Case Studies
Work that changed production systems
Each engagement started with a specific constraint—latency, cost, reliability, adoption. These are the measurable outcomes.
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Event-driven logistics orchestration
A multi-region logistics platform suffered cascading failures during peak demand. The monolithic event processor couldn't scale horizontally, and retry storms amplified outages. We redesigned the event architecture for predictable throughput.
Low-latency edge processing for connected vehicles
Single-digit millisecond latency with graceful degradation.
Market data pipeline modernisation
Predictable refresh without higher scan cost.
ML-powered demand forecasting
Automated forecasts with explainable recommendations.
Interactive constrained-generation product
Seconds-level UX with strict rule adherence.
Clinical workflow digitisation
Compliant digitisation without disrupting clinical flow.
Methodology
How we document outcomes
Every case study follows the same structure: context, constraint, intervention, measured outcome. No vanity metrics.
Constraint-first
We start with the hard limit—latency budget, cost ceiling, compliance requirement. The constraint shapes the solution.
Measured outcomes
Every claim has a number. “Faster” becomes “4h → 35min”. “Better” becomes “+8% availability”. No hand-waving.
Anonymised context
Client identifiers removed. Industry and system type preserved. Enough to understand the problem, nothing that shouldn't be shared.
Have a similar constraint?
Share your system context and the hard limits you're working within. We'll tell you if we can help—and what a realistic outcome looks like.