The conversational interface for your data warehouse that turns natural language into actionable SQL and visual insights.
DataSpeak is a high-performance conversational business intelligence platform designed to democratize data access within enterprise environments. By 2026, it has solidified its position as a leading 'Autonomous Data Analyst' by integrating deep-context LLMs with proprietary semantic mapping technology. Unlike traditional BI tools that require manual dashboard construction, DataSpeak allows non-technical stakeholders to query complex relational databases—such as Snowflake, BigQuery, and PostgreSQL—using plain English. Its technical architecture focuses on a 'Metadata-First' approach, where only the schema and obfuscated metadata are processed by the LLM, ensuring that sensitive PII never leaves the local environment. The platform includes a self-healing SQL engine that learns from user corrections, improving accuracy over time. Positioned as an essential layer for data-driven teams, it reduces the burden on data engineering departments by automating repetitive reporting tasks and providing instant, verifiable insights through chat-based interfaces like Slack and Microsoft Teams.
Filters and obfuscates sensitive data at the proxy level before sending schema information to the LLM for query generation.
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Transform raw data into real-time metrics with a powerful semantic layer and automated BI dashboards.
The AI-powered data scientist that automates complex analysis, visualization, and predictive modeling through sandboxed code execution.
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Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses graph-based schema analysis to automatically identify foreign key relationships even when they aren't explicitly defined in the DB.
Maintains a feedback loop where user corrections are converted into vector-based 'context embeddings' for future queries.
Seamlessly translates a single natural language prompt into database-specific SQL (T-SQL, PL/pgSQL, Snowflake SQL).
Predictive heuristic engine that determines the most effective chart type (Bar, Sankey, Heatmap) based on the resulting data shape.
Advanced understanding of relative time periods (e.g., 'last Tuesday vs the same day in 2024') within natural language.
Automated background execution of NLQ prompts to update cached data views for high-performance dashboarding.
Sales managers need real-time updates on pipeline changes without waiting for weekly BI reports.
Registry Updated:2/7/2026
A bar chart is returned directly in the Slack thread with a link to the raw data.
Support teams need to identify 'at-risk' users based on login frequency and ticket volume.
Finance teams spend days manually verifying transactions across different systems.