End-to-end data & AI, native to Azure

From architecture design through production operations — every service is built on deep Azure Databricks expertise and Microsoft ecosystem fluency.

Production-grade lakehouse architecture

We design and build lakehouse architectures on Azure Databricks — from raw ingestion through curated, governed data products ready for analytics and AI. Every pipeline is built with Delta Live Tables, medallion architecture, and Unity Catalog governance from day one.

Azure DatabricksDelta LakeDelta Live TablesUnity CatalogPySparkdbtADLS Gen2Medallion ArchitectureStructured Streaming

Power BI serving layers, done properly

We bridge the gap between Databricks data platforms and the Power BI dashboards your business users depend on — with proper optimization, not quick-and-dirty connections. Direct Lake mode, semantic model publishing, and query tuning over Databricks SQL warehouses.

Power BIDirect LakeSemantic ModelsDirectQueryDatabricks SQLMicrosoft FabricOneLake Shortcuts

Structured migration from legacy Azure services

We migrate Azure Synapse Analytics, Azure Data Factory, legacy data warehouses, and on-premises platforms to Azure Databricks — with structured roadmapping, governance mapping, and zero-downtime transitions.

Synapse → DatabricksADF MigrationEDW ModernizationHadoop MigrationAssessment & Roadmapping

From MLOps to production GenAI

From MLOps pipelines with MLflow to production GenAI deployments and agentic AI systems — all integrated into your Azure security, compliance, and identity framework. We build AI that runs in your governance model, not around it.

MLflowMLOpsGenAI / LLMsRAG ArchitectureAgentic AIModel ServingAzure AI Services

Single-pane governance across platforms

Unity Catalog + Microsoft Purview integration for unified metadata, policy enforcement, and lineage tracking. Entra ID SSO, Private Link networking, conditional access — the security architecture Microsoft-standardized enterprises require.

Unity CatalogMicrosoft PurviewEntra IDPrivate LinkZero TrustConditional Access

Control Databricks spend without limiting value

Cluster right-sizing, auto-scaling policies, spot instance strategies, and Azure Cost Management integration that keep Databricks spend under control while maximizing workload throughput.

Cost OptimizationAuto-scalingSpot InstancesAzure Cost ManagementDBU Optimization

How we work

Every engagement follows a structured methodology designed to deliver production outcomes, not proof-of-concept demos.

01

Assess & Discover

We audit your current data estate, map workloads, and identify the migration or modernization path with the highest ROI.

02

Architect & Design

Lakehouse architecture, governance framework, security model, and cost projections — all documented before writing code.

03

Build & Migrate

Iterative delivery using our accelerators and reference architectures. Each sprint produces working, tested data products.

04

Optimize & Operate

Post-deployment tuning, FinOps governance, and optional managed services to keep your platform at peak efficiency.

Let's architect your data platform

Start with a complimentary architecture assessment — we'll map your current state, identify opportunities, and propose a concrete path forward.