Data Engineering & Integration
Design dependable data movement from source systems to curated, analytics-ready datasets. Build for incremental processing, recoverability, observability, and clear ownership.
Our capabilities
Data services that connect the whole picture.
Technology is only part of the answer. We combine architecture, engineering, analytics, and practical delivery to help your data work reliably across teams and systems.
Service portfolio
From foundational plumbing to business-facing insight.
Engage us for a focused delivery, specialist expertise, or an end-to-end data initiative.
Business Intelligence & Analytics
Build governed semantic models, dimensional data marts, executive scorecards, and self-service reporting that align teams around consistent measures.
Cloud & Platform Modernization
Assess legacy workloads, plan migration waves, and evolve on-premises data estates toward secure, scalable cloud data platforms without losing sight of cost and reliability.
AI & Advanced Analytics Enablement
Prepare governed data for copilots, conversational analytics, predictive insights, and automation. We focus on answer quality, clear data access, and practical operational fit—not AI demos alone.
Enterprise RAG & Vector Search
Design retrieval-augmented generation solutions that connect language models to approved enterprise knowledge. From source ingestion and chunking to embeddings, vector databases, hybrid retrieval, citations, access control, and evaluation, we build systems designed to be useful, traceable, and maintainable.
Data Quality, Governance & Security
Define critical data elements, validation rules, lineage, access patterns, and ownership. Make data quality visible through practical controls and actionable monitoring.
Performance Engineering & Advisory
Diagnose slow reports, expensive queries, long-running ETL jobs, and fragile integrations. Prioritize improvements based on measured bottlenecks and operational impact.
Platform experience
Choose technology for the job it needs to do.
We help teams make sensible platform choices based on data shape, workload, skills, security, operations, and total cost—not the trend of the moment.
- Microsoft Azure, Azure Data Factory, ADLS Gen2, Synapse, and Azure SQL.
- Microsoft Fabric, Power BI, and analytics model design.
- Databricks, Spark, Python, SQL Server, and modern ELT patterns.
- Qlik Sense and existing BI estates where continuity matters.
- RAG application patterns, embeddings, vector search, and grounded knowledge experiences.
A platform designed for the workload
Ingest & orchestrateBatch, API, event, and CDC patterns
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Transform & modelReusable logic, tested transformations
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Serve & observeGoverned models, monitoring, access
Engagement options
Right-sized support for your next milestone.
Architecture sprint
Clarify the current-state landscape, target architecture, key risks, and a prioritized delivery roadmap.
Plan a sprint ↗Project delivery
Move a defined data, reporting, migration, or modernization initiative from design through release and handover.
Scope a project ↗Continuous improvement
Strengthen an existing platform through targeted optimization, operational support, documentation, and backlog delivery.
Improve a platform ↗Not sure where to begin?
Start with a focused discovery conversation.
We’ll help turn an open-ended data challenge into a clear set of options and next steps.