Foundational context: Cross-industry & function-specific accelerators for Lakebase

Foundational context: Cross-industry & function-specific accelerators for Lakebase | Databricks Blog

Skip to main content

Automated Database Migration & Modernization: Partners with specialized accelerators that automate the risk assessment, schema conversion, and code migration from legacy systems like Oracle, Informatica, and SQL Server, using Lakebase database branching to safely rehearse cut-overs.

Stateful Memory for Agentic AI: A vast array of SI solutions that leverage Lakebase as a high-velocity, low-latency ‘working memory’ layer, enabling autonomous AI agents to maintain multi-session context, track workflow states, and safely execute real-time operational writes.

Ready-to-Deploy Functional Applications: Industry-specific accelerators across Finance, Marketing, Sales, and Supply Chain translate Lakebase's capabilities into immediate business value.

Databricks Lakebase is a fully managed, serverless Postgres database built for the agentic era. For years, teams have paid an architectural tax, running separate operational and analytical systems and connecting them with brittle ETL pipelines. Lakebase closes that gap. It is 100% standard Postgres, built into the Databricks Platform alongside the lakehouse and Unity Catalog, and it separates compute from storage to deliver serverless economics. Today, native integration through Synced Tables and Lakebase CDF moves data between the lakehouse and Lakebase automatically, with no pipelines to build. This is the first step toward our longer-term vision of Lake Transactional Analytical Processing (LTAP): transactional and analytical workloads running together on one platform, under one governance model, so applications, models, and agents can read and write operational data without standing up a separate serving stack.

Engineered to eliminate infrastructure friction, Lakebase introduces ground-breaking primitives like copy-on-write database branching. Developers and autonomous AI agents can instantly spin up isolated, zero-storage production clones in seconds for risk-free testing, alongside intelligent autoscaling that dynamically scales compute to zero when idle. Governed natively through Unity Catalog, Lakebase unifies enterprise security and auditability across your entire data estate. To help organizations realize this value immediately, our global consulting and SI partner ecosystem has built a powerful set of cross-industry and function-specific solutions. This blog highlights these ready-to-deploy offerings, designed to accelerate enterprise data modernization, MLOps, and agentic AI transformation at unprecedented speed.

This blog showcases innovative partner solutions built on Databricks Lakebase across the following categories:

Technology Solutions

Finance

Marketing

Sales

Supply Chain

Human Resources

Customer Service

Operations / Project Management

Technology Solutions

Advancing Analytics

Advancing Analytics’ Lakebase Wizard helps organizations move existing PostgreSQL workloads into Databricks Lakebase with confidence, not guesswork. The accelerator assesses a source Postgres database, highlights compatibility risks, and guides teams through a structured migration covering discovery, decision, rehearsal, cut-over and validation. It identifies issues such as unsupported extensions, session-state dependencies, authentication changes and platform quotas before they become delivery problems. Using Lakebase branching, teams rehearse migrations safely, validate outcomes and reduce cut-over risk. The result is a practical, repeatable path from legacy operational databases to lakehouse-native Postgres on Databricks, governed through Unity Catalog. Watch this video and read this blog to learn more.

Aimpoint Digital

AgentOps: Genie spaces are intended to be highly specific, built with a single data domain or specialty to ensure high accuracy, but what happens if you need to blend data from multiple Genie spaces? Aimpoint Digital’s multi-agent Genie system, powered by their Brickbuilder Accelerator AgentOps provides deep observability and a robust deployment framework. Gain access to insights through a single chat interface backed by Lakebase for long term chat history, with a powerful custom supervisor agent capable of reasoning across multiple Genie spaces. Integrate with your business users via apps, slack, teams or wherever business decisions are made. Maintain focused Genie spaces while unlocking its true potential through a single customizable interface driving real, long-term adoption. Read this blog to learn more.

