Airbyte launches agents to unify data for AI workflows

Airbyte has launched Airbyte Agents, a product designed to give AI agents a unified view of company data.

The new offering aims to solve a common production problem: AI agents often fail because they rely on fragmented, inconsistent data spread across multiple business systems.

Known for data movement software, Airbyte is using the launch to expand further into tools for AI agents. Its approach centres on a Context Store, which brings together data from business applications into a replicated, searchable index before an agent runs.

That allows an agent to query a prepared data layer instead of pulling information from several live application programming interfaces when a user asks a question. Airbyte says this reduces the number of system calls needed to answer a request and lowers the risk of stale or conflicting responses.

The launch reflects a broader shift in the AI software market, where suppliers are focusing less on large language models themselves and more on the data and system design needed to make those models useful in business settings. Airbyte argues that many problems blamed on models are actually caused by poor access to reliable data.

Context store

The Context Store is designed to combine records and activity from systems such as Salesforce, Zendesk, Jira and Slack into a single index while preserving history and state. It launches with 50 connectors covering systems Airbyte views as central to business operations.

The wider catalogue of more than 600 connectors will be added to the Context Store over time. Some support write actions, allowing agents not only to read data but also to update records, create tickets and post messages in source systems.

Access options

Access is available in two forms: through the Model Context Protocol, or MCP, for use in clients including Claude, ChatGPT and Cursor, and through a software development kit for companies building their own agents and applications.

All connectors use OAuth-based authentication and row-level permissions so agents can access only the information available to the invoking user. That control is likely to matter for businesses deciding whether to let AI agents interact with operational systems and sensitive internal records.

Nate Chambers, Chief Product Officer, ORCA Analytics, described the beta programme's impact on his company's product plans.

"Airbyte Agents has massively accelerated our roadmap. What we thought would take 6-plus months, we were testing in the first week of the beta program," said Nate Chambers, Chief Product Officer, ORCA Analytics.

"They're shipping everything we need for agentic workflows, and launching new data connections faster than we can build them into our product. If you're building an AI product, you can stop rolling your own data pipelines and start shipping," Chambers said.

Michel Tricot, Co-founder and Chief Executive Officer, Airbyte, said the company sees data quality and consistency as the main constraint on agent deployments.

"Most agent projects stall for the same reason: The model is fine, the data is a mess. Five disconnected systems, inconsistent entities, no shared state," said Michel Tricot, Co-founder and Chief Executive Officer, Airbyte.

"Airbyte Agents gives every agent a unified view of the business, replicated and ready to query. That is what separates an agent that can do the work from one that just talks about it," added Tricot.

Customer use

Drivepoint, which develops a finance platform for eCommerce and omnichannel consumer brands, said the software reduces the need to build custom integrations for each new data source.

"Without Airbyte, we'd be stitching together bespoke data connectors for every integration, which would slow us down dramatically," said Franziska Ibscher, Head of Product, Drivepoint.

"With Airbyte, our AI features have fresh, reliable data to work with. Whether we're running automated financial models or powering AI agents that answer questions about a brand's business, none of it works without trustworthy data flowing in, and that's what Airbyte gives us," Ibscher said.

Alongside Airbyte Agents, Airbyte is also making available a research preview of Automations, a visual interface for building and running agents inside Airbyte. Built on the same Context Store, it is aimed at teams that want to assemble agent workflows without code.

For existing customers, Airbyte is offering three months of access to Airbyte Agents with usage limits. Consumption is measured in Agent Operations, which cover reads, searches, actions and reasoning calls against the Context Store.

Airbyte says its technology is already used by 7,000 enterprises to move structured and unstructured data across cloud and hybrid environments.