MIT puts it at roughly 95% of enterprise AI never reaching production value, against $40B+ invested. Customer records sit in the CRM, orders in the ERP, approvals in email and tickets, and every new use case has to rediscover all of it from scratch. The answer is one layer of context underneath them — intelligence that compounds, so every project after the first inherits it.
Connect every customer, employee, order and ticket into one model — with the relationships, permissions and actions already built in.
Connect the systems you already run with 1,000+ prebuilt connectors — CRM, ERP, HCM, warehouses, document stores, ITSM. Nothing gets ripped out and replaced.
Click a layer to see what it does inside the graph, or open its own page for the full detail.
One governed layer under every project — and five places the business feels it: revenue, risk, cost, speed and control.
Accelerate revenue cycles Shorten every cycle where back-office latency is the constraint — quotes, onboarding, collections, fulfilment.
Keep control as AI spreads Enforce RBAC and human approval, keep a full audit trail, and see model and agent usage centrally in one place.
Catch problems earlier Detect issues sooner, apply controls consistently, and defend every decision after the fact.
Lower marginal cost for every subsequent AI deployment Retire overlapping point solutions and bring token spend down with them.
Ship new AI use cases in days that work at scale Roll out each new use case faster once the first ones are live.
Industry-leading security and privacy standards.