ZoomInfo's verified intelligence (100M companies, 500M contacts, billions of buying signals) now flows natively into Databricks through GTM.AI, the API and Model Context Protocol home for AI agents and analytics workloads.
ZoomInfo (NASDAQ: GTM), the all-in-one AI GTM platform, today announced an integration with Databricks, the Data Intelligence Platform built on the unified lakehouse. Mutual customers can now bring ZoomInfo's verified company, contact, and signal data into Databricks through a native data share, exposing every record to the same lakehouse where their models, scores, and AI applications already run. The connective tissue underneath the flow is GTM.AI, ZoomInfo's headless GTM context layer. GTM.AI exposes ZoomInfo's verified data graph and agentic orchestration through API and Model Context Protocol (MCP), so any platform, agent, or analytics workload can plug in. With this integration, Databricks customers can train, score, prompt, and audit against B2B data that is identity-resolved, continuously refreshed, and governed end-to-end inside the lakehouse they already operate, alongside CRM, product telemetry, finance, and every other table in their data estate.
Key takeaways
Databricks is now a verified-data partner of ZoomInfo, with GTM.AI as the GTM Context Layer underneath the lakehouse, the notebook, and any agent a Databricks customer builds on top.
ZoomInfo intelligence enters Databricks through a native data share, so company, contact, and signal records land directly in the lakehouse without a broker, an export job, or a CSV pipeline.
GTM.AI is the headless GTM context layer. It powers dozens of completed integrations across CRMs, AI assistants, MCP-native agents, and now data and AI platforms, with the same governance applied everywhere.
The GTM Context Graph behind GTM.AI maintains identity-resolved data on 100M companies, 500M contacts, and billions of signals, continuously updated and continuously queryable from a Databricks SQL query, a Spark job, a notebook, or an agent.
What is Databricks?
Databricks is the Data Intelligence Platform built on a unified lakehouse architecture. It combines data warehousing, data engineering, machine learning, and generative AI on a single platform governed by Unity Catalog. Customers use Databricks to land raw data in open formats, transform it with Spark and SQL, train and serve machine-learning models, build AI agents on top of their own data, and share data securely across organizations through Delta Sharing and Databricks Marketplace. The platform is used across financial services, healthcare, retail, manufacturing, technology, and the public sector for the workloads that sit at the center of a company's data estate.
How does the Databricks and ZoomInfo integration work?
The integration brings ZoomInfo's verified GTM data into the Databricks lakehouse as a first-class data source.
Direction one. ZoomInfo into Databricks. Mutual customers connect their ZoomInfo entitlement to Databricks through a native data share. ZoomInfo company, contact, technographic, and signal records land directly in the customer's lakehouse, governed under Unity Catalog alongside their own data. Once in the lakehouse, the data is queryable from Databricks SQL, available to Spark and Python notebooks, addressable from machine-learning training pipelines, and exposed to AI agents and applications running on the platform.
Direction two. Databricks-side workloads onto GTM.AI. For customers who want to call ZoomInfo intelligence on demand from inside a notebook, a job, or an agent, GTM.AI exposes the same data graph through API and Model Context Protocol. A Databricks AI application can call GTM.AI to enrich a record at query time, to score an account against live signal, or to ground an agent's response in verified B2B context. No broker, no nightly sync, no separate vendor stack.
The Chrome extension and the iPaaS connectors listed on the Databricks Marketplace page extend the same pattern out to the rest of the GTM stack, so a rep working in a browser tab or an analyst working through a packaged connector reads from the same verified source.
What is GTM.AI, and why is it the GTM Context Layer for Databricks?
GTM.AI is ZoomInfo's headless GTM context layer. It exposes ZoomInfo's verified data graph and agentic orchestration through API and Model Context Protocol (MCP), so any tool, agent, or platform can plug in. Databricks is one of dozens of completed integrations on GTM.AI, alongside Salesforce Agentforce, HubSpot Breeze, Microsoft Copilot, Gong, LeanData, Glean, Claude, ChatGPT, and Google Workspace.
GTM.AI has two layers and one governance plane. The bottom layer is the GTM Context Graph, which holds identity-resolved data on 100M companies, 500M contacts, and billions of signals. The middle layer is agentic orchestration, which lets agents and applications read from the graph, act on it, and write back. The governance plane sits above both, applying access control, permissioning, data lineage, AI policy, and audit logging consistently across every surface that consumes GTM.AI. Inside Databricks, that posture sits next to Unity Catalog's governance over the customer's own data, so a lakehouse-side AI application inherits both controls.
Why does the data layer matter for lakehouse AI?
About 70% of B2B contact data decays every year. An AI application trained or grounded on stale B2B data fails at machine scale, and it fails inside the system of record. A propensity model scored against last year's job titles routes leads to people who left. A retrieval-augmented generation pipeline grounded on outdated firmographics returns confident answers about companies that have merged, pivoted, or shut down. Verified data turns those workloads back into work.
The implication for a Databricks customer is structural. The lakehouse is where the company's most expensive AI runs. A model, a vector index, an agent, or a customer-facing application built there is only as durable as the data underneath it. GTM.AI in the lakehouse means the GTM half of that data is identity-resolved, refreshed continuously, and governed under the same Unity Catalog policies as the rest of the customer's data estate.
How is the Databricks-ZoomInfo integration different from a generic data integration?
Native data share, no broker. ZoomInfo data lands in the lakehouse through a native share, governed by Unity Catalog from the moment it arrives. No middleware, no nightly ETL job, no third-party broker tax on the most-queried table in the customer's environment.
