How it works

Three products. One place.

Trampolyne covers the full AI security span at runtime - from continuous automated testing to governing employee AI use to enforcing policy inside production systems. Each product works independently or together.

Product 1

AI Red-Teaming

Find exploitable vulnerabilities in your AI system before procurement, regulators or attackers do. Not a generic checklist - context-aware adversarial testing specific to how your AI is built and deployed.

01

Configure your target

Provide your AI system's entry points - API endpoint, web interface or integration URL. Add business context: what the AI is supposed to do, what data it can access, what tools are connected.

02

Automated adversarial testing runs

Trampolyne runs a structured attack battery: prompt injection, jailbreaks, indirect injection via documents and tools, data exfiltration probes, privilege escalation attempts and multi-turn manipulation. Attacks are calibrated to your context - not templated.

03

Findings are mapped and ranked

Every finding maps to the OWASP LLM Top 10, OWASP Agent Top 10 and MITRE ATLAS. Severity is ranked by exploitability and business impact. Each issue includes proof of exploit - a working attack sequence, not a theoretical risk.

Report delivered - technical and governance layers

Engineering teams receive detailed technical remediation. Security reviewers and procurement teams receive a clean, evidence-backed summary formatted for AI security questionnaires and audit submissions.

No agent or SDK required

Trampolyne tests your system externally, the way an attacker would. No code changes needed.

📋

OWASP and MITRE mapped

Every finding references a numbered OWASP and MITRE categories, so security reviewers are well informed.

🔁

Re-test after remediation

Once you fix issues, re-run the same test battery to confirm they are resolved before your next review.

📅

Scheduled cadence available

As your AI system evolves, keep red-teaming on a regular schedule - the luxury of quarterly tests is gone.

Product 2

Shadow AI Controls

Your employees are already using AI tools. Some of what they share is sensitive. Shadow AI Controls enforce data governance at the point of AI interaction - without blocking productivity.

👤
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
01

Deploy the proxy or browser extension

Trampolyne sits between employees and the AI tools they use. Deployment includes an optimal combination of central and endpoint utlities to enable unmissable results with negligible perceived latencies.

02

Define your data policies

Specify what counts as sensitive: source code, PII, customer records, financial data, internal documents, source systems and more. Import from your existing DLP classification if you have one or author rules via the dashboard.

03

Traffic is classified in real time

Every prompt sent to an AI tool is classified against your policy before it leaves your environment. Sensitive data is blocked or redacted. Clean requests pass through transparently.

Full audit log, exception workflow

Every interaction is logged with classification result and decision. Employees can request exceptions for legitimate business use - with approval flow built in.

Product 3

Enterprise AI Governance

Inline, pre-execution policy enforcement for AI systems you have built and deployed. Trampolyne sits between your users and your AI - checking every request against your policies before any model or tool executes.

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.

The platform support all standard access control models:

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
01

Understand the request

Who is asking, what data is involved and what tools could be used - captured before evaluation starts.

02

Check against your policies

Your organization-defined rules are evaluated in real time and resolved in milliseconds.

03

Apply behavioral checks

Unusual requests, multi-session and multi-turn patterns, privilege escalation attempts and prompt injection signals are flagged automatically.

Allow, block or escalate

Every decision is logged with audit trail, severity mapping and actionable context.

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

Point traffic at Trampolyne

Route your AI API calls through Trampolyne's gateway endpoint. One DNS or config change.

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.