01 · Implementation & build
Production-grade AI, built on your data and wired into your systems
This is where most of our engineering time goes. We build the application, the model work and the integration as one delivery, with evaluation sets, guardrails and monitoring from the first sprint rather than bolted on later.
- Typical scope
- 6 to 16 weeks per phase, fixed fee
- Best for
- Teams with a validated use case that needs to ship
- Stack
- Python, Node.js, React, Angular; Azure, AWS, GCP; OpenAI, Anthropic, Google and open-weight models
Scope a build
GenAI / LLM applications
Retrieval-augmented assistants, copilots and document-AI pipelines on your own content, with evaluation suites so you can trust what ships.
- RAG over policies, contracts, tickets and knowledge bases
- Copilots inside your existing tools
- Document extraction, classification and summarisation at scale
ML model development & MLOps
Custom models for forecasting, scoring, classification and recommendation, with the pipelines and retraining loops to keep them accurate.
- Feature pipelines, experiment tracking, model registry
- CI/CD for models with automated validation gates
- Fine-tuning and distillation where it beats prompting
Enterprise integration
AI wired into SAP, Salesforce, Microsoft 365, Dynamics and your ERP, so outputs land where people already work instead of in another tab.
- API, event and workflow integration patterns
- Identity, permissions and audit carried through to the model
- Legacy system connectors and data contracts
Custom AI products
Productised AI built for one client: the API, front end, admin, billing and operational tooling around the model, ready for your customers.
- Full-stack delivery from design to launch
- Multi-tenant architecture and usage metering
- Hand-over with documentation and a trained team
AI infrastructure & cloud
GPU capacity, model serving, vector stores, gateways and hyperscaler landing zones sized for your workload and your budget, on Azure, AWS, GCP or on-premises.
- Serving and routing across hosted and self-hosted models
- Private networking, key management and data residency controls
- Cost modelling before you commit to capacity
