Databricks, delivered in weeks, not months.
New DAIS has developed AI agents that encode decades of Data Engineering and Data Modeling experience. We put them to work building governed medallion lakehouses on the Databricks Data Intelligence Platform, then deploy AI analytic agents on top so your teams query the data in plain language. Less time, less cost than legacy consulting.
Everything you need to stand up an AI-ready lakehouse.
Three integrated workstreams take you from a legacy data estate to governed, intelligent applications running on Databricks, all delivered on your cloud, under your control.
Platform & Environment Build
We architect and deploy a production-ready Databricks environment on your existing AWS, Azure, or GCP infrastructure, with the security and governance framework that underpins everything downstream.
- Architecture design & Databricks deployment
- Unity Catalog governance for data & models
- Unity AI Gateway controls for agents & LLM traffic
- Runs in your cloud: data never leaves your perimeter
AI-Assisted Lakehouse Implementation
Our Data Migration, Data Modeling & Planning, and Data Engineering Agents interpret your legacy ETL and rebuild it on Databricks using Lakeflow Connect for ingestion and Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) for Bronze-to-Gold transformation. The output is production ETL code that stays maintainable and refactorable, not opaque one-shot LLM output.
- Lakeflow Connect ingestion from source systems
- Lakeflow Spark Declarative Pipelines (Bronze → Silver → Gold)
- Custom Data Modeling, Planning & Data Engineering Agents
- Maintainable, refactorable ETL built to evolve with the business
Genie Spaces & Conversational Analytics
We deploy Databricks Genie Spaces and Genie One against your Gold semantic model, purpose-built natural-language interfaces tuned for business users. We also stand up AI/BI Dashboards and integrate with any analytics or visualization tools your teams already use.
- Genie Spaces deployment, semantic enrichment & tuning
- Genie One natural-language querying across spaces
- Databricks AI/BI Dashboards on the Gold semantic model
- Integration with existing BI and visualization tools
Three AI Harnesses. Native Databricks features. Bronze to Gold.
PETL runs end-to-end on Databricks primitives. Auto Loader for ingest, Lakeflow Spark Declarative Pipelines for the physical build, Unity Catalog for governance, with a human in the loop at every step.
Auto Loader, Lakeflow, Unity Catalog volumes
Ingests source data with Auto Loader and Lakeflow Spark Declarative Pipelines for CDC, stages files in Unity Catalog volumes, and lands the Bronze layer with row-level lineage from day one.
Unity Catalog managed tables, synthetic design
Designs star and snowflake schemas as Unity Catalog managed tables. Iterates on a synthetic copy of your data with expert feedback, then generates the PySpark ETL that stitches Silver to Gold.
Lakeflow orchestration, governed promotion
Builds the physical Silver and Gold layers in Lakeflow Spark Declarative Pipelines, applies expectations-based validation, and promotes from QA to Prod under Unity Catalog governance.
Struggled to get Genie working on your own?
You're not alone. Genie Spaces and other natural-language interfaces only work when the foundation underneath them is right: well-modeled Gold tables, business-aware semantic context, and the kind of metadata enrichment that lets an LLM answer like an analyst, not guess. New DAIS specializes in standing these up and tuning them until business users actually trust the answers.
A 25-year engineering legacy, applied to the modern stack.
Our team has spent decades designing and building data warehouses and analytics platforms for enterprises from mid-market through Fortune 100, across every era of the stack: on-prem classic warehouses, dedicated appliances like Netezza and SAP HANA, and now distributed cloud architectures like Databricks. The same rigor goes into every Databricks engagement.
Speed by design
Initial lakehouse and reporting delivered in weeks, not 6-12 month programs.
Governed & secure
Deployed in your cloud with Unity Catalog governance and full auditability.
Engineered for value
Each agent encodes decades of data engineering expertise, at a fraction of legacy consulting cost.
How a Databricks engagement runs.
An iterative, collaborative approach. We work directly alongside your team at every stage.
Architect & Deploy
Design the platform and stand up a production-ready Databricks environment with governance and security.
Scope & Profile
Identify the initial scope; run requirements workshops and data profiling.
Migrate & Model
Agents build governed Lakeflow Spark Declarative Pipelines and the Fact / Dimension data model with the semantic enrichment Genie needs.
Report & Activate
Deploy AI/BI Dashboards and Genie Spaces, integrate any incumbent BI tools, train users, and hand over.
Ready to put Databricks to work?
Talk directly with our founding partners about migrating your data to Databricks and deploying autonomous AI agents on top of it. Selective engagements only.