Enkrypt AI Guardrails vs Qpoint

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.

Qpoint monitors AI agents and applies policies where they run. It captures file activity, tool calls, outbound network requests and process execution, attributing events to agents and sessions. Policies can block secret reads, reject unapproved endpoints, redact outbound content and deny unapproved tool calls. Qpoint describes its endpoint deployment as a single binary, without gateways, sidecars or SDK integration; it can also run in containers, virtual machines, clusters and CI runners. It supports Linux, macOS, Windows and web, and lists Kubernetes support, network visibility and application tracing. Events can be exported to SIEM and observability systems, with Splunk, Datadog and Elastic named. The free Community plan covers up to 25 endpoints; Team covers up to 500, and Enterprise has unlimited endpoints. Enterprise includes SSO and role-based access control. Qpoint states that it has achieved SOC 2 Type II compliance.