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Substrate

Substrate

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The lakehouse, engineered.

Databricks gives you the platform. We deliver the pipelines, models, and governance on it.

Talk to Our Databricks Team

What we deliver under Databricks

A Databricks investment is only as valuable as the engineering capacity behind it. The platform is powerful; the work to populate it, govern it, and keep it producing is what most organizations underestimate.

What does co-architected mean?How does Unity Catalog fit in?Who deploys Substrate?Can you ship outcomes?What does co-architected mean?How does Unity Catalog fit in?Who deploys Substrate?Can you ship outcomes?What does co-architected mean?How does Unity Catalog fit in?Who deploys Substrate?Can you ship outcomes?What does co-architected mean?How does Unity Catalog fit in?Who deploys Substrate?Can you ship outcomes?
Is the lakehouse baked in?How do you handle workspaces?Which systems do you ingest?Where does DBU pricing come in?Is the lakehouse baked in?How do you handle workspaces?Which systems do you ingest?Where does DBU pricing come in?Is the lakehouse baked in?How do you handle workspaces?Which systems do you ingest?Where does DBU pricing come in?Is the lakehouse baked in?How do you handle workspaces?Which systems do you ingest?Where does DBU pricing come in?
Can you run inside our estate?What does the loop look like in production?How do you govern data?Can you run inside our estate?What does the loop look like in production?How do you govern data?Can you run inside our estate?What does the loop look like in production?How do you govern data?Can you run inside our estate?What does the loop look like in production?How do you govern data?

Substrate deployment

We deploy Substrate directly into the customer's Databricks workspace, ingest Unity Catalog as ground truth, and run engineering loops against the lakehouse.

Databricks-tuned delivery

Delivery posture tuned to Databricks idioms by default DLT, Workflows, Unity Catalog, and MLflow baked into how we ship.

Lakehouse as runtime

The lakehouse is a first-class runtime for the AI work Substrate executes inside customer environments no learning curve on customer time.

Co-architected references

Reference architectures co-architected with Databricks depth most consultancies cannot match because we arrive already inside the platform.

Substrate solutions on Databricks

Pre-packaged Substrate solutions on Databricks

Each of these is a pre-scoped engagement shape, priced in ECUs, delivered against a known story set.

Lakehouse Migration Engine.

Migrate legacy data platforms to Databricks ingesting schemas, pipelines, and reports as inputs, generating a lakehouse target with continuous parity validation.

Pipeline Modernization on DLT & Workflows.

Convert legacy ETL stored procedures, hand-written Spark jobs, ad-hoc orchestration into Databricks-native primitives with schema-aware engineering throughout.

Unity Catalog Rollout & Data Governance Program.

Stand up Unity Catalog as the organization's data control plane. Substrate enforces schema, lineage, contract, and access posture across every change.

Production ML & AI on Databricks.

Build and operate production ML and GenAI workloads end-to-end on Databricks training, evaluation, registry, serving with the evaluation harness that makes the non-deterministic outputs safe to ship.

Data Contracts as a First-Class Workload.

Convert implicit producer/consumer relationships into enforced contracts.

DBSQL & Serverless Cost Engineering.

Cost engineering on Databricks Serverless SQL as a continuous workload, not a quarterly cleanup.

What changes for the customer

The throughput is the bottleneck.We take it on directly.

  • 01

    The catalog drifts

    Unity Catalog policies lapse, lineage breaks, governance rots between reviews.

  • 02

    Pipelines bit-rot

    DLT and Spark jobs decay quietly until the next outage forces a rewrite.

  • 03

    Notebooks never ship

    The model that worked in the notebook stalls on the way to production.

Outcome guarantee

The work we're hired to ship, ships.

The same guarantee that applies anywhere else applies here. The lakehouse becomes a system engineering work happens against continuously not a project that periodically gets attention.

Make the lakehouse produce.

Let's build something that lasts. Our team is ready to talk.

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