Enkrypt AI Guardrails vs Google Cloud Secret Manager

Enkrypt AI Guardrails is a runtime layer for controlling risky behavior across AI agents, tools, retrieval-augmented generation, and MCP. It can filter, rewrite, block, or escalate at prompt, retrieval, tool, and output boundaries, and approve or deny tool calls. Covered risks include prompt injection, unsafe tool actions, boundary violations, sensitive-data exposure, jailbreaks, toxic content, and compliance issues. Policies apply to text, image, and audio inputs. The product supports API-first use with existing model stacks, agent hooks or middleware, MCP Gateway, SIEM and ticketing routes, and identity claims such as Okta, Azure AD, and custom JWT claims. Enforcement logs record a policy ID, version, and reason code and can be exported to SIEM. The product page claims latency under 15 milliseconds. Explore is free and includes 50 credits per month and seven-day data retention; Launch starts at $134/mo (annual). Enterprise includes VPC or on-premises deployment and custom retention.

Google Cloud Secret Manager has no write-up on Specifiction yet; its figures are above.