Data for AI and analytics
AI that answers from the right records.
Forecasts, assistants and document automation are only as good as the data under them. We prepare and run that data: the entities, definitions, documents, access and test sets each use case depends on. Your team, a partner or a specialist we place builds the model.
01 / Symptoms
What it looks like.
- A pilot that demos on a sample and stalls on production data.
- Forecasts built on history broken by acquisitions.
- Document extraction that works, then attaches to the wrong customer or supplier.
- An assistant that can see more than the user may see.
- No test set, so "accurate enough" is a matter of opinion.
02 / What we do
The data under the model, not the model.
- Mapping each use case to the entities, sources and documents it needs.
- Resolving the customer, supplier, product and counterparty IDs it touches.
- One definition per metric and feature, traced to source.
- Feature and training data pipelines that are tested and monitored.
- Documents linked to the right records, with access that matches who may see them.
- Test sets and data checks that show when answers go wrong.
- Lineage you can show an auditor for each AI-assisted decision.
Building the model or the assistant is work for your team, a partner, or a specialist we place through Senior data talent. We say which fits.
03 / How it connects
Why it sits on top of everything else.
AI and analytics inherit every gap below them. If one customer has three IDs, the AI finds all three. If finance and sales define a metric differently, AI answers won't match board numbers. That's why we start with master data, definitions and documents.
04 / Experience
- Cloud platforms
- Delivery on Snowflake and Databricks.
- Party data
- An organization party master on Databricks for a specialty finance company.
- Specialists
- Data scientists, ML engineers and AI engineers available through Senior data talent.
Where it shows up
Questions
Do you build the AI?
We prepare and run the data it depends on. The model or assistant is built by your team, a partner, or an AI or ML engineer we place. We'll say plainly which fits.
Our vendor says its AI works on our data as it is.
Test it on a sample of real records first. Our assessment does that for a fixed fee, and the self-assessment gives you a first read in five minutes.
Start with 30 minutes.
Tell us the symptom. We'll tell you plainly whether we can fix it.