Case study 01
AI Healthcare Intelligence
GenAI + machine learning systems for healthcare claims analysis, risk detection and intelligent processing.
- Generative AI
- Risk detection
- Document intelligence
- Stack
- Python · LLMs · PostgreSQL · Azure
SELECTED WORK
Systems built for real-world scale.
Selected engineering experience from the founding team. Client names and commercial figures are intentionally withheld — what is here is the architecture, the trade-offs and what we would do again.
Pick a domain
- Healthcare & claimsClaims, clinical documents and prior authorisation generate enormous volumes of semi-structured text. The engineering problem is rarely the model — it is handling that material safely, traceably and at volume.
- Media & videoAudio and video workloads punish naive architecture. Throughput, cost per hour processed and resumability decide whether a pipeline handles a catalogue or falls over on it.
- Commerce & personalizationRecommendation is an infrastructure problem wearing a machine-learning hat. Feature freshness, serving latency and cold-start behaviour matter more than the choice of algorithm.
- Enterprise platformsInternal tools carry the operational load of a business and almost none of its design attention. The work is integration, permissions and reliability far more than interface.
Case studies
Case study 02
Transcription & Video Platform
Real-time transcription and scalable video processing infrastructure using Python, RabbitMQ, FFmpeg and cloud technologies.
- Real-time transcription
- Media pipelines
- Queue architecture
- Stack
- Python · RabbitMQ · FFmpeg · GCP
Case study 03
AI Recommendation Engine
Machine-learning recommendation infrastructure designed to deliver personalized recommendations at scale.
- Recommendations
- Feature pipelines
- Model serving
- Stack
- Python · scikit-learn · FastAPI · Docker
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