AI solutions, model integrations and intelligent systems built around a real business process — not a demo.
Overview
Most AI projects stall because they are built as experiments rather than systems. We start from the decision or workflow you want to change, then engineer the shortest reliable path to it.
That means grounded retrieval over your own data, evaluation harnesses that catch regressions before users do, and deployment paths your team can actually operate.
- Faster resolution time
- 63%
- Manual review removed
- 71%
- Answer accuracy
- 94%
Figures are medians across recent engagements in this practice, not best-case results.
- LLM application development
- Retrieval-augmented generation
- Model selection and evaluation
- Fine-tuning and prompt architecture
- Vector search and embeddings
- Structured extraction pipelines
- Guardrails and safety layers
- Inference cost optimisation
- 01
AI opportunity map
A ranked view of where intelligence changes a metric, scored on impact, data readiness and engineering effort.
- 02
Production AI service
A deployed, observable service with retrieval, guardrails, evaluation suites and cost controls in place.
- 03
Evaluation harness
A regression suite over real cases so model or prompt changes are measured, not guessed.
- OpenAI
- Anthropic
- LangGraph
- pgvector
- Python
- FastAPI
- TypeScript
Tell us the constraint you are trying to remove. A senior engineer will read it and reply within one business day — no sales sequence.