Real bottlenecks, the stacks we chose, and the metrics that reached production.
Enquiries were leaking across Rightmove, Zoopla, OnTheMarket, phone calls, and walk-ins, and the ones that slipped through were often the ones that would have closed. We built a white-label, multi-tenant SaaS that scores every lead the moment it lands and routes it to the right negotiator. Lead-to-viewing conversion rose 40%, with first response held under 5 minutes.
A Dubai operator was dispatching 400 vehicles over WhatsApp while fuel ate 28% of operating spend. We streamed MQTT telemetry into TimescaleDB, gave dispatchers a Mapbox control tower with AI route optimisation, and put an offline-first React Native app in every driver's hand. Fuel costs fell 22% and late deliveries dropped 35%.
A tutoring provider needed live GCSE and A Level classrooms up and running before term, with AI marking to match. We built the platform on LiveKit for low latency WebRTC video, PostgreSQL row level isolation to keep each school's data separate, and Stripe Connect for billing. It reached production in 10 weeks and holds 15,000 concurrent learners.
A 120 store chain shipped once a month by SSHing onto bare metal behind a single Nginx front door, and every release was a held breath. We containerised five services onto EKS, wired GitHub Actions with automatic rollbacks, and added Prometheus, Grafana, Loki, and Jaeger for full observability. Deploys now run daily and health checked, 30x more often than before, with zero downtime.
3,000 claims a month arrived as scans and PDFs, then sat for days while handlers retyped the same fields by hand. We built a pipeline that reads them automatically: Textract OCR, GPT-4 structured outputs, and an ML triage layer that now clears 85% of claims in 4 hours. Specialists review only the low confidence fields the model flags.
Written scope, timeline, and cost estimate within 48 hours. No sales pitch, just a plan.
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