Your AI acts on real data.
Do you control what it can do?
Trampolyne sits inline between your application and your AI - enforcing policy before every action, in milliseconds, without architectural changes. Every decision is logged. Every enforcement is auditable. Your enterprise buyers get the evidence they need.
AI in production isn't like software in production.
It misbehaves in ways you won't see coming.
Traditional access control assumes deterministic behavior. Your AI doesn't behave deterministically. It makes decisions based on context, prompts, and learned patterns - and those decisions can violate your policies in ways that no WAF or SIEM will catch.
In every AI security assessment we've run, teams discovered their production AI had accessed data outside its intended scope - and had no record it happened. Not because their access controls were absent. Because access controls built for deterministic software cannot evaluate the context-sensitive decisions an AI makes at runtime. Trampolyne is the enforcement layer that closes this gap.
Inline. Pre-execution. Milliseconds.
Trampolyne intercepts every AI request before it reaches your model or agent. Policy is evaluated against full context - user identity, data sensitivity, agent scope, session history - and enforcement happens before execution.
Request arrives
User or system issues an AI request
Context assembled
Identity, data scope, session history pulled together
Policy evaluated
Your rules checked against full context in milliseconds
Enforce & log
Allow, block, modify, or redact - with full audit trail
AI executes
Only allowed actions reach your model or agent
Four policy frameworks. One enforcement layer.
Most Enterprise AI Security & Runtime Control needs more than role-based rules. Trampolyne supports all four major policy models - so you can enforce the right constraint for the right context.
Enforce what AI can do based on the requesting user's organizational role. An analyst can ask the AI to summarize data; a sales rep cannot ask it to export raw PII. Simple, auditable, scales across orgs.
Policy evaluated against any combination of attributes: user department, data classification, time of day, geographic context, device state. Enables fine-grained rules that RBAC alone cannot express.
Express complex governance intent in declarative policy - "AI may access customer data only when the customer has an active support ticket" - evaluated at runtime against live context.
Graph-based policy that models organizational structure, relationships, and permissions natively. Purpose-built for the complex multi-entity hierarchies found in enterprise AI deployments.
Everything you need to govern AI in production.
Every AI request intercepted and evaluated before the model acts. Policy violations blocked before data is accessed, not after the fact.
Every AI decision logged with full context: who requested it, what policy was evaluated, what was enforced, and why. Exportable for compliance reporting.
Anomalous AI behavior flagged in real time. When an agent attempts something outside its authorized scope, you know immediately - not when a customer reports it.
Update enforcement rules in real time without redeployment. Tighten scope, add new data classifications, or respond to an active incident - changes propagate instantly.
Deploys as an API gateway in front of your existing AI stack. No SDK integration. No model changes. No rewrites. Ships in days, not quarters.
Reports and logs designed to answer enterprise security questionnaires. Shows GDPR Art. 25/32 controls, EU AI Act Art. 14 human oversight evidence, and data minimization compliance.
If you run AI in production,
you need governance before your customers ask for it.
Procurement wants to know how you govern your AI. Trampolyne gives you real enforcement and the audit trail to prove it - not a policy document and a promise.
Your AI agent is running in production. You've accepted that it can't be fully deterministic. Trampolyne gives you a deterministic enforcement layer so the model's non-determinism doesn't become your liability.
You need to demonstrate that your organization's AI systems operate within defined boundaries. Trampolyne gives you the controls and the evidence - across GDPR Art. 25, EU AI Act Art. 14, and internal governance frameworks.
New AI regulations require demonstrable controls, human oversight, and documented risk management. Trampolyne is the technical layer that makes compliance attestation credible.
Enforce what your AI can do.
Before it acts on your data.
20 minutes is enough to scope whether Trampolyne fits your production AI stack. Working with a limited number of partners.
Working with a limited number of partners.