Get your data ready for AI before you build on it
Most AI pilots that stall do so because of the data underneath: unclear definitions, undocumented tables and access nobody can explain. We assess where you stand, fix what matters, and give people and AI a reliable way to ask questions of your data.
What we do
- AI-readiness assessment of your platform, data models, quality and governance
- Semantic layers and metric definitions shared by analysts, dashboards and AI
- Natural-language analytics with Databricks Genie or Snowflake Cortex Analyst, delivered in Slack or Teams
- Unity Catalog governance: ownership, lineage and access control for AI workloads
- Agent-ready access to your data through governed APIs and MCP servers
- Data handling aligned with GDPR and the EU AI Act
Who it's for
Teams starting with AI
Find out what your data can support today, which use cases to pick first, and what has to change before you invest in models.
Teams whose AI pilot stalled
If answers are inconsistent or nobody trusts them, the fix is usually definitions and governance, not a better prompt.
Start small, with a clear scope
Fixed fee · 2 to 3 weeks
AI-ready data assessment
A review of your platform, data and governance against the AI use cases you have in mind, with a prioritised plan and cost.
Fixed scope · 4 to 6 weeks
Semantic layer & Genie sprint
One business domain modelled, defined and opened up for natural-language questions, inside your chat tool.
Fixed scope · 4 to 6 weeks
Agent-ready data sprint
Governed data access for agents: curated tables, APIs or MCP servers, permissions and evaluation data.
Tell us what you're trying to do
A 30-minute call with a practitioner. You'll get an honest view on fit, timeline and cost.