How it's built
Warehouse-agnostic by design. The NLP layer sits on top of a governed semantic model — so the same answer is correct whether your warehouse is Snowflake, Databricks, Fabric, or BigQuery.
- Acumatica (ERP)
- Ring Central
- Senta
- CRM
- Workday
- Custom APIs
- Snowflake
- Databricks
- Fabric
- BigQuery
- Metric definitions
- Entity resolution
- SQL generation
- Lineage & DQ
- Web app
- Slack
- Mobile
- Email digest
- Power BI / Tableau
Medallion data model
Bronze for raw, Silver for cleaned, Gold for the business-facing semantic layer.
CDC from every source system. Append-only, fully replayable. No business logic applied.
Deduped, type-cast, conformed entities. Customer is one customer across Acumatica, Ring, and CRM.
Governed metrics — Revenue, Margin, Service Calls — defined once, used everywhere. The NLP layer reads only this.
What this is, and what it isn't
Warehouse-agnostic
We don't replace Snowflake, Databricks, or Fabric — we sit on top. If you already invested in a warehouse, we ride that investment.
Governed, not freelance
The LLM doesn't invent metrics. It can only reference governed definitions in the semantic layer. Every number is traceable to a definition, a SQL query, and the DQ checks that ran.
More than a chatbot
Same engine powers ad-hoc Q&A, scheduled digests, anomaly detection, and KPI exploration for executives still defining what to measure.
Trust is the product
Every answer ships with its lineage. If trust breaks, the program dies — so trust is a first-class feature, not an afterthought.