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See how we've helped businesses across industries overcome challenges and achieve measurable outcomes.

Full-Stack Development

Building a Multi-Tenant SaaS Platform: 0 to $2M ARR in 14 Months

Full-Stack Engineering for a PropTech Startup

SaaSMulti-tenantNext.jsPropTechFull-StackStartup

The Challenge

A UK PropTech startup had a validated concept and seed funding but no technical co-founder and 18 months of runway. They needed to go from zero to a revenue-generating, scalable SaaS platform within 1...

Results Achieved

  • MVP launched in month 4 with 3 paying customers
  • $2M ARR reached by month 14
  • 99.95% uptime in the 12 months post-launch
  • Zero GDPR data-isolation incidents despite 120+ tenants
  • Field agent mobile app rated 4.8★ on App Store with 1,200+ active users
  • Codebase passed SOC 2 Type I audit without major architectural changes
Client: Confidential PropTech Startup (Seed, UK)Full Case Study
AI & Machine Learning

How We Reduced ML Inference Latency by 73% for a FinTech Fraud Detection System

From 450ms p99 to 120ms: A Model Serving Optimisation Story

Machine LearningFinTechModel ServingTriton Inference ServerONNX

The Challenge

A US-based Series B FinTech was running a gradient boosting fraud detection model on SageMaker real-time endpoints. The model processed every card transaction — but at 450ms p99 latency, they were blo...

Results Achieved

  • p99 latency reduced from 450ms to 120ms (73% improvement)
  • p50 latency reduced from 180ms to 38ms
  • Infrastructure cost reduced by 38% (Inferentia + ONNX efficiency)
  • Zero SLA breaches in the 6 months following deployment
  • Checkout abandonment rate at payment step decreased by 1.2%
Client: Confidential FinTech (Series B, US)Full Case Study
Data Engineering

Migrating 2.4 TB PostgreSQL to a Cloud-Native Lakehouse Without Downtime

CDC-Based Migration with Debezium, Iceberg, and Zero Business Disruption

Data EngineeringPostgreSQLApache IcebergDebeziumCDCMigration

The Challenge

A European B2B SaaS company had accumulated 2.4 TB of operational data in a self-managed PostgreSQL 14 cluster on bare-metal. Analytics queries were running directly on the production database, causin...

Results Achieved

  • Zero downtime achieved — production PostgreSQL untouched during migration
  • Query performance for analytics improved by 8–40× (Trino columnar reads vs PostgreSQL row scans)
  • Production database read load reduced by 65% (analytics traffic fully offloaded)
  • Storage cost reduced by 40% (Parquet columnar compression vs PostgreSQL heap files)
  • Migration completed in 22 days — 8 days ahead of the 30-day target
Client: Confidential SaaS Platform (Series A, Europe)Full Case Study

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