"We lost a large enterprise deal because we couldn't clear their security review. That was a wake-up call. We brought in Trampolyne AI and within weeks, the picture changed completely."
CEO, AI-native SaaS companyFor AI builders
You built the AI product. Now client's security review is blocking the deal.
Enterprise customers want a security review your team was never set up to pass. Trampolyne enables you to be ready with enterprise-grade security for core set-up, governance systems for continuous control and with evidence to prove it.
The situation
The deal is good. The product is ready. Security review is the blocker.
This is one of the most common ways AI-native SaaS companies lose enterprise revenue. Not on product fit. Not on price. On a security questionnaire they couldn't answer.
The questionnaire arrives
Enterprise procurement sends a 60-question security review. Most questions are about data handling, access control, audit logging and AI-specific risk. You have partial answers at best.
Generic tools don't help
SOC 2 reports cover infrastructure. Pen tests cover traditional attack surfaces. Neither speaks to AI-specific risk: prompt injection, data leakage via LLMs or agent scope violations.
The deal stalls or dies
Without a credible AI security report, the enterprise security team flags the engagement. Legal and compliance get involved. Timeline slips from weeks to quarters.
What we do
Two things that directly unstall the deal
Not a generic security assessment. Work that maps directly to what enterprise procurement asks for.
AI Red-Teaming report
We run automated, multi-turn adversarial testing against your AI system using real attack scenarios from your business context - not generic templates.
Attack types covered include model level (example: prompt injection, role escalation, tool misuse, jailbreaks) and system level (example: data exfiltration, privilege escalation, lateral movement).
Output: severity-ranked findings with OWASP LLM Top 10, OWASP Agent Top 10, MITRE ATLAS mapping, exploitability evidence, and remediation steps - formatted for enterprise security review.
See how it works →Runtime governance evidence
We deploy an inline enforcement layer between your users and your AI. Every request is policy-checked before execution. Every decision is logged with full audit trail.
What you get: auditable enforcement logs you can share with customers, proof that your AI cannot access data it should not access and policy version history for review.
Governance models supported: RBAC, ABAC, PBAC. Setup typically starts with a 20-minute call.
See how it works →What changes after
You go into the next security review with answers, not apologies
The shift from "we'll follow up" to "here is the report" changes how enterprise procurement sees you.
Answer every AI security question
Red-team findings map directly to OWASP LLM Top 10, OWASP Agent Top 10 and MITRE ATLAS. You have evidence, not assurances.
Show ongoing controls, not one-time scans
Runtime enforcement logs demonstrate that governance is live and
continuous - not just a point-in-time audit. This matters to
enterprise legal and compliance reviewers.
Compress security review timelines
Procurement cycles that stall for months on AI security
questions move faster when you can submit a credible report on
day one of review.
From design partners
This has unblocked real deals
"What really set them apart was unblocking large enterprise contracts for us. When enterprises came with rigorous security questionnaires, the team helped us answer every single one with confidence, backed by real evidence."
SaaS company building AI-native LMSHave a deal stalling right now?
20 minutes is enough to understand whether we can help and how fast. We work with a small number of design partners. Response within 1–2 business days.