Platform overview

Three products. One enforcement layer.

Trampolyne covers the full AI security span - adversarial testing before you ship, runtime governance over what employees share, and inline policy enforcement inside the AI systems you've built. Each product works independently or together as one platform.

Decision framework

Which product fits your situation?

The three products address different risk surfaces. Most customers start with one and expand.

AI Red-Teaming

You're building or operating an AI product and need to know what a determined attacker - or an enterprise procurement security team - would find.

Start here if:
  • An enterprise deal stalled on security questions
  • You're shipping a new AI feature to enterprise customers
  • You want a VAPT equivalent for AI - not a checkbox
See AI Red-Teaming →
Shadow AI Detection & Runtime Control

You're responsible for what employees share with ChatGPT, Claude and public AI tools - and you need enforcement, not just policy documents.

Start here if:
  • You have a DPDP Act, EU AI Act or ISO 42001 obligation
  • You need audit-grade evidence of AI data governance
  • Employees are using unsanctioned AI tools with real data
See Shadow AI Detection & Runtime Control →
Enterprise AI Security & Runtime Control

You've built AI agents or copilots and need policy enforcement at runtime - controlling what they can access, do and share before they act.

Start here if:
  • Your AI accesses sensitive systems or data at runtime
  • You need role-based or context-aware AI access control
  • Enterprise customers ask how you limit AI scope
See Enterprise AI Security & Runtime Control →

Not sure? A 20-minute call is enough to figure it out.

Product 1 · AI Red-Teaming

Find what attackers - and enterprise buyers - will find.

Trampolyne builds a custom attack model for your AI product and tests every known AI-specific attack class adversarially. The output is a report with working exploit sequences, OWASP/MITRE mappings and engineering-ready remediation - formatted for both technical teams and security reviewers.

27+ attack classes covered

Prompt injection, jailbreak, system prompt extraction, tenant isolation bypass, agent workflow manipulation, MCP & tool-call hijacking, data exfiltration and more - calibrated to your architecture.

OWASP LLM Top 10 & MITRE ATLAS mapped

Every finding maps to a numbered framework category. Security reviewers and compliance teams get the evidence layer they need - not just a vuln list.

No code changes required

Trampolyne tests externally, the way an attacker would. Provide an endpoint and business context - we handle the rest. No SDK, no agent, no model rewrites.

Now live on AWS Marketplace

Available directly or through AWS Marketplace. Re-test after remediation. Scheduled cadence available.

See full AI Red-Teaming details →
Product 2 · Shadow AI Detection & Runtime Control

Enforce data governance at the point of AI interaction.

Trampolyne sits between employees and every AI tool they use - classifying what's being shared, applying your data policies, and blocking sensitive data before it leaves your environment. Clean requests pass through transparently. Every interaction is logged for audit.

Employee
Uses AI tool at work
Request + data
Trampolyne
Classifies data, applies policy
Classify Policy eval Allow / Block
Clean request or blocked
AI Tool
Web LLM, API, MCP surface

All AI surfaces covered

Web LLMs (ChatGPT, Claude, Gemini, Copilot), LLM APIs, MCP workflows, productivity copilots and agentic pipelines - every channel through which org data can reach an external AI service.

Context-aware classification

Data is classified by type, provenance and user role - not just keyword match. PII, source code, customer records, financial data, regulated documents.

Audit trail for EU AI Act, DPDP & ISO 42001

Every interaction logged - what was shared, by whom, what policy triggered, what was blocked. Continuous compliance evidence, not a point-in-time snapshot.

Exception workflow built in

Employees can request exceptions for legitimate business use via a built-in approval flow. Productivity preserved, governance maintained.

See full Shadow AI Detection & Runtime Control details →
Product 3 · Enterprise AI Security & Runtime Control

Inline policy enforcement for AI systems you've built.

Trampolyne sits between your users and your AI - checking every request against your policies before any model or tool executes. Your IAM, your policy documents and your business context become composable, versioned, independently testable policies deployed in one click.

What you bring

IAM & entitlements
Groups, roles and existing access controls
Policy documents
Structured or natural-language authored rules
Business context
User roles, data classification, tool scope

What Trampolyne generates

Composable, versioned, independently testable policies. Deployed with one click from the dashboard.

All standard access control models supported:

RBAC
ABAC
PBAC
NGAC
User or System
Issues AI request
All traffic
Trampolyne AI
Enforces policy before the AI acts
Context Policy eval Enforce
Allow / Block / Modify
AI System
LLMs, agents, tools, APIs
See full Enterprise AI Security & Runtime Control details →
Integration

Ships in days - without touching your models

No SDK sprawl. No model rewrites. Trampolyne integrates as an API gateway or proxy layer, transparent to your existing architecture.

1

Connect through the proxy layer

Deploy Trampolyne's proxy or listen to your existing proxy layer. One config change - no SDK, no model rewrites.

2

Import your policies

Connect your IAM, upload policy documents or author rules in natural language via the dashboard.

3

Test before you push

Run policy tests in a sandboxed environment. Invite colleagues or red teamers before promoting to production.

4

Monitor and iterate

Live logs, exception management and risk dashboards keep your posture tight as usage grows.

Ready to see it in your environment?

A 20-minute call is enough to establish which product fits your situation first and what setup looks like.