Jedify Launches Data Agents for Autonomous AI Analysis
The new platform allows users to build AI-powered analysts that automate recurring data tasks using plain language.
Updated on Oct. 28, 2026 in Artificial Intelligence
Live Poll
Would you trust an AI agent to perform complex analytical tasks for your business?
Jedify has officially launched Data Agents, a tool designed to shift analytics from manual question-answering to automated task execution. The product enables users to create AI analysts that operate on defined metrics and existing user permissions.
Why it matters
The platform aims to replace recurring manual dashboard requests currently handled by human analysts with autonomous, AI-driven workflows. By utilizing context graphs and the Model Context Protocol, the tool integrates directly into existing professional platforms like Slack and ChatGPT.
Data Agents operates on a custom context graph that integrates record-level permissions and metric definitions. The system supports the Model Context Protocol, ensuring compatibility with AI platforms including Claude, ChatGPT, and Slack.
The players
Jedify
Jedify is a venture-backed technology company focused on building autonomous analytical tools for professional business environments.
RubyPlay Ltd.
RubyPlay Ltd. is an early adopter of the Data Agents platform, currently leveraging the software to automate its internal daily reporting processes.
The details
Users configure these agents by describing desired tasks in plain language, with capabilities to trigger actions on a set schedule or when specific data conditions are met. RubyPlay Ltd. is currently utilizing the technology to generate automated daily reports.
Timeline
Jedify raised a $24 million Series A round in June 2026.
The Data Agents product was officially launched on October 28, 2026.
The Tech Race
The deployment of Data Agents marks a transition from simple chatbot interfaces to autonomous agents that act on enterprise data. By integrating the Model Context Protocol, Jedify positions its tools to compete directly within the evolving ecosystem of AI-integrated professional software.
Professional users can expect a reduction in the time spent manually preparing or updating recurring dashboard reports for teams. The reliance on existing permissions means that users will only access data they are already authorized to view, maintaining standard security protocols.
The takeaway
Automating routine analytics allows teams to focus on higher-level decision-making rather than data retrieval. Organizations should audit their internal metric definitions before deploying agents to ensure the AI operates on accurate and consistent data sets.
Further reading
Explore the latest developments in autonomous software tools in our Artificial Intelligence section.
Live Poll
Would you trust an AI agent to perform complex analytical tasks for your business?
