OLEV provides an enterprise‑grade platform that invisibly instruments local development environments to capture AI‑related telemetry such as file accesses, tool usage, and user actions. The data is automatically turned into client‑facing compliance reports and zero‑noise alerts, enabling firms to demonstrate IP protection and meet audit requirements without disrupting developer workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises deploying AI models struggle to demonstrate compliance and protect intellectual property because AI-generated code and data usage are difficult to monitor, especially in sensitive client repositories. Traditional security tools often require heavy cloud permissions or disrupt developer workflows, leading to gaps in visibility and increased risk of data leaks.
Solution
OLEV offers an enterprise‑grade platform that continuously instruments local development environments with low‑overhead, invisible monitoring. It captures raw AI telemetry—such as file accesses, AI tool usage, and user context—and automatically converts this data into client‑facing compliance reports that can be attached to RFPs or audit submissions. The system delivers zero‑noise alerts that pinpoint the exact file, tool, and user involved in a security event the moment it occurs, allowing rapid response without slowing developers. By mapping AI activity directly to teams, OLEV enables organizations to enforce strict client compliance while maintaining developer velocity.
Target Audience
Primary customers are enterprise software firms and consulting agencies that develop AI‑enabled solutions for high‑value clients and need to prove data security and compliance to win contracts.
Features
- Invisible, low‑overhead instrumentation deployed only on sensitive client repositories, avoiding workflow disruption
- Real‑time, zero‑noise alerts with full developer context (file, AI tool, user) for immediate incident triage
- Automated translation of raw AI telemetry into polished, client‑ready compliance reports for RFPs and audits
- Comprehensive mapping of AI IDE usage across local machines to attribute activity to specific team members
- Fine‑grained monitoring focused on “crown‑jewel” assets, reducing noise and preserving performance