Avanade

Data to Impact: AI-Powered Innovation with Genie & Lakebase - Avanade helps organizations realize the full value of Databricks Lakebase by designing and delivering unified, AI-ready data platforms that combine operational and analytical workloads. In a recent engagement with a leading UK fashion retailer, Avanade implemented an agent-based AI solution built on Databricks Apps, Lakehouse, and Lakebase to modernize fit room processes. By unifying real-time transactional and analytical data, the solution eliminated manual rework, reduced resource demands, and accelerated supplier collaboration. With governance through Unity Catalog, the client gained trusted, real-time insights—enabling faster decisions, improved efficiency, and a scalable foundation for AI-driven product development and continuous innovation. Read this blog to learn more.

Blueprint

Informatica Data Migration: Data engineering teams modernizing from legacy Extract-Transform-Load (ETL) platforms can now run their Informatica-to-Databricks migrations through a governed, end-to-end workbench. Built on Databricks Lakebase and Unity Catalog, Blueprint's Data Migration Accelerator pairs a six-stage migration workflow (assess, design, migrate, integrate, validate, transition) with Lakebase-served prioritization scores and an agentic conversion flow powered by Agent Bricks. Migration leads, conversion engineers, and validation specialists collaborate inside one Databricks App, with every workflow's state, complexity score, and User Acceptance Testing (UAT) outcome traced back to its underlying Informatica source. Enterprise data teams shift from spreadsheet tracking to a governed, evidence-bearing modernization control plane.

Capgemini

Agentic-ready AI and Data Platform: Capgemini’s ‘Agentic-ready AI and data platform’ accelerates development of custom apps, advanced AI agents and low-latency data products natively on Databricks with the power of Lakebase. It brings architectural patterns, AI-assisted delivery lifecycle and integration best practices proven at large enterprises, as well as use-case templates based on their experience implementing industry-specific processes and platform apps powered by Lakebase.

Celebal Technologies

Eagle Eye IQ Brickbuilder accelerator: Eagle Eye IQ is using Databricks Lakebase as the operational backbone for autonomous data reliability. While Spark and Delta Lake power large-scale data quality analysis, lineage computation, and observability workloads, Lakebase provides the low-latency transactional foundation required for real-time agent coordination and remediation. At the core of Eagle Eye is Aquila AI, Celebal’s Agentic AI guardian. Aquila’s network of 35+ specialized agents use Lakebase to manage task queues, persist investigation context across handoffs, write remediation actions transactionally, and maintain a complete audit trail within the Databricks workspace boundary. From data quality monitoring and lineage analysis to AI observability, contract governance, and autonomous remediation, Eagle Eye IQ closes the loop between detection and resolution. Dive into the related blog, to see how Lakebase and Eagle Eye IQ are transforming observability into autonomous action.

Celebal Technologies Agent Garage: Celebal Technologies' Agent Garage Brickbuilder Accelerator extends the power of Databricks Lakebase into a stateful enterprise agent platform, enabling AI systems to persist memory, maintain workflow state, coordinate multi-agent processes, and securely read and write operational data in real time. Built natively on the Databricks Data Intelligence Platform, it combines Lakebase's transactional foundation with Agent Garage's orchestration and execution capabilities to power durable, context-aware AI applications across enterprise operations. The result is a unified system where data, memory, reasoning, and action work together to drive intelligent execution at scale. Read this blog to see how stateful AI agents are transforming enterprise workflows through persistent memory, coordinated execution, and governed operational intelligence.

Celebal Technologies CausalX is now an official Databricks Brickbuilder Accelerator and the first to operationalize causal AI on Lakebase. Zero-copy Lakebase branches power counterfactual what-ifs; transactional decision logs make every recommendation auditable; and sub-10 ms reads serve live agents and Genie. Ontos adds the governed business catalog, including data products, ODCS contracts, a knowledge graph, and MCP across Unity Catalog. From energy reliability and manufacturing yield to banking adverse-action traces, life sciences synthetic-control arms, retail promo lift, media attribution, telecom churn and public-sector policy what-ifs, CausalX turns 'why' into 'what now': explainable, auditable, and ready for production. Check out this blog to see how this architecture brings causal intelligence and operational execution together on Databricks.

