An AI agent that answers business questions directly from structured data

The Challenge

The data warehouse was solid. The bottleneck was everything downstream of it. Every business question — whether it came from product, sales, or marketing — still needed a data analyst to write the SQL, build the view, and assemble a report. Teams were waiting days for answers they needed in the same meeting. The analysts were doing good work, but most of it was assembly, not analysis.

Our Approach

Before any AI was involved, the data was cleaned and documented into a well-structured semantic layer — clear definitions, reliable logic, nothing ambiguous. That groundwork is what makes the output trustworthy rather than plausible-looking.

An analytics agent was then built that interprets plain-English questions and returns data-backed answers drawn directly from the warehouse. It works only within the data it has access to, every response links to the source query and tables, and it won't fill gaps with guesses.

Deployment went through Slack — the tool everyone was already in. Any team member asks a question in a channel, gets an answer in seconds. No new tool, no training, no ticket.

Key Deliverables

• Clean, documented semantic data layer as the AI query foundation
• Analytics agent with natural language to SQL capability
• Slack integration for company-wide self-serve data access
• Full auditability — every answer linked to source query and tables
• Guardrails preventing out-of-scope or hallucinated responses

“The data team used to be a queue. Now anyone can get an answer in seconds. That changed how fast we move.”

— Head of Product, Global SaaS Scale-Up

Results

Engagement

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