Delbridge Solutions
Delbridge Solutions

Databricks Partner

AI-Ready Data Platforms, Built on Databricks

We design, build, and govern data lakehouse on Databricks platform.

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TRUSTED BY TEAMS WHO DEPEND ON THEIR DATA

Problems We Solve

Most Databricks conversations start somewhere less glamorous than AI. They start with a platform that has grown faster than anyone can govern it.

Data silos

Finance, operations, and product each build their own version of the truth, and reconciling them becomes a full-time job.

Governance as an afterthought

Access rules, lineage, and ownership get retrofitted onto a platform already in production, which is expensive and rarely complete.

AI stuck in pilot

Models and agents demo well and then stall, because the data underneath them was never built to serve production workloads.

Platform sprawl

Pipelines multiply, costs drift, and nobody can say with confidence which jobs still matter.

Waiting on the data team

Business users file a request and wait days for an answer that should have taken a minute.

Our Datarbricks Capabilities

Databricks is a broad platform, and the parts that matter depend on where you are. Here is where we work, whether you are standing up a lakehouse for the first time or trying to get more out of one you already have.

Data Engineering and Pipelines

We build and modernize ingestion and transformation on Lakeflow, using Spark Declarative Pipelines so pipelines describe the result they should produce instead of the steps to get there. That means less brittle orchestration code, built-in data quality expectations, and pipelines your team can actually read six months later.

  • Build batch and streaming pipelines with Spark Declarative Pipelines
  • Ingest from cloud storage, databases, and message buses with Lakeflow Connect
  • Handle change data capture and slowly changing dimensions without custom merge logic
  • Consolidate orchestration onto Lakeflow Jobs and retire legacy schedulers

Genie and Agentic AI

Genie is how business users get answers without filing a ticket. We set up Genie Agents against trusted datasets, metrics, and business rules, so the answers people get are grounded in data your team has approved, and we help you decide which questions should become reusable agents rather than one-off queries. Done properly, this is the difference between a chat box that guesses and one your CFO trusts.

  • Configure Genie Agents with curated datasets, metrics, and business rules
  • Test agent answers against known questions before anyone relies on them
  • Bring Genie into the tools teams already use, including Slack and Teams
  • Decide which use cases justify a dedicated agent and which do not

Unity Catalog and Data and AI Governance

Unity Catalog gives you one place to manage access, lineage, and metadata across tables, models, dashboards, and agents. We implement it as a foundation rather than a cleanup project: permissions structured around how your business is actually organized, lineage you can hand to an auditor, and governance that covers your AI assets, not only your data.

  • Migrate from Hive metastore to Unity Catalog without breaking downstream work
  • Design catalog and schema structure around business domains, not team habits
  • Implement fine-grained access control, including row and column level rules
  • Establish lineage, auditing, and monitoring across data, models, and agents

Lakebase and Apps

Lakebase is serverless Postgres inside the lakehouse, and it removes one of the most tedious problems in data architecture: keeping an operational database in sync with your analytics platform. We use it for teams that need transactional workloads, application backends, or agent state sitting next to the data they report on, without another ETL pipeline holding it together.

  • Stand up serverless Postgres that scales with load and scales to zero when idle
  • Serve governed lakehouse data to applications at low latency
  • Sync Postgres changes back to Delta tables for reporting and audit
  • Use database branching to test against realistic data without touching production

Analytics, ML, and Production AI

Model development, tracking, and deployment with MLflow, plus the surrounding work that decides whether a model survives contact with production: feature availability, monitoring, retraining triggers, and cost control.

  • Track experiments and manage model versions with MLflow
  • Build feature pipelines and serve features to models in production
  • Deploy models and agents behind governed serving endpoints
  • Monitor drift and performance, and set retraining triggers that fire on evidence

Book a Free Consultation Session!

Curious what a real Databricks setup would actually look like for your team? Book a free 30 minute session and find out, no strings attached. We’ll walk through your current data architecture together, talk honestly about where Databricks fits and where it doesn’t, and show you a Genie workflow running against a use case that matters to you.

Contact Our Team

What our customers say

We make transformation feel possible. With deep technical skill and a refreshingly human approach, we help teams move faster, work smarter, and build solutions that actually stick.

