Research that turns into action, not archives.

Upload your reports. Get a living insight graph that builds journey maps, personas, and recommendations automatically — so your team spends time acting on research, not re-reading it.

Your research repository is a graveyard, not a resource.

Most research tools are built report-first: you upload a study, tag some insights inside it, and move on. Six months later, nobody remembers it exists. The next person with the same question re-reads three old decks instead of getting an answer.

The problem was never tagging. It's architecture. If insights live inside reports, your repository can only ever be as good as someone's memory of what's in there.

We built this differently: the insight is the primary object, not the report. Every report you upload strengthens a single connected graph — insights get reinforced, contradicted, or connected across every study you've ever run. Reports pile up. Insights compound.

From raw report to actionable synthesis in minutes, not weeks.

Every research team has felt this: the study is done, the interviews are transcribed, and then the real work starts — synthesizing findings into something a stakeholder can actually use. That's the part that eats a week.

We collapse it. Upload a report and get atomic insights, evidence-linked back to source, dimension-tagged, and ready to act on — automatically extracted, not manually assembled.

Stop storing reports. Start building a graph.

Traditional repositories: report in, report sits, tags live inside it, next report starts over.

Ours: report in, atomic insights extracted, each one linked to every other insight it supports, contradicts, or builds on — across every report you've ever uploaded, indefinitely.

Journey maps that build themselves.

Journey mapping is normally a workshop: sticky notes, a whiteboard, someone's best guess at stitching together six interviews into one narrative. It's slow, it's subjective, and it goes stale the moment new research lands.

We generate journey maps directly from your insight graph — every step populated with real evidence, filterable by segment or team, updated automatically as new research reinforces or contradicts what's already there.

Personas grounded in evidence, not a workshop's best guess.

Personas usually calcify the day they're created — a snapshot of what was true at one meeting, never updated again.

Ours regenerate from live insight data. Every persona narrative is built from the actual evidence behind it, with inline references back to the insights that inform it — and a one-click regenerate whenever the graph learns something new.

Your analytics and your interviews, finally speaking the same language.

Everywhere else, qualitative and quantitative research live in different tools, different formats, different conversations — a researcher has to manually connect "conversions dropped 23%" to "users told us the CRM step was confusing." That connective work rarely happens, and when it does, it's ad hoc.

We treat both as the same kind of evidence. Drop in a GA4 export or a suggestion-box spreadsheet alongside your interview reports, and get a single, unified insight graph — statistical anomalies and qualitative findings, evidence-linked side by side, not siloed in separate tools.

Who this is for

Most repositories help you store research. We help you act on it.

Your next research question already has an answer. You just haven't connected the dots yet.