PLATFORM

One Control Plane. Every Layer of Your AI Stack

Six purpose-built Guards. One unified policy engine. Four enforcement outcomes on every interaction.

PLATFORM

One Control Plane. Every Layer of Your AI Stack

Six purpose-built Guards. One unified policy engine. Four enforcement outcomes on every interaction.

ARCHITECTURE

How Our 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 interaction to 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 interaction to 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.

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

Every decision carries one of four outcomes. Each is logged with a confidence score, a reason code, and a permanent entry in the audit trail.

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.

Learn more about Red Teaming

Learn more about 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.

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.

Learn more about Red Teaming

Learn more about 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.

AI VALUE CHAIN

Built for every layer. Deployed where you need it

Beyond Guard covers six distinct interaction surfaces in your AI stack. You might use one, three, or all six, each Guard operates independently.

  • DATA

    Where training data, vector embeddings, user-uploaded files, and retrieved knowledge enter the AI pipeline. Threats here poison downstream inference and leak sensitive information outbound.

    Threats
    Controls

    RAG corpus poisoning — adversarial content injected into the knowledge base

    PII and secrets surfaced through vector search results

    Malicious file uploads — embedded scripts, steganographic payloads

    Indirect prompt injection via retrieved documents


    See Data Leakage & PII

    See Data Leakage & PII

  • Node 02

    Model

    Where learned behaviour is encoded and where supply chain integrity matters. The target of jailbreaks, prompt injection, and system prompt extraction attacks.

    Threats
    Controls

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    See Data Leakage & PII

    See Data Leakage & PII

  • Node 03

    Application

    Where prompts are formed, scope is enforced, and business logic meets the model. Threats exploit the gap between intended and actual model behaviour.

    Threats
    Controls

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    See Data Leakage & PII

    See Data Leakage & PII

  • Node 04

    Agent

    Where LLMs take autonomous action — chaining tool calls, maintaining memory, executing plans. The fastest-evolving attack surface in enterprise AI.

    Threats
    Controls

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    See Data Leakage & PII

    See Data Leakage & PII

  • Node 05

    MCP / Tool

    Model Context Protocol servers and external tool integrations. A category that didn't exist before 2024 and is now one of the fastest-growing attack surfaces.

    Threats
    Controls

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    See Data Leakage & PII

    See Data Leakage & PII

  • Node 06

    User

    The last mile — where responses reach humans, where unmanaged AI usage happens, and where outbound data leakage is measured. This is often the first surface an organisation needs to secure.

    Threats
    Controls

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    Tool Poisoning

    Malicious definitions manipulating model behaviour

    See Data Leakage & PII

    See Data Leakage & PII

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 full deployment journey

STEP

Observable Mode

All six Guards deployed in scoring-only mode. First-time visibility into your AI traffic risk.

STEP

Policy definition

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

STEP

Selective enforcement

Activate the most critical controls first. Measure impact and tune thresholds as you scale.

STEP

Full enforcement

All six Guards active across every surface. Four outcomes operational. Audit trail streaming to your SIEM.

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, applied across every Guard and every surface. These are what make BeyondGuard a control plane, not a collection of point tools.

The controls that bind the chain

Six platform-level capabilities, applied across every Guard and every surface. These are what make BeyondGuard a control plane, not a collection of 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

What we're learning and sharing.

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

See All

See All

Research

Adversarial Multi-Turn Prompt Injections

Guide

AI Security Glossary

Research

Decoding the Latest AI Exploits

RESOURCES

What we're learning and sharing.

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

See All

See All

Research

Adversarial Multi-Turn Prompt Injections

Guide

AI Security Glossary

Research

Decoding the Latest AI Exploits