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Case studies in capital markets and fintech engineering — cloud modernization, trading systems, data platforms, and fractional CTO engagements for tier-one institutions.

machine learning gcp

Finance crime ML platform modernization

Delivered a global machine learning platform on GCP that detects financial crime faster while cutting infrastructure cost.

  • Improved model training performance by 25% through targeted platform upgrades.
  • Cut infrastructure spend by ~20% by eliminating drift across global environments.
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cloud modernization gcp

Capital markets cloud landing zone

Built a regulated-ready cloud landing zone that moved critical trading workloads to Google Cloud in under six months.

  • First mission-critical workloads live in six months.
  • Infrastructure deployment cycle time reduced by 52%.
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risk analytics Apache Beam

Realtime risk analytics modernisation

Unified batch and streaming risk calculations with Apache Beam and Dataflow to cut reporting time from hours to minutes.

  • Intraday VaR windows dropped from 3 hours to 14 minutes.
  • New data feeds onboarded in 3 weeks instead of 10.
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All case studies

Explore the breadth of work spanning liquidity, platform engineering, AI, and market infrastructure.

capital markets liquidity

Liquidity reconciliation engine

Built a greenfield matching engine that reconciled every cash movement for a tier-one bank’s liquidity and regulatory reporting.

  • Delivered a production-ready matching engine that reconciled 100% of cash movements for a key legal entity.
  • Cut reconciliation time from end-of-day batches to near real-time with an event-driven architecture.
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