Does BI Backlog need access to our actual data?

No. BI Backlog analyzes metadata and usage information without requiring access to the underlying business data.

How long does a migration assessment take?

Assessment timelines vary based on the size and complexity of the BI environment, including the number of dashboards, reports, users, and data sources involved.

What does an assessment cost?

Assessment costs depend on the scope of the engagement, BI environment complexity, and migration requirements. KPI Partners provides pricing based on each organization’s needs.

Redefine what's
possible

One Governed Platform for Transactions, Analytics, and AI

KPI Partners helps enterprises bring operational data, analytics, and AI agents together on Databricks Lakebase, so live data reaches the apps and agents that act on it, governed by Unity Catalog from day one.

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Databricks Silver Partner, Migrate & Modernize Specialized

What Databricks Lakebase Changes for Each Team

1 Executive Leadership

Run fewer separate databases and sync pipelines, and build the foundation autonomous AI needs.

2 Business Leaders

Move from insight to action faster, with apps and AI agents working on live operational data.

3 Technical Decision Makers

Govern operational and analytical data under one Unity Catalog model, with less data movement to maintain.

4 Engineers and Architects

Build on standard Postgres next to the Lakehouse, with synced tables, instant branching, and a governed home for agent state.

Operational Data Is the Next Step

for Enterprise AI

Many enterprises have already modernized analytics on the Lakehouse. The transactional side

often still lives in separate databases, linked by sync pipelines that add cost and delay. As AI

moves from answering questions to taking action, closing that gap becomes the opportunity.

Three Ways to Put Databricks

Lakebase to Work

Start from where your estate is today, from any source system. Each

entry point delivers value on its own and builds toward the next.

Real-Time Data for Apps and APIs

Serve curated, governed Lakehouse data to the apps and application programming interfaces (APIs) your teams and customers use every day, without building another copy.

Operational Database Modernization

Move legacy online transaction processing (OLTP) databases, custom application databases, and integration stores onto Lakebase, with schemas and procedural logic converted and every table reconciled.

AI Agents That Remember and Act

Give agents fast reads of live data, stateful memory in Lakebase, and a governed path to write approved actions back to your systems of record, with people in control.

How We Engage

Each engagement has a defined scope and outcome, so

you can start small, prove value, and scale on evidence.

We inventory your operational databases, apps, and agent plans, then classify each workload: stay, serve from Lakebase, or convert.

Workload map across stay, serve, and convert
Target architecture on the Lakehouse and Lakebase
Prioritized release plan

We take one process into production on Lakebase: a real-time app, a converted database, or an agent with memory.

Synced tables serving live, governed data
A Databricks App or API in production
Database branches for safe testing

We convert schemas and procedural logic from any source into Postgres on Lakebase in waves, reconciling every table before cutover.

Generative AI (GenAI) assisted schema and code conversion
Table-level reconciliation with our Data Quality Validator
Legacy database decommissioning plan

We keep apps, agents, and databases reliable and costs predictable once they are live.

Monitoring, alerting, and incident response
Compute and cost optimization
New apps, agents, and sources onboarded

Moving to Lakebase from the Systems You Run Today

We work from any source. We map each workload to its Lakebase pattern, convert what needs converting, and reconcile the results before cutover.

Built to De-Risk Your Lakebase Journey

Lakebase-Ready Architecture

Patterns that unify transactional and analytical workloads, designed for real-time insight and AI at scale.

Proven Modernization Discipline

Our Data Platform Migration Accelerator brings GenAI-powered conversion and automated validation, proven across Oracle, Informatica, and other enterprise estates moving to Databricks.

AI-Ready Operational Data

Governed data models that give apps and agents trusted business context, not raw tables. IQ Foundry brings domain agents for procurement, supply chain, HR, sales, and finance, and its SalesIQ agent already runs on Lakebase.

Governance-First Execution

Unity Catalog access control, lineage, and audit in place from day one, ready for regulated environments.

A certified Databricks partner, validated through real customer migrations

Explore the KPI Partners and Databricks partnership

Impact across industries

SalesIQ: Agentic Proposal Generator on Databricks Lakebase

Read Blog

Databricks Lakebase: The Future of OLTP in an AI-Ready Lakehouse

Read Blog

Oracle ADW to Databricks Migration for a Global Insurance Company

Read Case Study

Common Questions About Databricks Lakebase

What is Databricks Lakebase?

Lakebase is a fully managed, serverless Postgres database built into the Databricks platform. It handles low-latency transactional work such as application state, agent memory, and operational records, scales automatically with demand and down to zero when idle, and is generally available on AWS and Azure.

How is Lakebase different from the Lakehouse?

The Lakehouse holds governed history for analytics and AI. Lakebase serves live, low-latency reads and writes for apps and agents. Synced tables bring curated Lakehouse data into Lakebase, and operational changes can flow back for analytics, all under Unity Catalog.

Do we have to replace our ERP or existing databases?

No. Systems of record such as your ERP stay in place. We classify each workload as stay, serve from Lakebase, or convert, and most organizations start with one app, database, or agent before expanding in waves.

Which databases can move to Lakebase?

Any source. Because Lakebase is built on standard Postgres, most existing drivers and tools work with minimal changes. We convert schemas and procedural logic from sources such as Oracle Database, SQL Server, IBM Db2, and MySQL, then reconcile every table before cutover.

How does Lakebase support AI agents?

Agents keep state, memory, and approvals in Lakebase, right next to the governed data they reason over. Lakebase supports pgvector for embeddings, and approved actions can be written back to your systems of record with people in control.

How do teams test changes without risking production?

Lakebase creates instant, zero-copy branches of production data in seconds, so teams can test and develop against real data safely, with point-in-time recovery if something goes wrong.

Ready to Put Databricks

Lakebase to Work?

Whether you are planning your first real-time app, modernizing operational databases, or giving AI agents a governed memory, KPI Partners will help you find the right starting point.

Talk to an Expert

KPI Partners and Databricks partnership

Standard Enterprise

AI Engagement Model

Success Stories

Reduced claims turnaround using AI-driven workflow automation, improving speed and consistency across operations.

Global Financial Services Leader

Enabled self-service access to ERP and analytics using governed GenAI, reducing IT dependency and improving decision speed.

Leading U.S. Beverage Manufacturer

Improved reliability through predictive intelligence and root-cause analysis embedded into operational workflows.

Global Manufacturing Leader

Data Platform Migration for Modern Analytics

KPI DataBridge Suite is designed to help enterprises modernize their data and analytics infrastructure across:

BI Modernization 🔗
Data Platform Migration 🔗
Data Products 🔗