M1 Unify and M1 Assure are built on the same foundation — AI-native entity resolution and a privacy model that keeps every client's data inside its own boundary.
A single, governed view of customer, policy, and party data — resolved by machine learning instead of hand-written match rules that break every time a source system changes.
Probabilistic matching trained on insurance and financial services data patterns — names, addresses, and party relationships that rules-based MDM tools consistently miss.
Every merge, split, and survivorship decision is logged and reversible. Data stewards see exactly why a record looks the way it does.
Built to sit alongside Guidewire, Majesco, Oracle OIPA, and IBM IAA/IIW environments without requiring a core replatform.
AI applications built specifically for P&C and specialty insurance workflows — not a general-purpose model with an insurance prompt library on top.
Each deployment runs in a dedicated tenant or inside the client's own cloud environment. Outputs, prompts, and documents never train a shared model.
Models and workflows are tuned on policy, claims, and rating concepts, so outputs read like they came from someone who understands the business.
Pre-built connectors for Guidewire, Majesco, and Oracle OIPA-based cores shorten the path from pilot to production.
Most engagements start with a scoped pilot against a real subset of your book — not a generic demo environment.
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