Fivetran, the data foundation for AI, announced the completion of its merger with dbt Labs, the creator of dbt and the leader in standards for AI-ready structured data. Initially operating as Fivetran + dbt Labs, the all-stock transaction, originally announced on October 13, 2025, brings together two category-defining platforms to advance a new era of trusted, Open Data Infrastructure for AI at scale. George Fraser will continue serving as CEO, and Tristan Handy will serve as President.

Fivetran + dbt Labs are building the data foundation for the agentic AI era. Together, these companies deliver the data infrastructure layer that makes agents trustworthy.

Together, Fivetran + dbt Labs support a global community of more than 100,000 data teams across analytics, data engineering, and AI initiatives, including some of the world’s most recognized brands such as OpenAI, Zendesk, Coupa, and HubSpot, as well as leading enterprises across financial services, retail, manufacturing, and healthcare.

A new foundation for agentic AI

AI agents are quickly becoming the primary consumers of enterprise data, and they behave differently from the human analysts that today’s data stack was built to serve. Agents operate continuously, in parallel, and at machine speed. And many organizations want to move into a world where most agents are autonomous — no human in the loop. This shift raises the bar for the data they run on, requiring it to be reliable, fresh, governed, and accessible across every system in the enterprise.

Fivetran + dbt Labs are building the data foundation for the agentic AI era. Together, these companies deliver the data infrastructure layer that makes agents trustworthy, from data movement and transformation to the governed context needed for reasoning and action. Fivetran ensures agents operate on complete, continuously synced, and reliable data. dbt ensures that data is defined, tested, and trusted through governed business logic, shared semantic context, and software engineering best practices embedded throughout the data lifecycle. Built on open standards, this foundation works across any cloud, engine, and tool, giving organizations the freedom to evolve their architecture without lock-in while maintaining portable business logic, cost efficiency, and control.

“The next generation of enterprise AI will be defined by the quality and trustworthiness of the underlying data,” said George Fraser, CEO and Co-Founder of Fivetran + dbt Labs. “Together, Fivetran and dbt Labs are creating the infrastructure layer that helps organizations deliver governed, high-quality, and semantically rich data to power trusted AI agents at scale.”

“The companies that deploy AI successfully over the next decade will be the ones whose agents can be trusted to act,” said Tristan Handy, President and Co-Founder of Fivetran + dbt Labs. “Trust is built at the infrastructure layer, on high-quality tooling and on open standards. That’s the bet we’re making together.”

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Joint product innovations

The merger also marks the first major milestone in a shared innovation roadmap, with the first combined innovations from Fivetran + dbt Labs debuting today. The announcements span agentic development workflows, intelligent orchestration, and continued investment in open source innovation, including extending powerful dbt capabilities to the dbt Core open source user base.

Key innovations announced today include:

• dbt Core v2.0 (alpha): The open sourcing of the dbt Fusion engine runtime, released as dbt Core v2.0 under an Apache 2.0 license, giving every practitioner the dbt experience they know on a faster, more capable foundation. Additionally, the locally installable distribution of dbt gives developers free access to the full breadth of Fusion’s capabilities — core language features and warehouse adapters — with the ability to seamlessly unlock additional platform features by logging in directly from the terminal.
• dbt State (preview): dbt State acts as a caching layer for data pipelines. It only builds what’s changed and skips what hasn’t, helping companies reduce underlying infrastructure costs by 30% or more.
• dbt Wizard (beta): dbt Wizard brings autonomous assistance for model authoring, refactoring, and debugging, grounded in full dbt project context, including lineage, tests, contracts, and defined metrics. The result is governed recommendations and trusted SQL generation that reflect how enterprise data is actually structured and defined.
• Agents Schema: An open source standard for agentic context that designates a single schema in the warehouse or lake as the shared context layer for AI agents. Metric definitions, semantic models, dbt lineage, and business documentation are stored in plain SQL tables and can be published from existing systems through tools such as GitHub Actions, metadata connectors, or custom integrations. Compatible with any warehouse, lake, ingestion tool, or SQL-capable agent, Agents Schema gives organizations a customer-owned context layer that works within existing security and governance policies, improves token efficiency through richer context, and eliminates the need for new infrastructure or vendor-locked agent systems.

Customers building with Fivetran + dbt Labs

“With Fivetran and dbt, what used to take months now happens in weeks,” said Akshay Agrawal, Director of Data Engineering at Zendesk. “It gives the business faster access to trusted data and creates the foundation we need to scale analytics, agents, and AI across the enterprise.”

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“Our focus now is on how we operationalize AI across Inova. With Fivetran and dbt, we’re creating the foundation for AI agents and applications that can act on trusted, governed data — not just generate insights, but drive action,” said Jon McManus, Chief Data and AI Officer, Inova Health.

“The combination of Fivetran and dbt isn’t just about efficiency today,” said Lakshmi Ramesh, VP of Data Services at Tinuiti. “It’s about being ready for what’s next. Analytics, AI, and agentic workflows all run on trusted data, and together, Fivetran and dbt are the data infrastructure that makes it all possible.”

“By building an AI-ready data foundation with Fivetran and dbt, we’re improving how teams across Shutterstock access and operationalize trusted, real-time data for analytics and emerging AI-driven workflows,” said Jitesh Kumar, Senior Software Development Manager at Shutterstock.

“AI and agents are only as strong as the data behind them,” said Piyush Bhargava, Sr. Director, Data Architecture and Engineering at DocuSign. “By investing in Fivetran and dbt, we’ve built the reusable, trusted data assets that are central to how we scale AI and drive innovation.”

The combined innovations are now available and will be showcased throughout Snowflake Summit 2026. Summit attendees can visit the Fivetran booth (booth #2313) or the dbt Labs booth (booth #2112) to connect with product experts, experience demonstrations of the combined innovations, and explore customer use cases powering trusted AI agents at scale.