Databricks Consulting for Enterprise AI at Production Scale
DS Stream is a Databricks Partner with 80+ enterprise projects delivered — from Lakehouse data foundations to production agentic AI. We design, build and operate the platforms, operating models and AI use cases that create measurable business value for Fortune 500 organizations.
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End-to-end Databricks delivery for Fortune 500 CPG and Retail
Governed by design, proven at scale. Our delivery is built on 80+ projects on Databricks, a certified team, standardized delivery patterns, and reusable accelerators that reduce time-to-value.
Do you have technical credibility for production-scale AI on Databricks?
Most enterprises hit four recurring blockers when scaling AI on Databricks: unclear platform risk, ownership gaps between data and AI teams, missing engineering standards, and slow delivery cycles. We close these gaps with a proven operating model and reusable patterns.
Databricks Expertise
From scalable Lakehouse foundations and declarative data pipelines, through governed ML/AI operations and business-facing analytics, to production-grade agentic AI.
Our expertise spans the full platform stack, end to end.
We have Databricks-certified team members in Data Engineer, Data Engineer Professional, and Machine Learning Professional roles.
Certification is backed by real production delivery.
We use standardized patterns for Databricks architecture, security, CI/CD and operations.
These patterns are refined across 80+ enterprise projects.
We have built reusable accelerators on Databricks that reduce time-to-value for clients.
These accelerators eliminate rebuilding common components from scratch.
How We Build Your Databricks Practice
Conduct an architecture audit, technology inventory, cloud footprint review, and governance analysis to understand the current state.
Run a blueprint whiteboarding workshop using DS Stream's reference architecture as the starting point for the target design.
Build the target architecture with a reusable component library and governance controls designed in from the start.
Select the right technology components: Databricks services, cloud AI services, MLOps/LLMOps tooling, and IaC standards.
Business Impact
10x faster time to first AI product in production.
60% reduction in model deployment effort through automation.
100% model visibility — every model tracked, governed and auditable via MLflow and Unity Catalog.
Who This Is For
Industries We Serve on Databricks
We bring deep, vertical-specific Databricks experience across regulated and data-intensive sectors — from CPG and Retail to Financial Services and Healthcare.
Most Common Questions
Partnership means production delivery — not certification alone. DS Stream has 80+ enterprise Databricks projects completed.
DS Stream has a Databricks-certified team (Data Engineer, Data Engineer Professional, Machine Learning Professional), standardized delivery patterns for Databricks architecture, security and CI/CD, and reusable accelerators built on the platform. Partnership is grounded in outcomes, not vendor alignment.
Platform access is table stakes. The hardest challenges are the operating model, governance, and MLOps layer underneath.
DS Stream brings 80+ projects of production delivery patterns, reusable accelerators, ISO 42001-aligned governance frameworks, and an AI Factory operating model that compresses time-to-value. We can compare approaches and identify any gap we can fill.
Unity Catalog is non-negotiable on every DS Stream engagement — governance is embedded from day one.
Every engagement includes Unity Catalog for centralized metadata management, column-level access control, full data lineage, and immutable audit logging. MLflow model registry tracks every model version, experiment, and deployment. The result is 100% model visibility and governance coverage, as demonstrated in a leading CPG AI Engineering Platform engagement.
CPG is DS Stream's deepest credential — multiple years building the AI Factory for a Fortune 500 CPG company.
Secondary focus areas are Financial Services (governance and MLOps) and Retail and Manufacturing using CPG proof points. All 80+ Databricks projects span enterprise-scale organizations with complex data environments.
The engagement model is phased and value-gated.
For the AI Factory, Phase 1 (MVP, 8 weeks) delivers a governance framework, Databricks platform foundation, and the first two use cases in production. ROI baseline is captured before committing to Phase 2. For Agentic CPG Data Operations, a 4-week PoC (credited toward full implementation) delivers a working prototype with 5 automated sources. Clients proceed only when each stage delivers validated results.
Pilot phase is the ideal time to engage.
The most expensive mistake in enterprise AI is building pilots without a governance architecture and reusable platform foundation, then retrofitting both after scale. Even a short architecture conversation at the pilot stage can eliminate months of rework and technical debt later.
DS Stream is deliberately focused rather than broad.
Our CPG AI Factory depth on Databricks is specific — multiple years of ongoing platform partnership, 80+ projects of production patterns, and reusable accelerators that generalist SIs cannot replicate. We build alongside client teams with genuine knowledge transfer as a design objective, not a dependency model. Clients leave every engagement more capable.
Ready to Industrialize Your Databricks Platform?
Book a free 30-minute architecture review. We will walk through your current Databricks setup, identify the highest-impact wins, and outline a clear path to production-grade AI delivery.
Architecture audit
Conduct a full architecture audit of the current Databricks environment, including technology inventory, cloud footprint, and governance review.
Platform foundation
Build the Databricks platform foundation with governance controls, reusable architecture patterns, and CI/CD pipelines in place.
First two use cases
Deliver the first two use cases in production with ROI baseline captured before proceeding to the next phase.