The Problem
Enterprise AI deployments fail not because models lack capability, but because they lack context. Data lives across dozens of systems — CRM, ERP, data warehouses, documents, chat platforms — each siloed and inaccessible to AI agents in real time.
Without unified context, AI agents hallucinate, return incomplete answers, and require constant human oversight. The promise of autonomous AI operations remains unfulfilled.
The mantle Approach
mantle sits between your data infrastructure and your AI agents as a semantic context layer. It connects to every enterprise data source, builds a real-time knowledge graph with entity resolution, and serves quality-scored context via MCP — giving every AI agent the full picture in under 100ms.
Key Capabilities
Unified Data Access
42 zero-copy connectors read data in place across every enterprise system. No ETL, no data movement, no duplication.
Semantic Understanding
Knowledge graph with 200+ entity types resolves identities and maps relationships across all connected sources in real time.
Quality-Scored Context
Every piece of context is scored for relevance, freshness, and reliability — ensuring agents act on signal, not noise.