SQOR.io: Predictive SaaS Analytics Dashboard & Real-Time Alerting
Unifying multi-tenant CRM, billing, and product usage telemetry into a sub-second executive dashboard with predictive churn detection and zero browser UI freezing.
The Objective
SQOR.io provides venture-backed founders and B2B SaaS executives with an automated financial health cockpit. As Full-Stack Engineer & Data Pipeline Architect, I structured the Next.js React frontend, the asynchronous Python data normalization engine, and the multi-tenant caching topology.
The Engineering Bottlenecks
- Query Latency on Cohort Aggregations: Calculating churn risk across hundreds of thousands of historical billing events took 12+ seconds using traditional SQL JOINs.
- DOM Choke on 50,000 Datapoints: Rendering granular timeline charts caused mobile safari and desktop browsers to freeze due to excessive DOM nodes.
Pipeline Architecture
Virtualized Canvas Charting
I replaced DOM-heavy SVG elements with an offscreen HTML5 Canvas renderer that downsamples dense visual data clusters based on the device viewport width. Rendering 50,000 historical datapoints now consumes under 18ms of frame rendering time.
Measurable Impact
Query execution speeds jumped by 3.5x, enabling real-time drilldowns by cohort and customer tier with automated Slack notifications when user engagement drops cross critical limits.
Building a B2B SaaS dashboard or analytics engine?
I engineer SaaS platforms designed for rapid query response and clean multi-tenant isolation.