DataProdigy
Conversational Business Intelligence for deep-dive data exploration and predictive forecasting.
Convert natural language prompts into high-performance SQL for the Atlassian Data Lake.
Jira AI SQL is a sophisticated natural language to SQL (NL2SQL) engine integrated directly into Atlassian Analytics. Built on the Atlassian Intelligence framework, it leverages Large Language Models (LLMs) to bridge the gap between non-technical stakeholders and complex project data housed in the Atlassian Data Lake. The technical architecture focuses on semantic mapping of the Atlassian schema, allowing users to query across Jira Software, Jira Service Management, and Confluence using plain English. By 2026, this tool has matured into a core component of the Atlassian Cloud Enterprise offering, enabling autonomous dashboard generation and real-time predictive reporting. It eliminates the friction of manual SQL authoring while maintaining strict data governance through Atlassian's centralized permissions model. The system is designed to handle multi-product joins, such as correlating incident response times in JSM with developer velocity in Jira Software, providing a holistic view of the engineering lifecycle without requiring manual data extraction or third-party ETL pipelines.
Uses RAG (Retrieval-Augmented Generation) to inject specific Atlassian Data Lake schema metadata into the prompt context for hyper-accurate joins.
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.
The Intelligent Semantic Layer for Natural Language Data Analytics and SQL Automation
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
AI analyzes the returned result set and automatically selects the most effective visualization type (e.g., Heatmaps, Burndown charts).
Deconstructs complex SQL logic into human-readable steps to educate users and verify query logic.
The AI recognizes user-defined custom fields and project-specific nomenclature automatically.
Iterative chat interface to narrow down data sets without rewriting the original prompt.
Rewrites generated SQL to ensure index usage and minimize compute costs on the Snowflake-backed data lake.
Synthesizes data across the entire Atlassian ecosystem in a single query execution.
Leadership needs a cross-project view of budget vs. actual progress without manual exports.
Registry Updated:2/7/2026
Correlating Jira Service Management incidents with developer deployments to find root causes.
Identifying teams that are over-allocated across multiple concurrent projects.