Trusted Clients
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“It is great to work with a dedicated consultant from Delbridge Solutions who truly understands our business model and evolving needs. They take the time to explain every issue, improvement, or new process in a clear and practical way, helping our team learn as we go. Because of their guidance and ongoing support, we feel more confident in our system and increasingly less dependent.”

Linda Heinze

VP of Financial Systems and Reporting, ICBA
“The entire team is professional. They have technical experts whose experience and knowledge shine. Every time we reach out, we receive a timely response and their team members have gone above and beyond to ensure our implementation was and continues to be successful.”

Josh Issertell

Planning & Analysis Manager, American Crystal Sugar
“It was very good, the Delbridge team was very knowledgeable and fast.”

Christian Sims

FP&A Manager, Schumacher Electric

Real transformations, proven results

See how organizations across industries modernize finance, operations, and decision-making with Delbridge’s expertise.

Explore Customer Stories

Let’s deliver impact

Databricks programs lose momentum when data platforms grow faster than governance, pipelines become difficult to manage, and analytics and AI initiatives are pushed into production without the right architectural foundation. Databricks offers a powerful unified platform for data engineering, analytics, and AI, but strong outcomes depend on disciplined execution across platform design, data pipelines, governance, workload performance, and cost management. The result is a more scalable data environment, faster paths to production, and better control over platform complexity, spend, and data quality.

At Delbridge Solutions, we support Databricks with a data-first approach. We help teams design scalable lakehouse foundations, modernize data pipelines, unify fragmented tooling, and build platforms that support both analytics and AI workloads. From foundational implementation and enterprise data streaming to governance, machine learning applications, and ongoing optimization, we focus on helping organizations use Databricks in a way that is efficient, secure, and ready to evolve with business demand.

Learn About Delbridge
What does it mean that Delbridge is a Databricks Bronze partner?
1
Databricks restructured its partner program in 2026 around four tiers: Bronze, Silver, Gold, and Platinum. Bronze means we are formally enrolled, with access to Databricks training, enablement, technical resources, and partner support. What we bring is a data engineering practice built over years on other platforms, applied to Databricks with Databricks' own resources behind us. We are actively working toward Silver.
What is included in the free session, and what is not?
2
Included: a review of your current data architecture, a walkthrough of where Databricks would and would not help, and a demonstration of a Genie workflow against a use case you care about. Not included: access to your production systems, a full assessment of your existing pipelines, or a fixed-price proposal. Those come later, if it makes sense for both of us.
What happens after the session?
3
You get a written summary of what we found and what we would do first. If you want to keep going, the usual next step is a short scoped engagement with a defined deliverable, not an open-ended retainer. If the session tells us Databricks is not the right answer for your problem, we will say so and you will not hear from us again unless you ask.
Do you work with data platforms other than Databricks?
4
Yes, and it is most of what we do. We are a MongoDB partner and the exclusive partner in MongoDB's Migration Factory offering, with a proprietary reporting solution built for MongoDB data. We also work across Snowflake, AWS, Microsoft, and Redis, alongside a long-running enterprise reporting and performance management practice. That range is why we can tell you when Databricks is the wrong tool.
We already run Databricks. Can you help without a migration?
5
That is a common starting point. Existing environments usually need governance structure, pipeline consolidation, cost control, or a path to putting AI workloads into production rather than a rebuild. We start by looking at what is already there.
Which clouds do you support?
6
Databricks runs on AWS, Azure, and Google Cloud, and we work across all three. Feature availability sometimes differs by cloud, particularly for newer capabilities like Lakebase, and we will tell you where those differences affect your plan.

Databricks solutions that scale with your roadmap

See how Databricks supports modern data engineering, real-time analytics, unified governance, and AI-ready data platforms, and how Delbridge helps you apply it with strong architecture, practical delivery, and operational discipline.

Learn more about Databricks

See Databricks in Action

In a live demo, explore how we approach Databricks architecture, lakehouse implementation, enterprise data streaming, governance and data quality frameworks, workload optimization, and support for both analytics and AI use cases, so your Databricks environment stays scalable, efficient, and ready to grow with your business.

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Take the next step

Fill out the form below, and our team will connect with you within a few hours. No matter where you are in your data, AI, or performance journey, we’ll help design a path forward that meets your needs.