Amazon QuickSight
Unified serverless BI with Generative AI for data-driven decision making at scale.
Turn Natural Language into Production-Ready SQL and Executive Insights
DataQueryAI is a high-performance Generative BI platform designed to bridge the gap between non-technical stakeholders and complex relational databases. Built on a proprietary RAG (Retrieval-Augmented Generation) architecture optimized for metadata schemas, DataQueryAI analyzes database structures to generate context-aware SQL queries from natural language prompts. As of 2026, the platform has evolved from a simple query generator to a comprehensive 'Data OS' that handles schema mapping, query optimization, and automated visualization. Its technical core leverages a multi-model approach, routing simple queries to efficient small language models (SLMs) while utilizing frontier models for complex multi-join operations. The platform prioritizes data privacy through a 'Schema-Only' access protocol, ensuring that raw data never leaves the client's infrastructure. Positioned as a direct competitor to legacy BI tools, it offers a self-service experience that drastically reduces the burden on data engineering teams by automating the generation of ad-hoc reports and real-time dashboards.
Uses embeddings to map colloquial business terms (e.g., 'Churn') to complex SQL logic (e.g., 'status = 0 AND last_login < 30 days').
Unified serverless BI with Generative AI for data-driven decision making at scale.
Transform business intelligence with generative AI that answers data questions in seconds.
The all-in-one generative BI and predictive AI platform for data-driven growth teams.
The enterprise-grade natural language interface for structured data.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Analyzes the generated SQL against the DB execution plan to suggest indexes or rewrite inefficient joins.
Supports real-time translation between Snowflake, BigQuery, PostgreSQL, and T-SQL.
Integrates directly with dbt (data build tool) to pull existing documentation and metrics definitions.
Connects to Kafka or Pulsar streams to provide real-time NL-querying on moving data windows.
Processes only metadata on the control plane; row-level data stays within the customer's firewall.
Generates a textual summary explaining the 'why' behind the data trends identified in the query.
CEOs need answers to complex questions immediately without waiting 48 hours for a data analyst.
Registry Updated:2/7/2026
Support agents need to check user status in the DB but lack SQL skills.
Marketing teams struggle to join Salesforce data with internal product usage logs.