Factual and interaction.
Maps every customer touchpoint (contracts, support cases, meetings, emails) into a permissioned graph the model can reason over. Every fact carries its source, timestamp, and ACL.
A live demo of a company brain.
Pretend this is your company. Four customers, five years of contracts, support cases, emails, meetings, commitments. Ask the brain anything about them. It reads from Microsoft Fabric, reasons with gpt-4o-mini, and shows you which parts of the ontology the answer touched.
Customer context is scattered across CRM, support, contracts, emails, and meetings. Nobody can answer "what is going on with this account right now" without four tabs and a call.
Unifies all of that into one graph on Microsoft Fabric. Every fact carries its source ID, timestamp, and ACL. An LLM reasons over it, cites the source, and proposes the next step with an approval gate.
A working demo over four sample customers (HelioWorks, Cobalt Harbor, Northstar, Juniper Vale). Each question fires the same three tools a production brain would: Foundry IQ retrieve, Fabric ontology context, gpt-4o-mini reasoning.
Every answer starts from grounded context. The brain turns scattered signals (emails, support cases, contract terms, product usage) into one permissioned graph that recalls, reasons, and acts.
Every answer starts from grounded context. The brain turns scattered signals (emails, support cases, contract terms, product usage) into one permissioned graph that recalls, reasons, and acts.
Every artefact maps to the layer where it lives. Factual is what happened. Interaction is why it matters. Action is what should happen next. Conflicts surface where teams hold different assumptions about the same thing.
The brain runs on Microsoft Fabric. The ontology binds entity types to Lakehouse tables, Fabric Data Agents reason over them, and Foundry IQ retrieves grounded knowledge with Microsoft Purview ACLs enforced end to end.
Maps every customer touchpoint (contracts, support cases, meetings, emails) into a permissioned graph the model can reason over. Every fact carries its source, timestamp, and ACL.
Surfaces the next step with owner, due date, and approval gate. Flags where teams hold different assumptions about the same customer, and shows the chain of evidence.