As an MSP, you’re already managing a robust security stack. Web filtering, DNS security, endpoint protection, and application control all solve important problems. But those tools weren’t designed to answer the questions that AI introduces:
- Which AI tools are employees actually using?
- What information are they sharing?
- Which applications has the client approved?
- Where should the client be concerned about data exfiltration?
- And what should happen when an employee uses a tool that falls somewhere between fully sanctioned and explicitly blocked?
Traditional controls only see the application
Traditional security controls are often built around a binary decision: allow an application or block it. That model does not translate cleanly to AI. ChatGPT, Claude, and other popular AI tools are increasingly useful parts of everyday work, and simply blocking access creates friction without solving the underlying governance problem.
MSPs should not have to become the “Department of No.” AI governance requires policies that reflect those distinctions rather than treating every interaction as a simple allow-or-block decision.
Longwave gives MSPs a way to apply different policies to different AI tools, monitor how they are being used, and apply safeguards around that usage. Your goal shouldn’t be to prevent employees from using the AI tools they use at home. It’s to give them a safer, governed, sanctioned way to use these tools in the workplace.
AI policy needs an enforcement layer
Longwave gives MSPs a purpose-built policy framework for AI. Applications can be classified as Approved, Unapproved, or Blocked, with controls applied according to the client’s policy.
MSPs gain visibility into users, AI tools, prompt activity, policy violations, and sensitive-data exposure across supported browser and desktop environments. The result is a governance layer built around the way employees actually interact with AI.
Longwave complements the security stack you already manage
Longwave doesn’t replace endpoint security, web filtering, or traditional DLP. It fills the gap those products were not built to address: understanding and governing AI usage itself.
Continue operating the security stack you already trust while adding the visibility, policy controls, and reporting required to manage AI as a distinct part of the client environment.
Ongoing governance creates recurring value
AI usage isn’t standing still. New tools are appearing, employee behavior is changing, and client policies need to evolve.
Longwave gives MSPs something concrete to monitor, review, and report on over time, from new applications and policy violations to sensitive-data exposure and changes in usage. Clients can see that governance is actively being managed rather than treated as a one-time assessment. That ongoing client value is what makes AI governance a durable managed service, and a recurring revenue opportunity for the MSP.