The AI Data Analyst that talks to your database and delivers instant, board-ready insights.
DataGPT is a next-generation AI data analyst designed to bridge the gap between complex data warehouses and business decision-makers. Unlike standard LLM-to-SQL tools that often hallucinate queries, DataGPT utilizes a proprietary 'Analytic Engine' that processes data locally to ensure 100% accuracy and sub-second latency. The architecture involves a semantic mapping layer that understands the relationship between different tables, enabling it to handle complex joins and aggregations that traditional SQL assistants struggle with. By 2026, DataGPT has positioned itself as the premier solution for 'Conversational BI,' allowing users to ask questions like 'Why did our churn rate spike in EMEA last Tuesday?' and receive not just a SQL query, but a full root-cause analysis with supporting visualizations. It integrates deeply with modern data stacks including Snowflake, BigQuery, and Redshift, providing a secure environment where raw data never leaves the user's infrastructure, only the metadata and query results are processed for the conversational interface. This makes it a critical tool for organizations looking to democratize data access without expanding their data engineering headcount.
A proprietary data processing layer that caches and optimizes query paths to provide sub-second responses even on multi-terabyte datasets.
Convert natural language prompts into high-performance SQL for the Atlassian Data Lake.
Conversational Business Intelligence for deep-dive data exploration and predictive forecasting.
Turn Complex Natural Language into Production-Ready SQL and Executive Insights Instantly
Turn complex data warehouses into conversational intelligence engines using agentic RAG and NLQ.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses machine learning to scan data patterns and proactively notify users of anomalies or significant trend changes.
Translates complex database jargon into business terminology, ensuring the LLM understands that 'rev_90_d' means '90 Day Revenue'.
The assistant breaks down complex prompts into multiple SQL queries to find correlations between disparate datasets.
Generates the most appropriate chart type (Bar, Line, Sankey) based on the dimensionality of the query result.
Displays the generated SQL side-by-side with the natural language answer for technical verification.
Applies Row-Level Security (RLS) policies from the source database directly to the AI chat interface.
Marketers struggle to identify which channels are driving the highest ROI without waiting for a data analyst's weekly report.
Registry Updated:2/7/2026
Detecting stock-outs before they happen based on seasonal trends.
Identifying at-risk customers by analyzing product usage drops.