Domain-specific depth
Claims, shortfalls, providers, insurers, and reconciliation create a much more believable healthcare finance story than a generic admin panel.
Healthcare Revenue Operations/5 screens
Baines Claims
Claims operations workspace for documents, claims, shortfalls, providers, insurers, bank reconciliation, and AI-driven document intelligence.
Screen walkthrough
A fuller gallery for the product story.
This gallery is meant to show progression, not just a single hero frame. Use it to talk through navigation depth, records, analytics, and workflow context during a call.
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Screen 01
Primary interface capture used for the listing card and story lead.
Overview
Baines Claims is a strong operational case study because it pairs domain-specific modules with a clear automation angle. The screen combines documents, claims, shortfalls, provider and insurer data, bank reconciliation, and AI insights with a visible extraction-accuracy signal.
Strongest story angle
Tell it as a healthcare revenue operations product that reduces document friction and gives operators a cleaner claims control surface.
Observable modules
DashboardDocumentsClaimsShortfallsProvidersInsurersBank ReconUpload RemittanceExport ClaimsAI Insights
Why this one works
Three angles worth carrying into the final write-up.
Automation with evidence
The AI insights module is supported by a visible extraction-accuracy claim, which is a useful anchor for motion graphics and portfolio positioning.
Operator utility
Quick actions such as upload remittance and export claims keep the narrative rooted in daily operational work.
Motion outline
This sequence can still become a short teaser.
- 01
Open with the claims intelligence dashboard and document stack.
- 02
Animate claims, shortfalls, and reconciliation callouts with the AI insight badge.
- 03
Close on the idea of healthcare finance workflows with less manual document handling.
Next publishing pass
The structure is now cleaner: better screenshots, stronger conversion paths, and shared page chrome that behaves correctly. The next layer is adding repository-backed build notes and verified outcome data.
Still worth adding
- 1. Verified repository context for stack and architecture notes.
- 2. Approved proof points to replace generic performance language.
- 3. Short teaser renders once the repository evidence is in place.