OmniGuard · Runtime Detection & Response

Stop the unsafe response before it ships.

Detect and enforce at the model level. Block, re-route, or re-prompt before the user sees it.

OmniGuard Policies dashboard: active runtime policies, enforcement events, and policy violation timeline for production AI
Policy Authoring

Author policies in plain English.

Write the policy the way your security team explains it. OmniGuard compiles plain-English intent into runtime enforcement. No DSL. No template wrangling. No re-training.

OmniGuard policy authoring: plain-English policy creator with live preview of enforcement behavior

The only platform that detects and enforces at the model level.

01

BLOCK PROMPT INJECTIONS

Direct and indirect. Catches what pattern-matching gateways miss. See the response forming. Stop it before commit.

02

PROTECT YOUR BRAND

Stop the response that names a competitor, swears at a customer, or trashes your own company. In flight, before it reaches the user.

03

PREVENT DATA LEAKAGE

Sensitive data exfiltration, PII spillage, and unauthorized disclosures, blocked at the model layer rather than the gateway.

Coverage

The failure modes that put you on the front page.

01

Prompt injections & jailbreaks

02

Brand damage & harmful content

03

Sensitive data leakage

04

Bias amplification & unauthorized advice

Detected and enforced at the model interior, not at the input or output string.

How OmniGuard enforces.

OmniGuard deploys through an AI gateway. Detection happens in-line, not after the fact.

HOW OMNIGUARD ENFORCES

Inspect. Decide. Enforce.

01

INSPECT

Deep Neural Inspection reads the model's hidden states during inference. Sees the response forming, before commit.

02

DECIDE

Classifies intent against your policy taxonomy. Bring your own hazard categories, regulatory definitions, red-team test sets.

03

ENFORCE

Block, re-route, or re-prompt. The user gets the right answer or no answer, never the unsafe one.

Sits in front of every model.

OmniGuard intercepts at the gateway layer, in front of OpenAI, Anthropic, Gemini, and self-hosted models. No model swap. No prompt rewrite. The same instance protects every model your team uses.

Reference architecture: OmniGuard intercepts at the gateway layer in front of every model provider
In
prompt, tool calls, session metadata.
Out
allowed, blocked, or rewritten response, plus structured signal to your SIEM.
Deployment
SaaS, VPC, or fully on-prem.

Frequently asked.

What is the enforcement latency?

Under 50 ms at p95 for the detection decision. Enforcement adds the re-route or re-prompt time only if a block is triggered, which is the exception, not the norm.

What does OmniGuard catch that a content-moderation API does not?

Indirect prompt injections, multi-turn manipulation, brand damage, competition praise, and intent-level signal. Content-moderation APIs match patterns on the response string. OmniGuard reads what the model was about to do.

How does OmniGuard handle false positives?

Policy thresholds are tunable. Every decision produces a confidence score and a reason code. False positives are never silent.

Can I bring my own policies?

Yes. Bring your hazard categories, your regulatory definitions, and your red-team test sets. OmniGuard enforces them without retraining.

How is this different from a guardrail library like NeMo Guardrails or Llama Guard?

Those are gateway-layer pattern matchers. OmniGuard sees the model's internal state at inference time. It catches what surface-level filters cannot see and enforces with intent-level fidelity.

Built for enterprise AI.

Realm Labs easily integrates into your AI applications, agentic frameworks, and AI gateways, supporting enterprise AI infrastructure without requiring any changes.

SELF-HOST OR AIR-GAP

Run Realm in your VPC, in your on-prem cluster, or fully air-gapped. No data leaves your boundary, ever.

EVERY MODEL. EVERY FRAMEWORK.

OpenAI, Anthropic, Gemini, self-hosted Llama, Mistral, Phi. LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel.

YOUR POLICIES, YOUR TAXONOMIES.

Bring your own hazard categories, regulatory definitions, and red-team test sets. Realm enforces them.

PURPOSE-BUILT FOR PRODUCTION.

Not a re-skinned LLM-as-judge. Not a pattern-matching gateway. Realm's detection layer was built from scratch for sub-100ms enforcement at production scale.

ENGINEER-TO-ENGINEER SUPPORT.

Direct Slack with the team that built it. No tier-1 ticket queue.

Compatible with modern AI and cloud infrastructure

AWSMicrosoft AzureGoogle CloudOracle CloudNVIDIADocker

Stop the response that costs you the brand.

30-minute working demo. Bring your hardest prompt injection.

RUNTIME AI OBSERVABILITY AND CONTROL

See Realm in your environment.

30 minutes with the Realm Labs team. We tailor the demo to your stack. No slideware.

Use your work email. We auto-route you to the right person on our team.

Built on the same interpretability research foundation used at Anthropic, Google DeepMind, and OpenAI.