Data warehouses solved data fragmentation.
We solve context fragmentation — the structured
layer where AI agents query understanding, not just data.
Context, decisions, ontology, and metrics — unified into a single traversable graph. That’s the Intelligence Warehouse. Click any node to inspect.
Data warehouses store facts. BI visualizes them. But neither captures the decision context — the rules, logic, and tribal knowledge that drive actual operations. The Intelligence Warehouse is the missing architecture layer.
The graph doesn’t just replicate existing decisions — it discovers new ones by walking across functions.
“If markdown is imminent on slow-moving SKUs, reduce reorder quantity by 40% and accelerate promotion cadence.”
Every enterprise has decision logic trapped in tribal knowledge — rules, thresholds, and edge cases that live only in the minds of operators. Extracting this into a structured blueprint is the bottleneck everyone hits.
MORRIE is our agentic interface that solves this. It doesn’t hand you a questionnaire. It has a conversation.
Everyone else asks you to fill out a spreadsheet.
MORRIE has a conversation.
A unified intelligence graph doesn’t just organize knowledge — it transforms how enterprises analyze, decide, and act.
Structured context means agents query understanding, not raw data. Analytics become faster to build, easier to adapt, and more reliable at scale.
Every team, every agent, every workflow references the same ontology and decision rules. No more conflicting definitions or inconsistent logic across the organization.
Graph traversal discovers multivariate decisions that span supply chain, pricing, sales, and marketing — decisions no single team could see in isolation.
Stop building agents on fragmented context. Start with the infrastructure layer that makes AI actually work.