We take on the parts of your technology estate that decide whether the rest works: the data, the platform it runs on, and the automation around it.
Snowflake and Azure Databricks platforms built with Python, PySpark and dbt — ingestion, modelling, CDC and streaming pipelines your analysts can trust.
Typical work: source onboarding, dimensional and Data Vault modelling, batch and near-real-time pipelines, ETL/ELT with Informatica PowerCenter and IICS, data quality tests, cost and performance tuning.
Discuss this serviceArchitecture and migration across Azure, GCP and AWS — landing zones, infrastructure-as-code and FinOps guardrails from day one.
Azure: Databricks, Data Factory, Synapse, Data Lake Gen2, Purview. GCP: BigQuery, Dataflow, Composer, Vertex AI. AWS: Glue, Redshift, Athena, EMR, SageMaker. Provisioning via Terraform, CloudFormation and ARM.
Discuss this serviceProduction GenAI rather than demos: RAG pipelines grounded in your own documents, AI agents that carry out real operational work, and the governance to run them safely.
Built on Azure AI Foundry, Azure OpenAI, Vertex AI, Claude and LangChain. Includes RAG retrieval design, agentic workflows, prompt engineering, evaluation, model lifecycle management and Responsible AI / AI governance checkpoints.
Discuss this serviceGovernance people actually follow — domain ownership, data products, lineage and stewardship modelled on DAMA-DMBOK rather than a policy document nobody reads.
Data Mesh and Data Fabric operating models, data product design, master data management with Informatica MDM, metadata and lineage automation, access control, and AI governance for model and agent deployments.
Discuss this serviceGoverned metrics and dashboards that answer real questions, built on a semantic layer instead of spreadsheet archaeology.
Power BI and federated analytics, metric definitions, self-service enablement, report rationalisation and adoption tracking.
Discuss this serviceSub-second product search and honest product analytics — the layer that decides whether customers find what you sell.
Elasticsearch indexing and faceted discovery for customer-facing catalogues, Mixpanel product-usage analytics, and HubSpot CRM data joined into lead scoring and conversion funnels.
Discuss this serviceSystems that stop disagreeing with each other — REST integrations, event-driven flows, reverse ETL and federated query where copying the data is the wrong answer.
REST API design, StackSync and SnapLogic integration, orchestration with Airflow, Cloud Composer and Azure Data Factory, and data virtualisation with Dremio and Starburst for logical warehousing.
Discuss this serviceMonitoring, release discipline and advisory retainers so the platform keeps improving after go-live instead of quietly rotting.
Datadog observability and threshold alerting, MLOps and CI/CD through Azure DevOps, Git and Jira delivery governance, incident response, cost reviews and quarterly roadmap sessions.
Discuss this servicePick the one that matches the risk you are carrying. Most clients start small and expand.
Two to three weeks. We review your current state and deliver a costed roadmap you can act on with or without us.
Fixed scope and milestones for a defined build — a warehouse, a migration, a platform, an integration.
An agreed number of days each month for support, optimisation and advisory once you are live.
We are deliberately opinionated. These are the platforms and tools we have run in production and know well enough to be accountable for.
Certifications are not the work, but they do mean somebody independent has checked the fundamentals. Our architecture practice is held by a certified multi-cloud architect with 15+ years across enterprise data and AI platforms.
Specialty chemicals and B2B SaaS, telecom, banking and finance, retail and e-commerce, logistics, insurance, healthcare, academic and automotive.
Platforms serving catalogues of 350,000+ products and 500,000+ members, with sub-second search across 15+ dimensions.
Tell us the stack you are on. If we cannot be accountable for it, we will say so and point you elsewhere.
Whether it's a data platform that needs rescuing or a makhana order that needs quoting, you'll get a straight answer from someone technical.