How to Choose an AI Gateway: Enterprise Buyer's Guide 2026

Enterprise AI gateways in 2026 are presented as infrastructure layers that sit between applications and AI providers to enforce security policies, route traffic, log interactions, manage costs, and support compliance across LLM, Model Context Protocol (MCP), and autonomous agent workloads. The guide recommends evaluating gateways on seven core areas: independent prompt-injection and data-leakage protection, structured observability and tamper-evident audit logs, model-agnostic and cost-aware routing, cloud, self-hosted, or hybrid deployment options, compliance support for frameworks including the EU AI Act, UK GDPR, SOC 2, and ISO 27001, MCP inspection and agent-session controls, and portability to reduce vendor lock-in. It emphasizes that regulated organizations should prioritize data residency, gateway-level controls, SIEM integration, least-privilege agent access, and emergency shutdown capabilities, then validate vendor claims through practical security, routing, logging, compliance, and migration tests. The text positions NeuralTrust TrustGate as a product meeting these criteria, highlighting its security, observability, multi-model routing, deployment flexibility, compliance controls, and support for MCP and agentic AI.

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