AI SECURITY PLATFORM

One Control Plane. Every Layer of Your AI Stack

Six purpose-built Guards inspect prompts, files, RAG context, agents, MCP tools, and model outputs through one policy engine with four enforcement outcomes: allow, deny, mask, and rewrite.

AI SECURITY PLATFORM

One Control Plane. Every Layer of Your AI Stack

Six purpose-built Guards inspect prompts, files, RAG context, agents, MCP tools, and model outputs through one policy engine with four enforcement outcomes: allow, deny, mask, and rewrite.

ARCHITECTURE

How the BeyondGuard Platform Works

Users & Apps

Employees

AI Chatbots

AI Agents

MCP Clients

RAG Applications

Prompt Guard

Context Guard

RAG Guard

File Guard

Agent Guard

MCP Guard

CONFIDENCE SCORING · UNIFIED POLICY

Allow

Deny

Mask

Rewrite

AI Value Chain

LLM Providers

Agent Frameworks

MCP Servers

Vector Databases

External Tools

On-premise Models

HOW IT WORKS

From AI Interaction to Security Decision

Every AI interaction in your organisation passes through BeyondGuard before reaching its destination: prompts, file uploads, agent plans, tool calls, model responses. Each of the six Guards inspects the pattern at its layer, scores it with a confidence threshold, and feeds the result to a unified policy engine that decides what happens next.

HOW IT WORKS

From AI Interaction to Security Decision

Structurally independent

BeyondGuard sits outside the LLM's execution context, not inside it. Swap your model, change providers, or watch the model itself get jailbroken. Enforcement continues unchanged.

Structurally independent

BeyondGuard sits outside the LLM's execution context, not inside it. Swap your model, change providers, or watch the model itself get jailbroken. Enforcement continues unchanged.

Model-agnostic

Works with any LLM: OpenAI, Anthropic, Google, Meta, Mistral, or your own on-premise models. Run them side by side under one security layer. No code changes required.

Model-agnostic

Works with any LLM: OpenAI, Anthropic, Google, Meta, Mistral, or your own on-premise models. Run them side by side under one security layer. No code changes required.

Deploys where your data lives

On-premise, cloud, hybrid, or fully air-gapped. Runs as containerised microservices on Kubernetes or OpenShift, inside your perimeter, in the jurisdiction your data has to stay.

Deploys where your data lives

On-premise, cloud, hybrid, or fully air-gapped. Runs as containerised microservices on Kubernetes or OpenShift, inside your perimeter, in the jurisdiction your data has to stay.

Four Enforcement Outcomes for Every AI Interaction

Every decision produces one of four outcomes: allow, deny, mask, or rewrite. Each decision is logged with a confidence score, a reason code, and an audit-ready record.

Allow

The request passes through unchanged. Used when the interaction falls below your configured risk threshold.

Deny

The request is blocked and the user receives an explanation. Used for high-confidence adversarial content or unrecoverable policy violations.

Mask

The request passes through with sensitive elements redacted. Used when PII, credentials, or protected data appear in an otherwise legitimate interaction.

Rewrite

The request passes through in a reformulated, policy-compliant form. Used when content has drifted off-policy but the underlying intent is legitimate and worth preserving.

RED TEAMING

Know where you're exposed before you deploy a single control.

Most enterprise AI ships on the strength of a few hundred manually-written test cases. Beyond Guard runs thousands of adversarial attacks against your AI systems, mapped to the frameworks your auditors already know.

Explore AI Red Teaming

The attack surface expanded faster than teams can map

Enterprise AI systems now expose more entry points than manual review can track. Most teams are still catching up.

The judge runs in your production stack

Other tools judge attacks with a generic model. Beyond Guard uses the same classifier that protects your production stack, so what's caught in testing is caught in production.

RED TEAMING

Know where you're exposed before you deploy a single control.

Explore AI Red Teaming

The attack surface expanded faster than teams can map

Enterprise AI systems now expose more entry points than manual review can track. Most teams are still catching up.

The judge runs in your production stack

Other tools judge attacks with a generic model. Beyond Guard uses the same classifier that protects your production stack, so what's caught in testing is caught in production.

TIMELINE

Start by watching. Enforce when ready

Most organisations jump straight to blocking and spend weeks tuning false positives. BeyondGuard starts differently. Observable Mode runs all six Guards in scoring-only mode, calibrating against real traffic before a single control is enforced. Observable Mode deploys all six Guards in scoring-only mode. Every interaction is inspected and logged, nothing is blocked.

See the AI security deployment journey

STEP

Observable Mode

Selected Guards run in scoring-only mode to reveal AI traffic, risk patterns, and policy gaps without blocking users.

STEP

Policy definition

Define per-application policies, calibrated against Observable Mode data. No guesswork on thresholds.

STEP

Selective enforcement

Activate the highest-priority controls first, measure impact, and tune thresholds before expanding enforcement.

STEP

Full enforcement

Guards enforce allow, deny, mask, and rewrite decisions across selected AI surfaces, with audit records streaming to SIEM and governance systems.

ONGOING

Governance & continuous assurance

Red Teaming findings feed runtime policies automatically. Evidence packages generated on schedule.

The controls that bind the chain

Six platform-level capabilities apply across every Guard and every AI surface. Together, they make BeyondGuard a unified AI security control plane, not a collection of disconnected point tools.

The controls that bind the chain

Six platform-level capabilities apply across every Guard and every AI surface. Together, they make BeyondGuard a unified AI security control plane, not a collection of disconnected point tools.

Unified policy engine

One policy, applied consistently across all six Guards. Definitions set per application, per endpoint, per role.

Unified policy engine

One policy, applied consistently across all six Guards. Definitions set per application, per endpoint, per role.

Confidence scoring

Every detection produces a confidence score, not a binary match. Thresholds configurable per control, per application.

Confidence scoring

Every detection produces a confidence score, not a binary match. Thresholds configurable per control, per application.

Explainable AI

Every enforcement decision carries a reason code, human-readable and machine-parseable. The audit answer is in the decision record.

Explainable AI

Every enforcement decision carries a reason code, human-readable and machine-parseable. The audit answer is in the decision record.

Immutable audit trail

Every interaction logged, timestamped, and tamper-evident. Streams to SIEM and SOAR in real time, exportable for regulatory evidence.

Immutable audit trail

Every interaction logged, timestamped, and tamper-evident. Streams to SIEM and SOAR in real time, exportable for regulatory evidence.

Closed-loop assurance

Design, test, and runtime enforcement share one classifier. A finding from Red Teaming strengthens the runtime policy automatically.

Closed-loop assurance

Design, test, and runtime enforcement share one classifier. A finding from Red Teaming strengthens the runtime policy automatically.

Hybrid detection

AI classifiers trained on 717,000 attack samples, combined with deterministic rules. Together they cover the full surface.

Hybrid detection

AI classifiers trained on 717,000 attack samples, combined with deterministic rules. Together they cover the full surface.

Explore Explainable AI

RESOURCES

AI Security Research and Resources

Research reports, threat intelligence, deployment playbooks, and the occasional blunt opinion on where the AI security category is going.

See All

Blog

How to Evaluate AI Security Platforms in 2026

Whitepaper

Multi Dimensional Risk Management for LLM Safety

Research

Adversarial Multi-Turn Prompt Injections

RESOURCES

AI Security Research and Resources

Research reports, threat intelligence, deployment playbooks, and the occasional blunt opinion on where the AI security category is going.

See All

Blog

How to Evaluate AI Security Platforms in 2026

Whitepaper

Multi Dimensional Risk Management for LLM Safety

Research

Adversarial Multi-Turn Prompt Injections