AIHigh complexity
Natural-language Analytics
An AI assistant over your modelled warehouse: ask questions in plain language and get governed, accurate answers, so the team self-serves without waiting on an analyst.
Ask your data a question and get a trustworthy answer, without writing SQL or waiting in a queue.
Who it's for
Teams whose questions bottleneck on the analytics team, and who have a modelled warehouse an assistant can safely query.
The engagement
What you get
- An assistant grounded in your semantic / modelled layer
- Guardrails: governed metrics, row-level access, answer citations
- Onboarding so the team knows what it can and cannot ask
What Fuse does
- Ground the assistant in the semantic layer and metric definitions
- Set access controls, guardrails and answer verification
- Pilot with a team, tune, and roll out
What we need from you
Data & access
- A modelled warehouse with defined metrics
- Access and governance rules
Your responsibilities
- Provide the modelled warehouse and metric definitions
- Confirm access and governance rules
Outcomes and proof
- Self-serve answers without an analyst in the loop
- Consistent numbers grounded in governed metrics
- Analysts freed for deeper work
Assumptions
- A trustworthy modelled layer exists to ground answers
Out of scope
- Answering off ungoverned raw tables
- Replacing judgement on ambiguous questions