Prophecy launches DataGPT, bringing enterprise data workflows to Claude, ChatGPT, and Copilot. DataGPT turns AI conversations into visual data workflows business teams can verify, and into reusable and governed data products that run on the cloud data platforms enterprises already own. October 28, 2026 05:00 ET | Source: Prophecy PALO ALTO, Calif., Oct. 28, 2026 (GLOBE NEWSWIRE) - Prophecy, the AI platform for business data work, today announced Prophecy DataGPT. DataGPT lets business data analysts do complete data work, from onboarding messy files to publishing finished reports, inside ChatGPT, Claude and Microsoft Copilot. Every result comes with a visual data workflow that can be inspected and validated, and approved work ships as repeatable code on the data platform the organization already owns. Highlights * Accelerate data work: Now, without leaving ChatGPT, Claude or Microsoft Copilot, analysts describe the outcome they need, and DataGPT builds the whole workflow right in the conversation: onboard, prepare, analyze and output. * Visually verify: Every answer brings in the visual workflow behind it, so business data teams can inspect and approve each step. * Compound knowledge: Prophecy uses a knowledge graph to connect business context with data workflows, helping teams apply relevant definitions and business rules across their data work. * Operationalize outcomes: Approved workflows ship as data products, and run as governed, repeatable code on Snowflake, Databricks or BigQuery, on a schedule. When business data analysts upload spreadsheets into AI apps like ChatGPT or Claude to reconcile a quarter of transactions, the AI writes and runs a script behind the scenes to produce the result. Because they cannot read that code, they cannot validate it, refine it, or stand behind it. Once the chat session ends, the workflow vanishes with it. The path that carried messy inputs to a finished output disappears, and so does the domain knowledge the user supplied along the way, such as their business rules, revenue definitions, and approved exceptions. That gap is growing as AI-generated data spreads. Gartner predicts that by 2028, "50% of organizations will adopt a zero-trust data governance as unverified AI-generated data grows." "Enterprise AI is moving from answering questions to doing repeatable work. Generating an answer has gotten simpler. The challenge now is making the underlying data verifiable, governed, and reusable. Companies that can close the gap between business intent and execution will improve decision velocity," validates Michael Ni, VP & Principal Analyst at Constellation Research. "Coders got AI that changed the way they work, collaborating with them on code all the way from development to production, unlocking tremendous productivity. Business data analysts got question answering, and nothing else changed," said Raj Bains, founder and CEO of Prophecy. "We are closing that gap. Business analysts now get what coders got - the visual workflow behind every result, in a form they can verify and change, built on governed knowledge. The work worth keeping moves to production on their data platform." AI that does the data work, not just answers questions AI assistants can answer questions about data that's already prepared. Enterprise data teams rarely start there. Their real work is getting the data ready: onboarding files, reconciling systems that disagree, matching records with no common key, and cleaning and transforming everything. Then they have to deliver reports, dashboards and filings in exact formats, where every number must be correct and verified. DataGPT is designed for finance, operations and line-of-business analysts who work in spreadsheets and desktop tools. In a single conversation, an analyst can upload a messy Excel file, check it against an audit list and data in SharePoint, Snowflake and Databricks, apply a pricing rule for discounted product bundles, review the results and schedule the workflow to rerun every month. DataGPT connects to files, SharePoint, data warehouses, ERP and CRM systems, and every workflow is backed by open code in Git, so the logic stays transparent and auditable. Data teams review instead of rebuild With DataGPT, business analysts no longer build every workflow from scratch. AI builds it, and they verify it visually instead, reviewing each step and its results on screen, making small refinements where needed and approving the final version. Approved workflows then rerun exactly the same way every time, with no new AI generation and no added AI cost. Bringing shadow AI under governance Many business analysts already paste company spreadsheets into AI chat tools without IT's knowledge or approval, one of the most common forms of shadow AI. With DataGPT, uploaded files go through Prophecy to the organization's own data platform, not into an AI chat. Data platform leaders and IT can see every workflow and govern it on the platform they already own, without adding another silo. Availability Prophecy DataGPT is available today. Bring Prophecy into ChatGPT, Claude, and Microsoft Copilot, or use DataGPT in the Prophecy app. Organizations can get started with a free account, with centralized deployment options for administrators. About Prophecy Prophecy is the AI platform for business data work. Business data analysts use plain language to prepare, analyze, and report on enterprise data, with every task backed by a visually inspectable workflow and open, editable code that runs on Snowflake, Databricks, or BigQuery. Founded in 2017 and headquartered in Palo Alto, California, Prophecy has more than 130 employees across the U.S., India, the U.K., and Australia and has raised more than $100 million. Leading enterprises, including SAP, HSBC, JP Morgan Chase, and Pfizer, rely on Prophecy for governed data work. Media contact

Prophecy launches AI data prep tools and expands agents to Snowflake. Prophecy has introduced new AI-powered data preparation products that give business users and data analysts greater visibility into work performed by AI agents. The capabilities allow users to review and validate agent-generated workflows before relying on their outputs for business decisions. Prophecy also expanded its AI agents to Snowflake, adding to its existing support for Databricks. Prophecy built the release around a growing problem for data platform leaders. As budget has gone toward AI model costs and scaling AI agents, pilots continue to stall before reaching production. Often this is not because of the model, but because the underlying data is prepared by hand in desktop tools by whoever happens to own the spreadsheet, or because companies rely on a few dedicated technical resources that cannot keep up with data preparation requests. Explore AI Tools "Companies have poured, and continue to pour, massive chunks of their budget into models and agents, yet pilots still aren't turning into value for business users," said Raj Bains, CEO, Prophecy. "Few are budgeting for AI data prep, and that's exactly what's led to AI projects not meeting anticipated goals or delivering the expected ROI." Prophecy's AI data prep tools give business users a way to quickly understand and verify what an AI agent changed in a data workflow or chart before trusting the output. Instead of reviewing pages of generated SQL or Spark code (or involving the data engineering team), business users can see changes laid out visually alongside the data produced. Prophecy's interface has also been simplified for the review process. Projects now open directly to the analysis view after a question is asked, with the underlying pipeline available a click away instead of the default starting point. "With this release, we want to keep business users focused on answers first, with the technical detail available on demand rather than upfront," said Bains. Prophecy's AI data prep and analysis capabilities for business users include: * A specialized data agent that draws on user prompts and metadata-based knowledge graphs to handle data tasks, including data prep workflows, onboarding data into target formats, and running analyses on demand * A step-by-step review flow, powered by Prophecy's specialized AI agents built on specialized Claude Code, enabling business users to see what an AI agent added or changed in a workflow or chart (piece by piece) before approving the output * A single canvas for AI data prep and analysis, so business users can refine workflows and generate charts without switching between separate tools * Analysis dashboards that turn a plain-language question into charts and summary findings so that users can test hypotheses and ask clarifying questions without writing a query AI agents for Snowflake. Prophecy's expansion of its AI agent products to Snowflake gives business analysts at Snowflake-native organizations the same self-serve workflow, without moving data outside the customer's existing environment to get there. Master Coding Skills "Most AI tools on the market assume you'll pull data out to somewhere else to get value from it," said Maciej Szpakowski, CTO, Prophecy. "Running our AI data prep tools on Snowflake ensures governance and access stay exactly where the data platform team already puts them - and wants them - and that the AI agent works within those boundaries instead of around them."