Celebal Technologies CT Visa uses Databricks Lakebase as the migration control plane for enterprise ETL modernization. Every project, parsed object, AI-driven assessment, conversion, validation result, lineage relationship, deployment activity, and JobRun is persisted through a governed operational layer running natively on Databricks. Combined with Unity Catalog, Delta Lake, Databricks AI Model Serving, Workflows, and SQL Warehouses, Lakebase provides the metadata, auditability, and traceability required to manage large-scale migration programs from assessment through deployment. The result is a migration platform where governance, lineage, testing, and operational oversight are built into every stage of modernization. Read here on how Lakebase powers a governed migration control plane for legacy ETL transformation.

CI&T

The Single Interface Multi-Agent System for Genie Orchestration revolutionizes user interaction by providing a unified gateway that integrates multiple communication channels, including WhatsApp, Teams, and Gemini via A2A APIs. This system enables seamless access to various domains and Genie spaces, while also incorporating internal documentation for enhanced support. Central to this solution is a supervisor agent that intelligently assesses user requests, determining appropriate access rights and business context. It orchestrates interactions with specialized agents, ensuring requests are triaged effectively and routed to the correct domain. Additionally, Lakebase serves as a context memory, enriching session continuity and user experience. Read this blog to learn more.

CitiusTech

AI-Driven Database Migration & Modernization (M&M) Accelerator: Healthcare and MedTech organizations often struggle with legacy data platforms that create silos, limit scalability, complicate integrations, and restrict real-time data access. These environments make modernization manual, slow, error-prone, and difficult to govern under regulatory requirements. CitiusTech’s AI-driven migration and modernization accelerator for Databricks Lakebase helps organizations securely transition clinical and operational workloads to a unified, AI-native Lakehouse. The solution combines automated AS-IS assessment, migration planning, phased roadmap creation, GenAI-powered schema and code conversion, workload modernization, and target architecture design. Built on Databricks Lakehouse services, it enables faster, lower-risk, FHIR-compliant, cloud-ready platforms for advanced analytics and AI-driven decision-making. Read this blog to learn more.

Cognizant

Agents that remember - building stateful AI on Databricks Lakebase: Enterprises are deploying AI agents that reason, plan, and act, but most fail in production because they have no persistent memory or state. Cognizant's Stateful Agent Stack, built on Databricks Lakebase, solves this by providing agents with a governed, low-latency operational data store, natively embedded in the Data Intelligence Platform, enabling resumable, auditable, multi-agent workflows across financial services, healthcare, and insurance without managing a single external database. Read this blog to learn more.

No More Write Locks - Real-Time Audit Logging at Scale with Databricks Lakebase: At 10,000+ Databricks workflows and 25,000+ datasets, every API call, pipeline run, and manual query was logged to Delta-based audit tables. At this concurrency, Delta's write-locking model became the bottleneck — writes queued, APIs timed out, and applications slowed platform-wide. Liquid clustering and table tuning eased but never solved it, since the real issue was transactional design, not storage layout. The fix: migrate audit logging to Databricks Lakebase, a fully managed, Postgres-compatible operational database governed through Unity Catalog. Its OLTP engine absorbs high-frequency concurrent writes without locking — cutting audit latency from over 2 minutes to under 2 seconds. Read this blog to learn more.

Building on Databricks Apps + Lakebase - The TrainTrack Story: Certification voucher tracking ran on spreadsheets — manual assignment, no visibility into expiring inventory, no clean trail from request to result. TrainTrack replaces that with a self-service portal on Databricks Apps, running entirely on Lakebase as its Postgres backend. Column-level security is plain SQL grants. Every environment configures itself idempotently from a clone, with database branching and point-in-time recovery built in — no ETL, no duplicate storage. Azure AD SSO, masked voucher codes, and full audit trails round out the security model. Two sprints and 92 automated tests later, TrainTrack proves Postgres can carry real transactional load inside the lakehouse. Read this blog to learn more.

Colibri Digital

Colibri Digital’s Data Market Portal, Aviary, enables users to quickly find, understand, and access the right data for their needs without requiring technical expertise or specialist support. It is built as a Databricks Apps on their bespoke Hummingbird framework, which orchestrates end-to-end data pipelines from multi-source ingestion through to curated consumption. Data is ingested via their proprietary Colibri Foundry, and progressed through a structured transformation pipeline covering data cleansing, standardisation, and modelling, resulting in governed, consumption-ready datasets. Through Aviary’s simple, intuitive interface, users can ask natural language questions—such as identifying datasets containing specific operational or customer insights. This is powered by Databricks Genie, which interprets user intent and performs context-aware searches across the catalog, leveraging metadata and tags to return relevant, governed datasets. Selected results are served back to the UI with ultra-low latency via Lakebase’s app-ready lakehouse synchronization. Read this blog to learn more.

