SaaS Web App Development for Startups

Rajasthan Royals, one of the founding IPL franchises and the inaugural T20 champions, partnered with Appycodes to build their internal analytics SaaS platform, Leading Edge. The platform powers the decisions the cricketing operations team makes day to day: player scouting across the global player pool, the trade engine for IPL auction modelling, ongoing player analytics for every athlete on the roster, and projection models that feed match strategy.

The data warehouse sits on Google BigQuery, every ball bowled across every competitive match the system tracks, ingested and structured. Most of the engineering challenge was not the front-end. It was the queries. Player scouting against multi-season ball-by-ball data, with strike-rate-against bowler-type filters, situational match-state segments, and venue-specific performance windows, runs across hundreds of millions of rows. Naive SQL costs minutes per query, unusable for an interactive scouting interface.

We restructured the query layer with materialised views for the highest-frequency analytical paths, partitioned and clustered tables on the filters scouts actually use, pre-aggregated rolling windows on a scheduled pipeline, and pushed projection models out of the query path entirely into a Python service that returns pre-computed responses. Scouting queries that used to take minutes return in single-digit seconds. The trade engine, which models trade scenarios across BigQuery in near real time during the auction window, runs on the same architecture.

Building software for an IPL franchise has a different bar than most SaaS work. The platform has to be right when the auction clock is running and millions of dollars of player contracts are on the line. We treated it that way from sprint zero.

CREOATE raised $5M from Fuel Ventures to build a B2B marketplace connecting independent retailers with global suppliers. The product needed to handle two distinct user journeys at the same time, buyers browsing thousands of SKUs, and suppliers managing inventory, orders, and payouts, without either side feeling slow.

Our engineering team contributed across the React frontend, the Node.js services that power search and checkout, and the PHP layer that handles supplier-side order management. The hard part was not any single feature, it was keeping the marketplace responsive as catalog size, order volume, and supplier count grew in parallel.

Eight hundred thousand orders later, the platform is still running on the same architectural decisions made in those early sprints: a hybrid database structure with DynamoDB on the catalog layer and MySQL on the dashboards side, with carefully chosen indexes, queue-backed background jobs for anything slower than 200ms, and a frontend that treats every network call as fallible by default.

Easyship is a global shipping platform now valued at over $40M, helping merchants compare and book carriers across two hundred countries. The product runs on a deceptively complex set of calculators: every quote requires reconciling rate cards, customs rules, surcharges, and merchant-specific contracts in real time.

We built and maintained many of these calculator engines in Vue, React and TypeScript, with Node services backing them. The interesting engineering was not the math, it was keeping the rules engine testable across all geographic and language combinations.

Strong typing across the boundary between the calculator engine and the UI was the single highest-leverage decision. When the rates API updated their data structures and response formats, the failures were caught at compile time in a single sprint, not by a user complaining that their quote did not work.