Openlayer Guardrails

Openlayer Guardrails is a runtime policy layer for applications that send requests to AI models. It is best suited to teams that need configurable checks and decision records across live traffic. Its free plan is useful for a tightly scoped evaluation, but its single-member limit makes it a poor fit for a shared production workflow.

Overview

Guardrails can block, redact, escalate, or send policy violations for review as an application processes AI inputs and outputs. Teams can set which sensitive-data categories to block and which topics an assistant should avoid, so enforcement can reflect their own policies rather than a single fixed rule set.

Its checks target prompt injection, jailbreak attempts, PII and PHI exposure, and harmful or toxic content. Openlayer says it detects and blocks more than 50 PII and PHI entity types inline. That breadth is relevant to teams handling sensitive information, but it does not remove the need to decide which categories and topics their policies should cover.

Key features

Teams can enforce guardrails through the Gateway or apply them directly with the SDK. SDKs, framework integrations, a CLI, and a REST API provide additional ways to connect; the network-level Gateway is designed to work across LLM providers. This flexibility suits teams with varied integration needs, while the enforcement point still needs to fit their application architecture.

Each decision can include a timestamp, system version, owner, supporting trace, and reason for a block. Openlayer says this activity feeds compliance evidence and names the EU AI Act, ISO/IEC 42001, NIST AI RMF, and OSFI E-23. Those records can help teams explain and investigate policy decisions; they are not a substitute for their own compliance work.

Deployment options include a customer's VPC and air-gapped environments, with on-premise deployment reserved for Enterprise. Openlayer states that it has SOC 2 Type II certification and GDPR compliance, supports HIPAA-aligned use cases, and encrypts data at rest with AES-256 and in transit with TLS 1.2 or higher. These provisions may suit organizations with deployment or security constraints, though the on-premise option requires Enterprise.

Pricing

The freemium model starts with Basic at free. It includes one member, one workspace, five projects, one inference pipeline per project, 20,000 inference logs per month, 20 tests per project, three months of data retention, and community support through Discord. This is enough to assess the product on a small footprint, but the member, project, pipeline, and log caps constrain wider evaluation and ongoing team use.

Enterprise has custom pricing and includes unlimited members and projects, custom inference pipelines and logs, unlimited tests, custom data retention, SAML SSO, on-premise deployment, white-glove onboarding, and direct Slack access to Openlayer's team. It is the relevant tier for organizations that need those deployment or access controls and room to scale; teams without those requirements may find Basic's strict caps a limiting ceiling.

Platforms

Openlayer Guardrails is available through API, self-hosted, and web options. Its hybrid deployment model and Gateway, SDK, and integration routes give teams choices for fitting enforcement into their setup, while on-premise deployment is an Enterprise feature.

Who it's for

Openlayer says engineering, AI, security, compliance, and finance teams use the platform, including in healthcare and financial services. Guardrails is a stronger fit for organizations that need to govern live model traffic and preserve decision evidence than for an individual looking for a standalone prompt filter. Basic's one-member cap is especially restrictive for cross-functional evaluation; Enterprise is better suited to a team that needs shared access or custom deployment.

Pros and cons

• Pros: Policies can be tailored to sensitive-data categories and prohibited topics, with inline detection for more than 50 PII and PHI entity types.
• Pros: Decision records can retain the reason, trace, owner, timestamp, and system version, supporting investigation and compliance evidence.
• Pros: Gateway, SDK, framework, CLI, and REST API connections offer multiple integration paths, and the Gateway is designed for use across LLM providers.
• Cons: Basic allows only one member and one workspace, with five projects and 20,000 inference logs per month, limiting collaboration and scale.
• Cons: On-premise deployment, SAML SSO, custom retention, and advanced support require custom-priced Enterprise.

Alternatives

PromptGuard is worth considering for teams that want a freemium option with API, extension, desktop, self-hosted, and web platforms. Its Free plan allows 20,000 scans a month, one API key, one project, and 24-hour log retention; Team costs $19 a month.

Prompt Inspector offers a free plan with 1,000 detections per month, a REST API, SDK, and MCP. It may suit a smaller detection workload where those connection options meet the need.

NVIDIA NeMo Guardrails is a free, open-source Python package for teams that prefer that model; external models and services may require separate setup.

Amazon Bedrock Guardrails is a paid, web-based option for readers considering that product instead.

GLACIS has a free account with no card required and setup described as taking about a minute, making it an alternative for readers who want to begin with a free account.

LLM Guard is free and open source, but its repository is archived and no longer actively developed or maintained.

CyberSecEval is a free open-source benchmark suite, a different option for readers seeking benchmarks rather than this product's runtime guardrails.

Sanctum Runtime is another alternative; its documentation describes an MIT-licensed repository and an open-core product.

For broader category comparisons, see LLM Security Tools and AI Governance Software.

Verdict

Openlayer Guardrails is a good fit for organizations that need configurable runtime controls across AI traffic and records that explain decisions. Its integration choices and detailed decision evidence are the main reasons to choose it; the single-member Basic plan and custom-priced Enterprise tier are the main reasons to look elsewhere, especially if a shared team workspace is essential from the outset.