We help enterprise data and engineering leaders consolidate fragmented warehouses, build production-grade pipelines, and operationalize AI on the Databricks Lakehouse.
Our partnership helps clients move faster with solution patterns aligned to the Databricks ecosystem, stronger architecture choices up front, and a delivery team that can translate platform investment into governed business outcomes.
From first architecture review to ongoing managed services, our Databricks practice covers the full lifecycle of building and running a modern Lakehouse.
Replatform legacy warehouses and on-prem Hadoop estates onto a unified Databricks Lakehouse. We handle target architecture, schema translation, landing-zone setup, workload mapping, and phased cutover with measurable cost and performance baselines.
Shape the business case, roadmap, and operating model before delivery begins. We help leaders define platform priorities, sequence use cases, align stakeholders, and make smarter Databricks investment decisions from the start.
Production-grade ingestion and transformation built on Delta Lake, DLT, and Workflows, with CI/CD, observability, and lineage from day one. Rebuild brittle Informatica and SSIS jobs as resilient assets.
Enterprise-grade governance across catalogs, schemas, and external locations. Role- and attribute-based access, lineage, and audit are wired to your IDP and aligned to SOX, HIPAA, and GDPR controls.
Take models and AI assistants from concept to production. Feature engineering, MLflow, model serving, vector search, evaluation harnesses, and guardrails are designed for enterprise-grade performance, governance, and trust.
Keep the platform healthy after go-live with monitoring, cost optimization, release support, incident response, and ongoing platform engineering. We help your team sustain momentum without carrying the full operational burden alone.
Data intelligence isn’t horizontal. We bring pre-built reference architectures, data models, and accelerators tailored to the regulatory and operational realities of the industries we serve.
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Retail & Consumer Goods
Data intelligence isn’t horizontal. We bring pre-built reference architectures, data models, and accelerators tailored to the regulatory and operational realities of the industries we serve.
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Automotive
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Professional Services
We align stakeholders on business priorities, assess the current estate, and shape the target Databricks architecture. This phase sets the roadmap, delivery sequence, and success measures before build work begins.
We stand up the core Lakehouse foundation, including environments, ingestion patterns, orchestration, security controls, and reusable engineering standards. The result is a stable platform ready for downstream analytics and AI use cases.
With the foundation in place, we build early dashboards, data products, and AI or analytics prototypes that demonstrate business value quickly. This phase helps teams validate use cases and refine priorities before broader rollout.
We productionize proven workloads, expand adoption across teams, and scale the platform through automation, performance tuning, and release discipline. The focus is moving from a strong pilot footprint to reliable enterprise-wide usage.
We reinforce long-term success with governance, monitoring, access controls, lineage, and ongoing platform optimization. This keeps the environment scalable, secure, and manageable as data products, users, and compliance needs continue to grow.
We’re not a Databricks-only shop. Our consultants have spent careers landing data into ERP, governance into regulated industries, and analytics into the hands of executives. That perspective is what your platform actually needs.
Two decades delivering ERP, data warehouse, and integration programs for global enterprises. We understand legacy estates because we built and ran them.
From ERP to AI
Source-to-insight capability on a single team, from Oracle, SAP, Salesforce, and custom apps into Databricks, then into governed data products and AI workloads.