Conversational Data Agents
We help organizations build trust in their data agent through metadata, business conventions, and validation.
We help organizations build trust in their data agent through metadata, business conventions, and validation.
Organizations that want to enable business users to query their data warehouse in natural language, while maintaining confidence in the answers they receive.
Conversational analytics can reduce dependency on analyst queues, but only if the agent understands the business context behind the data.
Assess table descriptions, column documentation, lineage, and ownership to identify gaps and inconsistencies.
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Identify the joins, filters, calculations, and business logic already used and trusted by your teams.
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Build a curated set of question-and-answer pairs that serve as reference examples for the agent.
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Evaluate answers across business questions and document where the agent performs reliably.
✓ A configured data agent for the selected business domain
✓ A qualitative QA assessment across business questions
✓ Updated metadata, descriptions, and documented conventions
✓ Findings and recommendations to support future agentic use cases
The proof of concept demonstrated how AI agents can already address today's analytical questions and revealed new possibilities for more complex, cross-functional analysis.
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Three weeks to a data agent your business actually trusts.