect but you will find it to be of high value; not to mention given that it is open source we can now get external contributions to further improve them :-)

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7h ago

Congrats on the launch! Tying coding sessions back to PRs and actual ROI is the piece most eng teams still can't show their CFO. Curious how you attribute ROI when one session spans several PRs or issues. Rooting for you.

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1d ago