Computomic

Computomic helps enterprises design and implement Lakebase-enabled solutions that solve the limitations of using analytical lakehouse storage for transactional, high-frequency operational workloads. Their solution combines Databricks Lakebase for low-latency operational state, ingestion tracking, metadata management, control-plane coordination, and application-facing updates, enabling scalable analytics and historical data processing. By using the right storage and processing pattern for each workload, the solution enables faster commits, more reliable pipeline orchestration, improved observability, and better separation between operational and analytical concerns. Integrated with Unity Catalog, Workflows, Delta Lake/Iceberg, and AI-enabled automation, the solution provides a future-ready Databricks architecture that significantly improves performance, reliability, governance, and business agility. Read this whitepaper to learn more.

Delaware

Delaware’s (Em)powering the connected worker with Genie & Lakebase: Delaware enables operators, engineers, and plant managers to make faster, data-driven decisions by turning factory data into a conversational experience. Through integration with a broad OT partner ecosystem, supported, real-time OT data is captured and contextualized directly into the Databricks Lakehouse, creating a unified view across IT and OT systems. Lakebase acts as a persistent foundation for reliable, high-volume industrial data. With Genie, users can query performance, quality, and downtime using natural language; without relying on static dashboards or engineering support. Unity Catalog ensures secure, governed access with full lineage and auditability across all data and interactions. The result is faster root cause analysis, improved traceability, and reduced downtime, while providing a scalable foundation for MES modernization and Industry 4.0 use cases.

DXC

DXC helps enterprises adopt Databricks Lakebase to completely unify real-time transactional and analytical workloads on a single, AI‑ready data architecture. Utilizing this serverless, Postgres-compatible database engine, DXC modernizes legacy platforms and enables scalable OLTP and OLAP workloads without requiring complex, brittle ETL integration pipelines. Building on this unified foundation, DXC combines Databricks Apps, Genie, and the Agent Bricks Custom Agents to deliver intuitive, business-facing solutions, leveraging Lakebase to enable low-latency natural language data access and power advanced agentic AI workflows. For example, DXC developed a Lakebase-powered application that allows business users to instantly analyze portfolio risk under changing geopolitical conditions, seamlessly combining governed data ingestion, automated data quality loops, and conversational analytics.

Entrada

Entrada’s Governance Atlas is a workspace-portable Databricks Apps accelerator that turns Unity Catalog into a product-grade governance operating surface. It unifies search-first discovery, lineage tracing, glossary management, native writeback workflows - eliminating metadata drift through authoritative updates pushed directly back into Unity Catalog. Delivered as governance-as-code via Declarative Automation Bundles, the accelerator ensures version-controlled, reproducible, and fully auditable deployments. Genie API and Lakebase integration enables agentic querying of the business glossary and production assets with actionable insights. Powered by Databricks SQL Warehouses, it scales concurrent metadata operations across the enterprise. Read this blog to learn more.

Entrada's Serverless Cost Control Accelerator unifies diverse cost telemetry - warehouse usage, job spend, business-unit allocation, system-level signals - into a single view of Serverless consumption. This accelerator replaces fragmented reporting with reusable cost models, telemetry pipelines, dashboards, and standardized chargeback workflows. Built-in Unity Catalog governance and Lakebase federation ensure secure, auditable, real-time cost attribution. Leveraging Genie Spaces, the accelerator enables teams to query spend, usage patterns, and cost drivers in plain language, surface inefficiencies instantly, and act decisively to reduce waste. Read this blog to learn more.

EY

MET – Model Ecosystem Transformation: The Model Ecosystem Transformation focuses on making the model development lifecycle feel less fragmented and more product-like on Databricks. Teams use Genie Code and Genie Spaces to simplify how models are built, tested, and accessed, while AI/BI dashboards make outputs easier to consume for business users. Databricks Apps provides a clean way to package everything into re-usable apps rather than scattered notebooks. Behind the scenes, Lakebase helps bridge the gap between analytics and realtime applications—supporting low latency model serving, state management for agent workflows, and seamless integration with governed data. This makes it easier to move from experimentation to production and actually operationalize models at scale.

