B2B Analytics SaaS Platform

A founding team with deep expertise in supply chain analytics had validated demand for a self-service analytics platform through manual consulting engagements. They had 30 companies on a waitlist ready to pay for the product, but no technical co-founder and no engineering team to build it. They came to us with a clear vision, a validated market, and a six-month runway to reach launch.

The Challenge

The product requirements were ambitious but well-defined: a multi-tenant SaaS platform where businesses could connect their data sources, build custom dashboards with interactive visualisations, and generate automated reports on a configurable schedule. The platform needed to handle enterprise-grade data isolation so that each customer's data was completely separated, even though they shared the same infrastructure.

The technical complexity centred on three areas. First, multi-tenancy at scale -- the platform needed to support hundreds of customers with varying data volumes without performance degradation for any single tenant. Second, real-time data visualisation -- customers expected interactive charts and graphs that responded instantly to filters and drill-downs, even with datasets containing millions of rows. Third, reliable subscription billing with usage-based pricing tiers, including trial periods, plan upgrades, and prorated billing.

The founding team had experimented with no-code tools during their consulting phase, but quickly hit limitations around data isolation, custom visualisation, and the level of white-labelling their enterprise customers required. They needed a purpose-built platform, and they needed it delivered within the six-month window before their runway expired.

Our Solution

We designed and built the platform using Next.js and TypeScript, deployed on Vercel with a PostgreSQL database implementing row-level security for tenant isolation. This architecture gave us server-side rendering for fast initial page loads, API routes for data operations, and a clean separation between the public marketing site and the authenticated application.

The multi-tenant data layer uses PostgreSQL's row-level security policies to enforce data isolation at the database level. Every table includes a tenant_id column, and security policies ensure that queries can only access rows belonging to the authenticated tenant. This approach provides defence-in-depth -- even if an application-level bug bypasses tenant filtering, the database itself prevents cross-tenant data access.

For the visualisation layer, we built a custom dashboard builder using D3.js. Customers can create charts, tables, and KPI cards from their data using a drag-and-drop interface, with the rendering happening client-side for interactivity while data aggregation runs server-side for performance. The system pre-computes common aggregations and caches results in a materialised view layer, allowing dashboards with millions of underlying data points to render in under two seconds.

Stripe integration handles the entire billing lifecycle. We implemented three subscription tiers with usage-based metering, automatic plan upgrades when customers exceed their tier limits, trial-to-paid conversion flows, and a self-service billing portal. Webhooks keep the application state synchronised with Stripe, handling edge cases like failed payments, plan changes, and subscription cancellations gracefully.

Automated reporting runs on a scheduled job system that generates PDF reports from dashboard configurations and delivers them via email on each customer's chosen schedule -- daily, weekly, or monthly. The report generation service renders dashboards server-side using the same D3.js components, ensuring visual consistency between the interactive application and the static reports.

Results

The platform launched on schedule at the six-month mark, with the first 30 waitlist customers onboarded in the opening week. Within three months of launch, the customer base had grown to over 200 paying businesses, processing more than 2 million data points daily across all tenants. The platform maintained 99.9% uptime through its first year of operation, with zero reported incidents of cross-tenant data leakage. The Stripe integration processed over $400,000 in subscription revenue in the first year, and the automated reporting feature became the most-cited reason for customer retention in exit surveys. The founding team successfully raised a Series A round six months after launch, with the technical architecture and growth metrics serving as key evidence of product viability.