The Ontomato approach

Give your AI a model
of your business.

An ontology gives your data a shared vocabulary: the things that matter, how they connect, and what your business definitions mean.

Define

Give each thing a meaning.

Supplier, Product and Order are types in one connected model.

SupplierMaterial batchProductOrderFeedback

Map

Connect meaning to a source.

A relationship becomes usable when its keys resolve the matching records.

orders.product→products.id
products.batch→batches.id
feedback.order→orders.id

Inspect

Keep the calculation inspectable.

All tire reports in the fictional sample match three orders. Count each order once.

$99,50048,000 + 32,500 + 19,000Inspect the working example

From definitions to a traceable result.

The question may be simple. The route through your data rarely is.

Our example follows feedback through orders, products and material batches to a supplier. The model makes each step explicit, including which date to filter and which amount to count.

01

Define the object types

Give Supplier, Order and Product stable identities and understandable properties. Keep the type separate from its records.

02

Map the sources

Connect source fields to those properties. Declare the keys that make a relationship possible.

03

Apply the meaning

Choose a business definition, calculate against matching records, and keep the evidence with the result.

A small example. A visible difference.

DefinitionMatched ordersOrder total
All tire reports3$99,500
Confirmed defects only2$67,000

These totals are computed from fictional records. Multiple feedback records on one order do not cause its amount to be counted twice.

Walk through the calculation

Know what is available.

Follow the question. Inspect the answer.

Start with the working example. No account needed.

Try the example

The next layer of the experience.