ZoomInfo and Databricks link GTM.AI to the lakehouse

ZoomInfo has integrated its GTM.AI context layer with Databricks, letting mutual customers pipe verified company, contact and signal data directly into the lakehouse. The move is meant to give AI models and agents fresher, identity-resolved B2B data under existing governance controls.

Why it matters: - Databricks customers can now run AI workloads on verified B2B data without moving to a separate vendor stack. - ZoomInfo says the setup can improve model accuracy, scoring and agent responses by reducing the risk of stale contact and firmographic data. - The integration puts GTM data under the same governance and audit controls already used in the lakehouse.

What happened: - ZoomInfo confirmed an integration with Databricks, its native data share and AI platform. - Mutual customers can connect ZoomInfo entitlements to Databricks through Databricks Marketplace. - Verified company, contact, technographic and signal records now flow into the customer’s lakehouse through GTM.AI. - The integration is generally available to mutual ZoomInfo and Databricks customers.

The details: - GTM.AI serves as ZoomInfo’s headless GTM context layer. - GTM.AI exposes ZoomInfo’s verified data graph and agentic orchestration through API and Model Context Protocol. - Databricks users can query the data in Databricks SQL, use it in Spark and Python notebooks, feed it into machine-learning training pipelines, and expose it to AI agents and applications. - The data lands under Unity Catalog, alongside a customer’s own data. - ZoomInfo says there is no nightly export job and no separate vendor stack. - Databricks applications can also call GTM.AI on demand to enrich records, score accounts against live signals or ground agent responses in verified B2B context. - ZoomInfo’s Chrome extension and iPaaS connectors extend the same data source across the rest of the GTM stack. - The same verified source can serve a rep working in a browser tab and an analyst working through a packaged connector.

Between the lines: - The pitch is not just about data access. It is about keeping AI systems connected to a continuously refreshed identity layer instead of stale exports. - ZoomInfo is framing B2B context as infrastructure for enterprise AI, not only as a sales and marketing tool. - The Databricks tie-in also reinforces GTM.AI as a distribution layer for ZoomInfo across multiple enterprise platforms. - ZoomInfo says the GTM Context Graph behind GTM.AI includes identity-resolved data on 100 million companies, 500 million contacts and billions of signals. - The same governance plane applies access control, permissioning, data lineage, AI policy and audit logging across GTM.AI surfaces. - Inside Databricks, those controls sit alongside Unity Catalog. - ZoomInfo says roughly 70% of B2B contact data decays every year, which makes freshness a central part of the product case. - Databricks is one of dozens of completed GTM.AI integrations, alongside Salesforce Agentforce, HubSpot Breeze, Microsoft Copilot, Gong, LeanData, Glean, Claude, ChatGPT and Google Workspace.

What's next: - Mutual customers can start using the native data share through Databricks Marketplace now. - Customers that want on-demand access can configure API and Model Context Protocol access through GTM.AI. - ZoomInfo is likely to keep positioning GTM.AI as the connective layer for more AI apps, agents and analytics workflows.

The bottom line: - ZoomInfo is trying to make verified B2B context a built-in layer of the Databricks lakehouse, so AI systems can work from fresher data with fewer manual handoffs.