Yan Matagne

From git log to boardroom.
How the translation works.

Every engineering team generates thousands of signals every week — commits, PRs, code reviews, deploys, incident responses. Each tells a fragment of a larger story. The problem? These fragments live in different tools and mean different things to different people. A PR titled "fix: debounce input handler" is clear to the engineer. It's opaque to the VP of Product. Here's how we bridge that gap.


01
1

Signal collection across your stack

We ingest events from every connected tool — GitHub webhooks, Linear updates, Jira transitions, CI/CD pipelines. Every event is timestamped, attributed, and contextualized. Nothing falls through the cracks, nothing requires manual entry.

02
2

Intelligent work unit detection

Raw events are clustered into work units — logical chunks that represent a feature, fix, or initiative. A single unit might span multiple PRs, several issues, and a deploy. We see the forest and the trees.

03
3

Impact synthesis and narrative assembly

Our AI produces plain-language summaries, business impact tags, and stakeholder relevance scores for each work unit. Then it assembles everything into coherent narratives — weekly reports, release notes, stakeholder updates — each shaped for its audience.


All updates

More Updates