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Founder-led build · AIBYTERS · Management reporting

Visual Intelligence Library: one standard for every report

How I replaced one-off charts with a single reusable library of 48 components, from KPI cards to SWOT and risk matrices, so leadership sees every number presented the same way.

  • Reporting standards
  • KPI visualization
  • Strategy frameworks
  • Reusable systems
  • React
  • TypeScript
48reusable components
6component categories
4strategy frameworks, live
1shared data spec

01The problem

Every new dashboard, report, or client deliverable redrew the same charts from scratch, each slightly differently. KPI cards didn't match between products, SWOT and risk matrices were rebuilt as one-off slides, and every new report meant repeated design and QA work.

Leadership was reading the same numbers presented a different way every time.

02My role

  • Defined the reporting standard: which visual form each type of management question needs (KPIs, trends, funnels, risk, strategy, AI insight).
  • Designed a single shared data specification, so any chart can be fed from the same data format.
  • Planned the catalogue by category and delivered it in phases, tracking progress per category.
  • Owned integration into the Credit Union platform's dashboards.

03What was delivered

  • 48 components across 6 categories, all wrapped in one consistent widget card with shared theming.
  • KPI cards: metric, delta, target, sparkline, severity, and progress.
  • Business intelligence: line, bar, combo, funnel, waterfall, matrix, Sankey, gauge, bullet, timeline, and more.
  • Strategy frameworks: SWOT, PESTLE, risk matrix, and competitive positioning as live components instead of static slides.
  • Data science, geospatial & network: forecast bands, anomaly timelines, control charts, choropleth maps, and network and dependency graphs.
  • AI intelligence: Insight and Recommendation cards for presenting AI-generated findings consistently.
  • Platform adapter so the same components drop straight into ERPNext/Frappe dashboards.

04Why it matters for operations

  • Consistency. Leadership sees the same KPI in the same form across every product and report.
  • Speed. New dashboards are assembled from tested parts instead of being built from scratch.
  • Quality. One shared data spec with automated tests means fewer broken or misleading charts.
  • Strategy next to the numbers. SWOT, PESTLE, and risk matrices sit beside the live data they depend on.

05Results

48reusable components
6component categories
4strategy frameworks, live
1shared data spec

This library powers the dashboards of the Credit Union Operations & AI Platform.

Next case studyCredit Union Operations & AI Platform
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