Service
AI-Ready Data
We help you make the warehouse safe for AI: governed inputs, documented grain, and a clear gate for what a copilot or agent is allowed to quote.
The work
How we help
Warehouse AI, Cortex-class tools, and internal agents will pick a join path and answer with confidence. They will not flag that two revenues already exist. We prepare the data layer first — marts, features, semantic context — then the go-live rule for what the model may say.
This is not a model-training engagement. It is the data work that has to be true before anyone points an agent at the board pack.
When this is the engagement
Leadership wants a copilot or internal agent on certified data, and the team cannot yet say which revenue is real.
Contracted and invoiced by Havilah Technologies LLC. Delivery in your warehouse and your git.
- 01Identify which certified marts and features an agent or copilot is allowed to read.
- 02Document grain and semantic context so the tool is not guessing the join.
- 03Set a go-live gate: which metrics may be quoted, and which require a human.
- 04Build Python services around the warehouse where scoring, orchestration, or APIs are required.
- 05Refuse to point a model at unresolved duplicate definitions of the same business number.
Typical work
What an engagement looks like
01
AI-ready marts
Selection and hardening of tables and features that are clean enough for retrieval or Cortex-class tools.
02
Semantic context
Views, descriptions, and grain notes the tool can use instead of inventing a join.
03
Go-live gate
A written list of what the model may quote, for whom, and what happens when it cannot.
04
Warehouse-adjacent services
Python APIs or scoring jobs that sit next to Snowflake/AWS when the use case needs them.
What you receive
Deliverables
- Marts and features an agent is allowed to read
- Documented grain and semantic context
- A go-live gate for what the model may quote
- Python around the warehouse where scoring or APIs are required
Capabilities
In scope
- AI-ready marts, features, and documented grain
- Semantic views and governed context for Cortex-class tools
- Agent go-live gates: what the model is allowed to quote
- Python services around the warehouse (scoring, orchestration, APIs)
Related services
dbt, SQL & Transformation
We build and refactor the dbt and SQL layer that turns landings into certified marts finance and operations can both use.
Data Integrity, Quality & Governance
We put tests, lineage, owners, and reconciliation in place so accuracy holds after delivery — at close, audit, and in regulated programs.
Analytics Architecture & BI
We define and deliver the metric layer so Tableau, Power BI, or Looker reports the warehouse — not a fourth version of revenue.
Discuss AI-Ready Data.
AI-Ready Data is contracted under Havilah Technologies LLC. Tell us the stack, the systems, and the outcome.