Enkrypt AI Guardrails

Enkrypt AI Guardrails is a runtime policy layer for teams securing AI agents and the systems they connect to. It is strongest when controls must span prompts, retrieval, tools, and outputs rather than just the final response. Its broad enforcement reach comes with credit limits and short retention on the lower-cost plans.

Overview

The product can approve, modify, or block risky behavior across an AI workflow. Controls include filtering, rewriting, escalation, and approval or denial of tool calls. That is useful when risk can arise from an agent action or retrieved material as well as generated text. Coverage includes prompt injection, jailbreaks, unsafe tool actions, privilege or tenant boundary violations, sensitive data exfiltration, toxic content, and compliance risks.

Policies also apply to image and audio inputs, including injection defenses, extending its scope to multimodal deployments. Enkrypt claims guardrails latency under 15 milliseconds and stable behavior under load; those claims will matter to teams placing checks in live paths, though the product page does not establish how they hold for a particular workload.

Key features

Workflow controls and integrations

API-first integration, agent hooks or middleware, and an MCP Gateway offer multiple ways to put controls around an existing model stack. Identity claims can draw on Okta, Azure AD, or custom JWT claims, which is useful when policy decisions depend on request identity. The listed SDK language is Python, so teams standardizing on other languages may need to rely on the API or middleware approach.

Auditable enforcement

Logs include a policy ID, policy version, and reason code, and can be exported to SIEM. That gives security and governance teams concrete records for reviewing enforcement and supporting internal control evidence. Listed security posture credentials and alignments include SOC 2 Type II, ISO 27001, GDPR Ready, HIPAA Ready, and NIST AI RMF Aligned.

Pricing

Enkrypt uses a freemium model. The Explore plan costs nothing, billed Free forever, and includes 500 starting credits, 50 credits per month, seven-day data retention, and community support. It is suited to spot checks and evaluation, not sustained assessment: a comprehensive red team assessment requires 5,000 credits.

Launch costs $149 a month, billed monthly, and includes 5,000 starting credits, 250 credits per month, 30-day retention, and email support. It provides a substantial starting allocation, but the monthly allowance is modest for ongoing or broad evaluation. Scale costs $1,499 a month, billed monthly, with 10,000 starting credits, 1,000 credits per month, 30-day retention, and dedicated Slack or Teams support. It better fits teams needing higher recurring capacity and closer support, though retention remains 30 days.

Enterprise has custom pricing and includes custom allocation, custom retention, custom SLAs, and VPC or on-premises deployment; VPC usage is unlimited. It is the relevant option for organizations needing private deployment or terms tailored to their operating requirements. Explore's 50 monthly credits and seven-day retention are the clearest constraints for teams wanting a free ongoing service. The stated paid entry point is $134/mo (annual), while the listed Launch and Scale prices are monthly-billed amounts.

Platforms

Enkrypt supports API, self-hosted, and web platforms. Enterprise adds VPC or on-premises deployment, giving organizations with deployment constraints an option beyond the standard platform range.

Who it's for

This is best suited to enterprises securing AI deployments that use agents, tools, retrieval, or MCP and need policy enforcement with reviewable records. AI safety researchers and people building safer AI may find Explore useful for spot checks, but its small monthly credit allocation makes it a poor fit for comprehensive assessment. Teams seeking only a narrow text filter, or a generous free allowance for sustained testing, should compare alternatives.

Pros and cons

Pros

Controls span prompt, retrieval, tool, and output boundaries, addressing risks that a final-response filter can miss.

Multimodal image and audio injection defenses broaden coverage beyond text inputs.

Policy-versioned logs with reason codes and SIEM export support audit and internal control workflows.

Enterprise offers VPC or on-premises deployment, custom retention, and unlimited VPC usage.

Cons

Explore's 50 monthly credits and seven-day retention limit its usefulness beyond spot checks.

A comprehensive red team assessment requires 5,000 credits, far beyond Explore's monthly allocation.

Launch and Scale retain data for only 30 days; custom retention is reserved for Enterprise.

Python is the only SDK language listed, which may mean more integration work for teams using other languages.

Alternatives

AI Guardrail Software is a broader directory for comparing products in this category. Consider PromptGuard when a free plan with 20,000 monthly scans is more important than Enkrypt's wider workflow controls; its free plan is limited to one API key, one project, and 24-hour log retention, and its Team plan costs $19 a month.

Fiddler Guardrails offers a free plan with real-time protection against harmful exposure, hallucinations, toxicity, PII/PHI, prompt injection, and jailbreak attempts; it may suit teams prioritizing those protections. OpenSecureAI Prompt Firewall is worth considering for a self-hosted or web option with a free allowance of 2,000 API requests per month and in-browser tools and npm packages.

Openlayer Guardrails may fit teams looking for a free starting tier with 20,000 inferences per month, five projects, and one member. Amazon Bedrock Guardrails is a paid, web-based alternative with separately priced text content filters and denied topics. HiddenLayer AI Runtime Security is another paid option, available via API, Linux, self-hosted, and web.

VotalAI is a paid alternative with a free plan and free trial. PII Firewall is a free, Linux and self-hosted option whose open-source Python package uses regex-only installation without ML dependencies.

Verdict

Choose Enkrypt AI Guardrails if your organization needs auditable controls across an agent workflow and can budget for the credit capacity and retention it requires. Its main advantage is the combination of boundary-spanning enforcement, multimodal coverage, and exportable evidence. Look elsewhere if a small team needs generous free testing, or if Enkrypt's lower-plan quotas and 30-day paid retention do not match the assessment and review cycle.