EY - AI Ready Data (AIRD): EY AIRD, built on Databricks, gives financial institutions a more practical way to get to trusted, AI ready data without heavy engineering overhead. By combining Genie and Unity Catalog with a governed data layer, users can explore, transform, and validate data using simple natural language instead of relying on technical teams. Lakebase plays a key role on the operational side—serving curated data from the Lakehouse into low latency applications and workflows. The result is a platform that connects data engineering, AI, and business usage more tightly, reduces manual effort, and helps teams move faster from raw data to decisions with confidence and proper governance built in.

Fractal Analytics

Turning Trusted Data into Real-Time Customer Experiences: Fractal’s solution helps enterprises turn governed Lakehouse data into real-time customer and operational experiences with Databricks Lakebase. By placing a fully managed, Postgres-compatible operational tier next to trusted analytical data, the solution supports fast reads, writes and transactions without adding a separate database estate. It gives teams a governed foundation for personalization, pricing, feature serving, agent memory and transaction-heavy workflows, while simplifying architecture, improving production readiness and helping applications respond faster when business moments demand it. Read this blog to learn more.

Frisco Analytics

LakeFusion MDM, implemented by Frisco Analytics, is a Databricks-native master data management platform. It resolves duplicate, conflicting records from any source into trusted golden records — Patient 360, Customer 360, Supplier MDM — without ever moving data out of the lakehouse. Lakebase makes mastered data interactive: Delta Lake holds the source of truth; Lakebase serves golden records, cross-references, and match candidates as Postgres tables with sub-5ms lookups and a three-layer cache that keeps repeat queries near-instant. Unity Catalog governs everything. The result: production-grade master data any application or business users can query in real time, running entirely inside Databricks — delivered by Frisco Analytics. Read this blog to learn more.

Frisco Analytics LakeFusion PIM, implemented by Frisco Analytics, is a Databricks-native product information management platform built for business users managing complex product catalogs across multiple upstream and downstream channels. Users manage 1- 2- 3- and 4-tier product hierarchies aligned to a taxonomy with unlimited depth — dynamically editing attributes in real time and live-editing the data model without IT involvement. Lakebase serves as the source of truth: taxonomy management, hierarchy inheritance, live data editing, and row-level access control all run natively on Lakebase. Unity Catalog governs everything end to end. Data syndication across the enterprise is simplified. Available as a Databricks Marketplace App — zero data egress, running entirely inside Databricks. Read this blog to learn more.

Frisco Analytics LakeGraph, implemented by Frisco Analytics, is a Databricks-native graph analytics platform. It turns operational data — Delta Tables, CSVs, PDFs, contracts — into a property graph and surfaces decision-grade insights: vendor risk, supplier concentration, fraud paths, network bottlenecks — without moving data out of the lakehouse. Lakebase makes the graph interactive: Delta Lake holds the source of truth; Lakebase serves the graph as Postgres tables with sub-5ms 1-hop lookups, sub-second multi-hop traversals, and a three-layer cache that keeps repeat queries near-instant. Unity Catalog governs everything. The result: production-grade graph analytics any business user can query in plain English, running entirely inside Databricks — delivered by Frisco Analytics. Read this blog to learn more.

Genpact

The AI-Powered Real-Time Personalization Engine, built on Databricks Lakebase, unifies transactional, analytical, and AI workloads on one governed platform. Lakebase handles high-velocity interactions and session data with low-latency, ACID-compliant Postgres, while native pgvector support enables real-time semantic search for RAG-powered recommendations; no separate vector database required. Synced Tables bring governed Unity Catalog data into Lakebase's serving layer, while Lakehouse Sync streams changes back into Delta tables, keeping systems aligned without custom ETL. Further delivered through Databricks Apps, this architecture removes manual data pipelines and delivers a genuinely AI-ready, low-TCO foundation for real-time personalization.

