A deliberately modern, well-maintained stack.
We choose tools for longevity and leverage, and we keep them current. No legacy lock-in, no fashionable dead ends — just proven technology, applied well.
AI / ML
We default to Azure OpenAI because it keeps your prompts and completions inside your own tenant and under your own data-residency commitments, which is usually the difference between a pilot and a production approval. Semantic Kernel and LangChain handle orchestration; PyTorch, TensorFlow and scikit-learn cover the cases where a bespoke model genuinely beats a general one — forecasting, anomaly detection and vision, where a small trained model is cheaper and more accurate than a large language model.
- Azure OpenAI
- TensorFlow
- PyTorch
- scikit-learn
- LangChain
- Semantic Kernel
Data
Almost every AI engagement turns out to be a data engagement first. Snowflake and Databricks for the warehouse and lakehouse, dbt so transformations are versioned and tested rather than buried in notebooks, Azure AI Search for the retrieval layer behind grounded assistants, and Power BI because it is already on the desk of the people who need the answer. Python ties the rest together.
- Snowflake
- Databricks
- dbt
- Python
- Power BI
- Azure AI Search
Cloud / Infra
Azure first, AWS where a client already lives there. Everything is defined in Terraform so an environment can be rebuilt from the repository rather than from memory, and containerised with Docker and Kubernetes so the same artefact runs in test and in production. This is the layer that decides whether you can hand a system over — undocumented, hand-built infrastructure is how projects become permanent dependencies.
- Azure
- AWS
- Kubernetes
- Terraform
- Docker
- GraphQL
Engineering
TypeScript end to end, so a change in a contract fails at build time rather than in front of a customer. Next.js and Node.js for web and services, .NET where we integrate deeply with Microsoft systems, Rust for the small number of components where throughput genuinely matters, and Power Platform when the right answer is a low-code app your own team can maintain after we leave — which is more often than consultancies like to admit.
- TypeScript
- Next.js
- Node.js
- Rust
- .NET
- Power Platform
Future-proof by design
We treat currency as a feature. Dependencies are pinned and monitored, security advisories are triaged continuously, and we build on actively-maintained, standards-based foundations — so what we deliver stays supportable for years, not months.