Trampolyne Enterprise AI Governance Platform Reviews & Product Details

Trampolyne Enterprise AI Governance sits inline between users and production AI systems, enforcing what the AI can access, do, and share on every request before the model or tool executes. Policies are generated from existing industry standards, org IAM entitlements, DB extract, policy documents, business rules - whatever is available - and versioned for audit. Enforcement covers model prompts, retrieval context, tool calls, outputs, and approval paths. Per-request decisions check user identity, data sensitivity, intended action, tool scope, and behavioural risk in milliseconds. Actions are then allowed, blocked, redacted, or routed for exception handling. Supports RBAC, ABAC, PBAC, and composable hybrid policy models. Integrates as an API gateway - no model rewrites, no SDK changes, typically ships in days. Every policy decision is logged with actor, context, decision path, and versioned rule history. This provides security teams, compliance functions, and incident response teams with a complete, auditable record. This is useful for internal reviews, customer security questionnaires, regulatory readiness, and forensic investigation. Built for internal copilots, tool-using agents, customer-facing AI, and shared governance programmes across security, platform, and product teams.