Hexaware

Vibe Analytics Agents: Vibe Analytics Agents use Lakebase to persist short-term and long-term memory. Short-term/working memory persisted in Lakebase allows various vibe analytics agents to reference recent interactions and prepare interpretable insights. Long-term semantic memory will be persisted in Lakebase such as facts, user profile, summaries to provide contextual insights and analyze past data interactions. Memory persisted in Lakebase supports rapid writes and many simultaneous reads for multiple analytics agents.

HTEC

Lakebase Branching in regulated environments: how HTEC turned constraints into advantage using Lakebase: HTEC implemented Databricks Lakebase branching integrated with Unity Catalog governance for a highly regulated risk and compliance technology provider. This breakthrough solution delivers parallel, fully isolated data branches for QA testing, eliminating environment collisions and scheduling bottlenecks without exposing sensitive customer data. It empowers operations teams to safely investigate production-level bugs within an auditable environment without ever touching live, active systems. Furthermore, the secure architecture introduces instant rollback capabilities for bad updates, ensuring robust compliance and data security. By treating regulatory constraints as core design drivers, HTEC proved that strict enterprise governance can successfully accelerate modern engineering innovation. Read this blog to learn more.

IConsulting

From KPI Sprawl to Semantic APIs - Serving enterprise metrics in milliseconds with Databricks Lakebase: A large luxury retail enterprise had accumulated thousands of KPIs across disconnected systems, making consistent definitions, reuse, and a single trusted view of performance nearly impossible. IConsulting addressed this with a unified, governed analytics architecture on Databricks. The business taxonomy and canonical KPI definitions are governed in Unity Catalog; a Lakehouse engine computes KPIs from a single source of truth; and Lakebase serves them through taxonomy-oriented PL/SQL functions exposed as low-latency Data APIs. The result is a single, channel-agnostic semantic layer delivering decision-ready metrics with millisecond response times — roughly 100× faster than previous DBSQL attempts — all within the Databricks Intelligent Platform.

iLink

iLink's DataVerse: AI-powered unified data catalog & context layer on Databricks: iLink's DataVerse is an AI-powered unified data catalog and business context platform built natively for Databricks Unity Catalog and hosted on Databricks Lakebase. It enables enterprises to establish a centralized, governed metadata foundation by integrating directly with Unity Catalog and extending it with business-friendly governance, data product management, and AI-driven contextualization. The platform helps organizations build a unified enterprise data catalog across domains, enrich technical metadata with business context and semantics, govern data products at scale, and enable AI-assisted metadata enrichment, glossary generation, stewardship, and classification improving discoverability, trust, usability, and business adoption of enterprise data assets.

Indicium AI

Pilot-to-Production AI Accelerator: Pilot-to-Production AI Accelerator closes the gap between AI experimentation and enterprise impact. Built on Databricks with Lakebase, it codifies the production patterns enterprises need most: workflow persistence and state management, runtime governance and guardrails, observability, and audit trails. Engineering teams stop rebuilding these foundations for every initiative and ship governed, reliable AI systems at portfolio speed. The outcome is measurable: time-to-production reduced from months to weeks, 3x more use cases live per engineering team, and per-use-case cost that decreases with each deployment. For enterprises with stalled AI portfolios, it provides the repeatable path from promising pilots to production systems driving P&L impact.

Infocepts

Observability Solution: Enterprise Data & AI leaders face the multi-faced challenge of managing data platform costs, performance, pipeline health, and AI sprawl. Infocepts Databricks Observability built natively with Unity Catalog, Lakeflow, AI/BI Genie, Agent Bricks, Lakebase, and Databricks Apps addresses these needs proactively. It provides a governed intelligence layer which continuously observes, understands, decides, and optimizes the Databricks platform for cost, health and performance. It serves six personas — FinOps, Platform Engineers, Data Leaders, Data Engineers, Governance teams, and AI/ML Leads — each receiving role-specific, KPI-ready, AI-powered insights on one trusted platform. Watch this demo to learn more.

