Prophecy Launches DataGPT for Enterprise Analytics
The new platform integrates data workflows into generative AI tools like ChatGPT and Microsoft Copilot.
Updated on Oct. 28, 2026 in Artificial Intelligence
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Prophecy has launched DataGPT, a platform designed to let business analysts perform complex data workflows directly within existing AI assistants like ChatGPT, Claude, and Microsoft Copilot. The tool generates visual workflows that allow users to inspect and verify data processes before exporting them as repeatable code.
Why it matters
The platform addresses the need for enterprise data work to be more verifiable, governed, and reusable. By creating a bridge between business context and data systems, it aims to standardize data operations across large organizations.
DataGPT supports integration with major data platforms including Snowflake, Databricks, and BigQuery. The software utilizes a knowledge graph to connect user prompts with data workflows, facilitating the creation of repeatable code for existing enterprise systems.
The players
Prophecy
A company headquartered in Palo Alto, California, that develops software for data engineering and analytics.
Gartner
A global research and advisory firm that provides insights and predictions regarding information technology and enterprise trends.
The details
The platform enables users to onboard, prepare, and analyze files through natural language prompts. Once a workflow is generated and verified, it can be exported to support production-grade data operations.
Timeline
Prophecy was founded in 2017.
The DataGPT platform officially launched on October 28, 2026.
Gartner projects that 50% of organizations will adopt zero-trust data governance by 2028.
The Tech Race
DataGPT reflects the industry-wide shift toward integrating enterprise-grade data governance into consumer-facing generative AI interfaces. It aims to replace manual, siloed data processes with automated workflows that align with the trajectory of zero-trust data security models.
Business analysts can now accelerate their data preparation tasks by using familiar chat interfaces to generate verifiable code. This reduces the technical barrier to building complex data pipelines while ensuring that the resulting workflows are compliant with enterprise standards.
The takeaway
As generative AI becomes more central to business operations, tools that prioritize verifiability and governance are becoming essential. Analysts should focus on verifying the workflows produced by AI to ensure data accuracy and security.
Further reading
Learn more about the evolving landscape of Artificial Intelligence.
More information
For additional technical specifications, visit the Prophecy product information portal.
Source note: This article includes information reported by The Manila times.
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