Case study · Financial services
FinTech EngineFrom 48-hour spreadsheet delays to real-time sync
- Uptime
- 99.99%
- Data sync, down from 48 h
- Real-time
- Lower running cost
- 35%
Before
Transaction data arrived from several sources and was merged into shared spreadsheets by hand. Each cycle took up to 48 hours, errors surfaced only at month-end, and nobody could see an up-to-date position during the day.
What we built
- 1Modelled transactions, accounts and reconciliation rules in MongoDB with indexes designed for the queries finance runs most.
- 2Built the ingestion and reconciliation engine as Docker services, so every environment runs the same image.
- 3Deployed on Render with health-checked releases, autoscaling workers and alerting routed to our on-call rota.
- 4Replaced batch uploads with continuous sync, so dashboards reflect new transactions as they land.
After
The team now works from a live position instead of a two-day-old one. The service has held 99.99% uptime, and consolidating onto right-sized containers cut running costs by 35%.