Infosys

Agentic AI SRE: The SRE Agentic AI solution introduces an intelligent control layer that augments traditional monitoring by converting telemetry into context-aware, actionable decisions. Using agentic workflows, it continuously monitors platform health and enables autonomous remediation actions such as restarts, scaling, and failover. Domain-trained agents enhance incident resolution through runbook-driven insights with human-in-the-loop governance, improving reliability, compliance, and efficiency. Databricks Lakebase powers this solution as the real-time data store and “working memory,” functioning as the high-velocity operational core that closes the gap between static analysis and real-time action. This transforms static data into an active decision engine, enabling fast, adaptive, and autonomous operations for resilient, high-performance SRE ecosystems.

Koantek

Ascend AI AppBase productizes Databricks Apps and Lakebase best practices into governed operational-app delivery. A growing library of Lakebase-first starter kits runs on a shared Data-Intelligent Starter foundation, starting with customer intelligence, AI agent operations, risk and compliance, and industrial operations. Each kit serves Unity Catalog data via Synced Tables, stores transactional app state in Lakebase, and ships via app resources, valueFrom bindings, service-principal permissions, and Declarative Automation Bundles. Koantek adds the field layer that moves a kit beyond a demo: vertical schemas, grant matrices, generated bundles, QA harnesses, and proof-ready evidence. Read this blog to learn more.

Lovelytics

DocInsights: Lovelytics built DocInsight to show what's possible when AI meets the modern lakehouse. DocInsight automates the extraction of structured data from unstructured documents - contracts, drilling reports, tax filings, and more - using native Databricks capabilities including ai_parse_document and Agent Bricks. Extracted content lands directly in Lakebase, giving business teams a governed, queryable foundation for analytics from day one. Once data is structured, Databricks Genie transforms how users interact with it: instead of building queries, reviewers simply ask questions and get answers - straight from the documents themselves. The result is a full pipeline from raw PDF to business decision, built entirely on Databricks. Watch this demo and read this blog to learn more.

LTM

Alcazar is an intelligent modernization accelerator built to supercharge Databricks migration journey from legacy EDW and CDW platforms. Fully native to Databricks, Alcazar automates the heavy lifting of Data/Schema and ETL migration through its powerful core components: Analyzer, Code Migrator, Data Migrator and Data Validator. Powered by Databricks AI, it delivers smart code conversion, seamless full and incremental data migration, and blazing-fast parallel processing for large-scale datasets. With built-in aggregate and hash-level validation, your data integrity is guaranteed. Deployed as Databricks Apps with Lakebase powered configurations, Alcazar turns complex migrations into a streamlined, confidence driven experience.

Mphasis

The Mphasis Datalytyx Migration Assistant is an AI-assisted tool that modernizes complex procedural SQL—such as Oracle PL/SQL—by migrating it to the Databricks Lakehouse and Lakebase. Built on Databricks using Anthropic Claude and the SQLGlot library, it goes beyond syntax conversion to extract and explain embedded business logic, automatically generating visual flow diagrams of decision points, validation rules, and exception paths. Crucially, it recommends where each workload should run, with reasons: Lakebase suits procedural and transactional logic by preserving PL/SQL semantics, while the Lakehouse excels at analytics and orchestration. It classifies code by complexity tier and validates conversions through real execution, ensuring faster, lower-risk migrations. Read this blog to learn more.

Nagarro

DEP.AI – Agent Driven Data Engineering: DEP.AI is Nagarro’s AI-powered data engineering accelerator built on Databricks Lakehouse architecture to accelerate enterprise data modernization and AI adoption. The platform provides a custom UI for creating Spark-based data pipelines with pipeline execution running on Databricks clusters, while leveraging Unity Catalog for centralized governance and Lakebase Postgres for managing operational metadata, AI iteration logs, workflow states, and job tracking. Integrated with GenAI capabilities, conversational interfaces, and Databricks Unity AI Gateway for agentic tasks, DEP.AI enables automated migration, ingestion, AI-assisted ETL development, schema evolution handling, data quality monitoring, and self-healing pipelines. Designed for multi-cloud environments, the accelerator helps organizations reduce engineering effort, improve observability, and rapidly build governed, AI-ready data products at scale.

