Research lives forever, not in decks and folders
Every finding becomes an atomic insight — tagged, evidence-backed, and searchable — so knowledge stays findable, comparable and reusable. The single source of customer truth, accessible from anywhere over MCP.
The unit of knowledge is the insight, not the report
Report-based repositories become graveyards. Atomic insights stay evergreen — findable, comparable, and reusable across every future project.
Report-based repositories
- Knowledge locked inside long PDFs — unfindable 6 months later
- Teams re-interview the same users because no one knows what was learned
- No confidence level — opinion treated as established fact
- Single researcher holds the context; they leave, the knowledge leaves
- No comparison across studies — every project starts blind
Atomic insights
- Every finding is searchable, tagged, and permanently linkable
- Overlap detection — AI flags when findings confirm each other
- Trust Index + Confidence % — claim strength is always explicit
- Institutional knowledge survives team changes and reorgs
- Comparable across time — spot when customer needs evolve
Every insight is backed by traceable evidence — highlights, clips, verbatims — linked to their source study or URL. No opinion-as-fact, no orphan claims. Confidence is always explicit.
Atomic, tagged, searchable units don't get lost in long reports. They're rediscovered and reused across teams, so knowledge compounds instead of being re-researched. Especially powerful for distributed, democratized teams.
Where insights come from
Three input channels — all feeding one repository automatically, so every finding is captured regardless of how it was produced.
Manually created
Researchers curate insights directly from studies or imported data. Trust is set manually when no source has yet confirmed it — every insight starts with clear provenance.
Automated by AI agents
Agents process every session automatically — extracting highlights, drafting atomic insights, and tagging them before a researcher even opens the study.
From external knowledge
Marketing reports, competitor research, app reviews, NPS verbatims, and any external document feed the repository — widening the evidential base of every insight.
What an atomic insight is
An atomic insight is not a slide or a summary. It is an observation + supporting evidence + traceable sources + a trust level — small enough to be reused in any context, rich enough to be trusted without reading the full report.
No more duplicates — one canonical truth
Usedge detects when insights overlap and surfaces merge suggestions. Three findings that say the same thing become one authoritative insight — with all the evidence consolidated behind it.
Similar insights detected
Users need price transparency before committing to a purchase
Users abandon checkout when the total is hidden before payment
Missing order summary causes drop-off at the payment step
91% overlap
detected
Merged canonical insight
Price transparency before commitment is a critical blocker across checkout and payment flows
Consolidated evidence
3 insights merged · 24 highlights combined · Apr–Aug 2025
A research-driven product backlog
Insights connect directly to Opportunities — backlog items with priority, team, and description. Every item traces back to evidence. Product teams stop debating what to build and start showing stakeholders why — in one click.
- Link any insight to one or more opportunities — no manual copy-paste
- 2 opportunities connected per insight on average — stakeholder-ready from day one
- Priority and team ownership visible alongside the supporting evidence
- Product backlog grounded in real customer findings, not assumptions
Product backlog — evidence-backed
Improve checkout transparency
Product · 3 insights
Mobile payment flow redesign
Design · 2 insights
Onboarding simplification
Product · 5 insights
Search relevance improvements
Engineering · 4 insights
Every backlog item traces to evidence — click any row to see linked insights
Living knowledge — not a static dump
The Trust Index changes over time. Insights get upgraded when new studies corroborate them, and downgraded or deprecated when evidence goes stale — so your repository stays accurate, not just large.
New corroborating evidence raises the Trust Index automatically
AI flags insights with no recent supporting evidence — prompting review
Mark superseded findings as deprecated — full audit trail preserved
Every change — shared, linked, updated — logged permanently for audit
Trust Index — over time
Insight created manually — no source yet
8 highlights added from usability study
Corroborated by 2 further studies
No new evidence in 6 months — trust reviewed
Marked as deprecated — superseded by new finding
Deprecated — Dec 2025
Superseded by new checkout research. Preserved for audit history.
Qual + quant, triangulated for stakeholders
An insight is not just what someone said — it is what you observed in sessions, confirmed by data. Usedge lets you attach both qualitative highlights and quantitative statistics to the same insight: a fully triangulated, stakeholder-ready finding in one place.
- Attach verbatim quotes alongside NPS stats or analytics data to one insight
- Qual and quant evidence clearly labeled within a single atomic unit
- Stakeholders see the full picture — not just the headline
- Cross-reference statistical confidence with real user language
Notifications are the primary driver of churn among power users in month 3
“I got six notifications in one day and just turned them all off. I haven't opened the app since.”
— Power user, cohort 3, churned
of churned users disabled notifications before day 90 — vs. 18% of retained users (NPS dataset, n = 2 412)
Access from anywhere, in plain language
The repository is not just searchable inside Usedge. Connect it over MCP to Slack, Teams, or Claude and your whole team can ask questions in plain language — and get sourced, cited answers without opening a single report.
Ask anything
Query your full repository in Slack, Teams, or Claude — natural language, sourced answers
Always cited
Every answer traces back to studies and highlights — no hallucinated context, no guesswork
Real-time
Agents see new insights the moment they are added — no manual syncs or exports needed
What do we know about onboarding friction for enterprise users?
Found 7 relevant insights. Top finding: enterprise users abandon step 4 (team invite) at a 63% rate due to an unclear permission model — High confidence, 89%. Supported by 14 highlights across 3 studies.
Sources
Is there quantitative data behind this?
Yes — the Aug NPS dataset shows 61% of enterprise churn happens within day 14. Onboarding completion for the invite step is 38%. This insight is linked to 1 opportunity: "Enterprise onboarding redesign" (P1 · Product squad).
Sources
Where research becomes institutional knowledge
Atomic insights, one source of customer truth, accessible to every team and every agent — without opening a single report.