Each one was built on go-to-market data by describing it to an agent — dashboards, heatmaps, scorers, and analyses. Read the index, open the one that answers your question.
Scores customers on likelihood to expand across seven factors.
View example →Every open deal scored — confidence tiers and a close timeline.
View example →Every program from members to closed-won, with side-by-side compare.
View example →How a founder's podcast appearances move pipeline, as source and proof point.
View example →How group size, touchpoints and MQL status relate to win rate.
View example →Every inbound traced from first-touch web channel to the last touch.
View example →Which channels influenced closed-won, across the full buyer journey.
View example →How paid search and social turn spend into influenced pipeline.
View example →Which modules are contracted vs used — coverage that spots whitespace.
View example →Scores open opps against the winning profile for a weighted forecast.
View example →Grades campaigns on whether a touch actually moved a deal forward.
View example →Engagement and opportunity-influence metrics, by division and rep.
View example →Clusters prospect questions into themes, ranks content ideas by demand.
View example →Calls, emails and meetings over time, with an activity heatmap.
View example →Every closed-lost deal read against the winning playbook.
View example →After a campaign engagement, how fast does sales follow up — and who's waiting?
View example →A voice-of-customer wall from call transcripts, with logo rights.
View example →Which accounts were pitched the flagship, across an adoption funnel.
View example →The day-and-hour windows where outbound earns the most replies.
View example →Every inbound lead by status, source and ICP fit — plus a revive queue.
View example →Target accounts through the ABM funnel, fused with buying signals.
View example →How much each prospect already knows before the SDR call.
View example →How AI engines move pipeline — citation traffic, call mentions and win-rate lift.
View example →Where pipeline really comes from, on a de-duplicated account rollup.
View example →The words that win vs the ones that stall, mined from calls.
View example →A resolved-or-past funnel that flags the real bottleneck.
View example →Scores every account against the playbook: which play fits, and why.
View example →Board-level influenced pipeline and the pipe-to-spend ratio.
View example →A win/loss deep-dive on a launch — benchmarks, loss patterns, risk.
View example →Matches a live deal to its closest cohort and writes the next play.
View example →Accounts showing buying signals with no open opp, ranked by intent.
View example →Tell Claude, Cursor, or Upside's hosted agent the tool you need — in plain language, no spec required.
The app is generated against your healed, identity-resolved GTM data. The hard data work is already done.
Ship it inside Upside with independent view and edit scopes. No BI backlog, no shadow IT.
Connect your go-to-market data and turn a prompt into an app like these — live for the whole team.
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