Client Overview
B2B Financial Tech Startup
The Challenge
The client's users were overwhelmed by raw data exports. They needed a beautiful, interactive dashboard that could process millions of data points in real-time and automatically generate executive summaries.
Our Solution
We engineered a robust React frontend powered by a highly optimized Python backend. We used advanced caching strategies and WebSockets to deliver real-time data visualization securely, along with a custom PDF generation service.
The Results
- Shipped to production in under 6 weeks
- Handle processing of 5M+ daily API events
- Zero downtime during peak reporting periods
- User engagement time increased by 300%
Turning Raw Data Into Executive Decisions
Financial tech startups live and die by data. But this B2B fintech had a problem: their customers — CFOs and financial analysts — were drowning in CSV exports and static PDF reports. The data was there, but the insights were buried.
They'd tried hiring an internal team to build a dashboard, but after 3 months and significant spend, they had a proof-of-concept that could barely handle 10,000 records without crashing. They needed a team that could execute fast and handle scale.
The Technical Challenge
The requirements were demanding:
- Real-time processing of 5 million+ API events per day
- Sub-second chart rendering for datasets spanning 12+ months
- Role-based access control (admin, analyst, viewer) with row-level security
- Automated PDF reports generated weekly with zero manual input
- SOC 2-ready architecture for enterprise client requirements
Our Approach
Data Pipeline (Week 1-2)
We built the ingestion pipeline on Python (FastAPI) with PostgreSQL as the primary store and Redis for hot caching. Key design decisions:
- Materialized views for common query patterns — pre-computed daily, weekly, and monthly aggregations
- Connection pooling via PgBouncer to handle concurrent dashboard loads
- Event streaming with WebSockets for real-time updates without polling
This architecture handles 5M+ daily events with P99 latency under 200ms for dashboard queries.
Frontend Dashboard (Week 2-4)
The React frontend was designed for maximum information density without cognitive overload:
- Recharts for interactive, responsive data visualization
- Virtualized tables for browsing raw event data (100K+ rows scroll smoothly)
- Keyboard-first navigation for power users
- Dark mode by default (financial analysts work in dark mode)
- Real-time WebSocket updates — charts animate as new data flows in
Reporting Engine (Week 4-5)
The automated reporting engine was the feature that sealed enterprise adoption:
- Puppeteer-based PDF generation that renders the actual dashboard charts (not static images)
- Scheduled via cron — weekly executive summaries, monthly deep-dives
- White-labeled per client with custom branding in the PDF header
Security & Deployment (Week 5-6)
- Row-level security in PostgreSQL ensuring analysts only see their assigned accounts
- JWT + refresh token authentication with 15-minute access token TTL
- Deployed on AWS (ECS Fargate) with auto-scaling based on CPU and memory thresholds
- CI/CD via GitHub Actions with staging and production environments
The Impact
Within the first month post-launch, the startup signed two enterprise contracts they attribute directly to the dashboard demo. Users went from spending 3 minutes glancing at static reports to 12+ minutes engaged in interactive exploration — a 300% increase in engagement that directly correlated with subscription upgrades.
The automated reporting feature alone saved their operations team 15+ hours per week previously spent manually compiling Excel reports.
"They understood our complex data requirements perfectly and delivered a dashboard that our enterprise clients absolutely love."