Perficient

The Easy Ingestion Accelerator is a Databricks-based, production-ready framework that simplifies and automates end-to-end data ingestion across diverse sources and formats, including CSV, JSON, Excel, and Parquet. Backed by Lakebase configuration management, it centralizes ingestion settings and governance while providing a target that supports Databricks Delta tables as well as Lakebase through the EasyETL Lakebase target sink. Built with reusable utilities for file validation, ingestion, auditing, and delivery, it reduces development complexity and accelerates onboarding of new data sources by up to 60%. The accelerator delivers observability, audit trails, and reliable data delivery to Delta Lake, Lakebase, and lakehouse environments at enterprise scale today.

Persistent Systems

iAURA Cost of Intelligence: iAURA Cost of Intelligence is a Lakebase-powered accelerator that captures real-time token-level telemetry across users, applications, prompts, sessions, and models, providing a live view of GenAI consumption. It integrates this with Lakehouse-based historical analytics to enable trend analysis, anomaly detection, and forecasting of token usage and cost patterns. By embedding token economics into delivery workflows, it enables continuous optimization, governance, and data-driven control of GenAI consumption, resulting in better cost visibility, early detection of inefficiencies, and predictable AI usage at scale. Read this blog to learn more.

Qubika

Lakebase Performance Intelligence Agent Accelerator: Lakebase ships as Databricks' managed Postgres OLTP engine, but its operational signals—connections, CPU, cache hit rate, replication lag—live scattered across system tables with nothing to correlate them. Qubika's Lakebase Performance Intelligence Agent closes that gap with six specialized AI agents on the Agent Bricks Agent Framework, a coordinating orchestrator, and compound correlation logic that classifies slow queries as downstream symptoms rather than root causes. A Unity Catalog–governed persistent layer means the system learns from every incident. Because the failure modes are universal—connection saturation, memory pressure, replication lag—any organization running Lakebase in production benefits, regardless of industry. Reactive firefighting becomes proactive operational intelligence. Read this blog to learn more.

Reply

Intelligent Document Processing Accelerator on Databricks Lakebase: Building operational AI apps requires sub-second transactional query performance, not just batch analytics. Databricks Lakebase addresses this by embedding a PostgreSQL-compatible engine directly in the lakehouse. Combined with a Unity Catalog Volume for unstructured document storage and Databricks Jobs for orchestration, it serves as a real-time operational database. This unified architecture eliminates cross-system data synchronization, sustains consistent performance under concurrent load through row-level locking, and scales from 10K to 100K+ documents annually — all without architectural rewrites and with full PostgreSQL ecosystem compatibility. Read this blog to learn more.

Sigmoid

Sigmoid LatticeIQ, powered by Databricks Lakebase, serves as a unified, low-latency serving layer that integrates transactional and analytical data under a single Unity Catalog governance plane, completely eliminating the need for separate database infrastructure. Sigmoid is currently deploying this solution across major global enterprises , partnering with a Fortune 500 Health & Hygiene company to deliver a robust Consumer Data Platform that has already secured a 3x marketing ROI and a 30% increase in data coverage. For a Fortune 500 Beverages company, LatticeIQ drives marketing budget optimization by enabling risk-free econometric model testing through instant copy-on-write database branching. Additionally, the architecture allows a leading Consumer Goods enterprise to achieve sub-10ms UI query latency paired with automated, scale-to-zero cost efficiencies to power an intelligent, agentic S&OP forecasting system.

Slalom

LakeSpeak: One of Slalom’s public sector customers is modernizing emergency response by using AI-powered tools like LakeSpeak, Slalom’s MCP powered Brickbuilder accelerator, to create dynamic, real-time Situation Reports. This enhances decision-making, reduces manual reporting, and offers an AI assistant for targeted data queries during disasters. LakeSpeak delivers a secure, standardized gateway to expose Databricks Genie and Lakebase to external apps, agents, and enterprise users - without duplicating logic, breaking governance, or rewriting integration patterns. Read this blog to learn more.

SoftServe

Lakebase Ingestion Architecture: SoftServe accelerates enterprise adoption of Databricks' Lakebase and Zerobus by delivering a production-ready reference architecture that unifies real-time ingest, operational serving, and agentic workflows on the Lakehouse. This eliminates the need for secondary databases, Kafka clusters, and reverse-ETL pipelin