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Revenue operators, founders, RevOps reviewers, and sales leaders evaluating deal health during a fast hackathon demo or local proof run. They need to understand why a deal changed without trusting uncited AI summary text.
Revenue Intelligence OS is a Gong-style workbench focused on causal deal memory. It helps a user replay what was known at a point in time, inspect cited deal evidence, and decide whether follow-up is stale because buyer state, objections, or CRM facts changed.
Precise, evidence-led, calm. The product should feel like an operator console for serious revenue decisions, not a decorative SaaS landing page.
Do not present broad Gong parity, live-provider validation, or customer deployment as proven when the app is running in local-demo mode. Avoid dense four-panel walls where every artifact has equal weight, decorative dashboards, generic AI command-center chrome, and uncited recommendation copy.
- Lead with the answer: show what changed, why it matters, and the next action before exposing raw evidence.
- Keep proof visible: every claim should stay connected to memory, call, CRM, or knowledge citations.
- Reveal complexity progressively: graph, timeline, and evidence are supporting material, not four equal first-screen destinations.
- Preserve operator density without clutter: compact data is allowed when hierarchy and grouping make the path obvious.
- Separate local proof from live-provider proof wherever readiness or submission language appears.
Target WCAG AA contrast and keyboard-readable structure. The UI should work without color-only meaning, keep text at readable product-UI sizes, preserve visible focus states, and avoid motion that blocks task completion.