Reliable agentic analytics
for your company's data.
Databao connects your data sources to a governed semantic layer, letting both tech and business users ask questions in natural language and get reliable, reproducible answers.
No more stalled dashboards, no ad-hoc tickets.
Two open-source tools to make your data AI-enabled
Fighting LLM hallucinations on SQL? Start with Context Engine. Want business users to self-serve analytics? Add the Data Agent.
Both open source, both run in your environment.
Context Engine
Automatically generate a governed semantic context from your databases, BI tools, documents, and spreadsheets — open source and designed to run locally in your environment.
Integrate it with any LLM to deliver accurate, context-aware answers. No more copying schemas or manual documentation.
Data Agent
Open source, local agents to query, clean, and visualize enterprise data.
Ask in plain language and get reliable, production-quality SQL across multiple tables, without switching between SQL editors, BI tools, and Python notebooks.
View SDK example on Colab
Analytics tool (CLI)
CLI for managing Databao components and for local testing of the end-to-end conversational analytics flow.
Set up, configure, and orchestrate your data workflows from the terminal — designed for engineers who prefer CLI-first tooling. The tool includes a Streamlit chat-based interface for testing conversational analytics scenarios end to end.
Enable production-ready agentic analytics & BI
Give your business users the power to ask questions in natural language and get verified, reliable answers instantly.
Trusted answers with no-code visualisations. No SQL, no friction.
Available everywhere:
- •In Slack. Enable users with data insights directly in Slack conversations
- •In your Web portal. Embed a self-service analytics block into your internal portal.
- •Integrated into any tool. Internal apps, or customer-facing products
Meet the teams building the future
Join Discord“Before Context Engine, I had to copy and paste my database schema into the LLM. Now I just point Context Engine to my data source and ask it to create a query, and it works. No more wrong column types, format mismatches, or hallucinations.
From local setup to a team platform
Databao starts as open-source building blocks you can run locally and experiment with today.
We're now building a team-ready SaaS layer on top of this foundation, designed for shared context, collaboration, and production workflows.
Individual
Best for: exploring concepts, prototyping, and working locally.
What you get today:
- Run components locally
- Test context generation and agent actions
- Access community plugins and docs
Databao SaaS
Best for: teams that need shared context, collaboration, and reliability at scale.
Tell us about your team's needs.
What's coming:
- Shared semantic context engine
- Multi-user workspace
- Self-service BI for teams
- Access control & observability
- Always up-to-date context
- Fully managed infrastructure (no setup or maintenance)
Join data engineers building with Databao
Get help, share tips, and shape the product.