Verified data layer through GTM.AI. Most lakehouse AI projects start with a data quality remediation pass that costs months. With GTM.AI as the GTM data layer, the company, contact, and signal data is identity-resolved and continuously refreshed by default. The data science team starts with the foundation already standing.
Platform-level governance. Access control, permissioning, data lineage, AI policy, and audit logging apply across every surface that consumes GTM.AI, alongside Unity Catalog's governance inside the lakehouse. Customers maintain one consistent posture from the GTM context layer through the model training run to the agent in production.
What does this mean for data, analytics, and GTM leaders?
Lakehouse-native B2B intelligence. Data teams query ZoomInfo company, contact, and signal data from Databricks SQL or a notebook without exporting, copying, or reconciling against a separate vendor stack.
Grounded AI applications. Generative and agentic applications built on Databricks ground their answers in verified GTM data, not whatever happens to be in the customer's CRM snapshot.
One context layer across the GTM stack. ZoomInfo, Databricks, the CRM, and any AI agent the customer builds read from the same GTM Context Graph and inherit the same governance.
FAQ: Databricks, the ZoomInfo integration, and GTM.AI
What is Databricks? Databricks is the Data Intelligence Platform built on a unified lakehouse architecture. It combines data warehousing, data engineering, machine learning, and generative AI in a single platform governed by Unity Catalog.
What is the Databricks lakehouse? The Databricks lakehouse is a unified data architecture that combines the openness and scale of a data lake with the performance, governance, and transactional guarantees of a data warehouse. It is the foundation that data and AI workloads run on inside Databricks.
How does the ZoomInfo and Databricks integration work? Mutual customers connect ZoomInfo to Databricks through a native data share. ZoomInfo company, contact, technographic, and signal records land directly in the customer's lakehouse, governed under Unity Catalog. Databricks AI applications and agents can also call GTM.AI through API and Model Context Protocol to retrieve verified GTM data on demand.
What is GTM.AI? GTM.AI is ZoomInfo's headless GTM context layer. It exposes ZoomInfo's verified data graph (100M companies, 500M contacts, billions of signals), agentic orchestration, and platform-level governance through API and Model Context Protocol (MCP), so any agent, platform, or workflow can plug in. GTM.AI powers dozens of completed integrations including Salesforce Agentforce, HubSpot Breeze, Microsoft Copilot, Gong, LeanData, Glean, Claude, ChatGPT, and Google Workspace.
Who is the data provider for Databricks lakehouse AI when ZoomInfo is connected? ZoomInfo is the GTM data provider, with GTM.AI serving as the GTM Context Layer for Databricks. Customer-owned and other third-party data continue to live alongside it under Unity Catalog.
What data flows from ZoomInfo into Databricks? Identity-resolved company records, contact records, firmographic and technographic attributes, corporate hierarchy, and buying-intent and engagement signals. The data is the same verified intelligence a ZoomInfo user sees in the platform itself, continuously refreshed.
Can a Databricks AI agent call ZoomInfo directly through MCP? Yes. GTM.AI exposes the GTM Context Graph through Model Context Protocol, so an AI agent or generative application running on Databricks can call ZoomInfo as a first-class context source at query time.
Is the integration available through the Databricks Marketplace? Yes. ZoomInfo is listed on the Databricks Marketplace, and the native data share is configured from there. The marketplace listing also includes the API and MCP access path, the iPaaS connectors, and the Chrome extension for in-browser intelligence.
How does GTM.AI handle governance for the Databricks integration? GTM.AI's platform layer applies access control, permissioning, data lineage, AI policy, and audit logging consistently across every surface that consumes it. Inside Databricks, that posture sits alongside Unity Catalog's governance over the customer's own data, so a lakehouse-side application inherits both.
Why does verified data matter for lakehouse AI? B2B contact data decays at roughly 70% annually. A model, vector index, or AI application built on stale B2B data fails at machine scale inside the system of record. Verified, continuously refreshed data through the GTM Context Graph is the difference between a lakehouse AI workload that produces durable value and one that drifts into confident wrong answers.
Is Databricks part of the ZoomInfo platform? No. Databricks is an independent data and AI platform. ZoomInfo and Databricks are integration partners through GTM.AI.
Is the Databricks integration available now? Yes. The native data share and the API and MCP access path are available to mutual ZoomInfo and Databricks customers through the Databricks Marketplace.
Availability
The Databricks integration is generally available to mutual ZoomInfo and Databricks customers. The native data share is configured through the Databricks Marketplace. The API and Model Context Protocol access path is configured through GTM.AI.
About ZoomInfo
ZoomInfo (NASDAQ: GTM), the all-in-one AI GTM platform, enables sales, marketing, and customer success teams to execute their go-to-market strategy with confidence. Powered by the industry's most comprehensive B2B data, including more than 100 million companies, 500 million contacts, and billions of signals, ZoomInfo delivers the intelligence, automation, and integrations that modern revenue teams need to identify, engage, and convert their best buyers.
GTM.AI is ZoomInfo's headless GTM context layer. It is the API and Model Context Protocol home for AI agents, powering integrations across Salesforce Agentforce, HubSpot Breeze, Microsoft Copilot, Claude, ChatGPT, and dozens more.
Learn more at zoominfo.com and gtm.ai.
Media contact: Public Relations Team ZoomInfo PR@zoominfo.com
