Activate data and AI

Choose where machine learning, generative AI, RAG or agentic AI makes sense, and where it doesn’t. We bring product, design, data, cloud and engineering perspectives together to assess use cases, risks, data readiness, platform options across AWS, Google Cloud and Azure, and the path to production.

Design, build and operate production AI applications, from RAG and LLM-powered tools to real-time assistants, workflow automation and user-facing product features, with clear evaluation, guardrails and human in the loop where needed.

Make data usable, governed and ready for AI. We design pipelines, data products, access patterns, lineage and quality controls so teams can trust the data behind the system.

Build cloud-native data platforms for analytics, machine learning and AI products. We implement batch and streaming ingestion, transformation, orchestration, metadata, lineage, observability and security so teams can trust and reuse the data.

Turn raw data into trusted data products, reusable models and decision tools, from self-service analytics and dashboards to forecasting, churn and demand prediction, classification, matching and optimisation across teams and workflows.

Use event streams, feature serving, edge inference and online data patterns to support personalisation, pricing, fraud detection and operational automation, so products and teams can respond in the moment.

Connect physical assets, devices and field systems to your platform, even where connectivity is patchy, hardware is constrained and conditions are hard to control. From device and firmware to secure connectivity, over-the-air updates and edge inference, we help make data reliable and actionable in connected environments.

Use generative to lift team productivity across discovery, prototyping, code and test creation, documentation and support, guided by clear product decisions and engineering discipline so speed doesn’t cost quality.