Monitor Local LLMs (Ollama, LM Studio)
usage at work.
PromptGlass finds local model runtimes such as Ollama and LM Studio on managed endpoints, inventories which models are installed, and records usage, so shadow AI that never touches the network is still visible.
Local LLMs (Ollama, LM Studio)
Models running on laptops and workstations, outside network controls.
What PromptGlass sees
- ✓Installed runtimes and model files
- ✓Running local API endpoints
- ✓Usage by user and device
- ✓Model license and provenance flags
Captured by
Why it matters
The Local LLMs (Ollama, LM Studio) questions security and finance ask
Network controls cannot see models that run entirely on the device.
Downloaded model weights have unknown provenance and licenses.
Local AI tools may expose local APIs on the network.
How Various handles data you send to Local LLMs (Ollama, LM Studio) depends on your plan and their current terms. Review them directly. PromptGlass controls what leaves your organization, whatever plan you are on.
Three steps
From Local LLMs (Ollama, LM Studio) blind spot to governed tool
- 1
Discover
See every user of Local LLMs (Ollama, LM Studio), which account type they use, and how often, from day one.
- 2
Protect
Turn on detectors for the data you care about and coach, redact or block it in Local LLMs (Ollama, LM Studio) prompts and uploads.
- 3
Optimize
Compare Local LLMs (Ollama, LM Studio) adoption and cost with the other AI tools in use, and right-size licenses and models.
Monitoring Local LLMs (Ollama, LM Studio): FAQ
How do I monitor Local LLMs (Ollama, LM Studio) usage in my company?
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Deploy one of the PromptGlass sensors that supports Local LLMs (Ollama, LM Studio): Endpoint agent. Usage is tied to people and teams through your identity provider and shown in the PromptGlass console within hours.
Can PromptGlass stop sensitive data being shared with Local LLMs (Ollama, LM Studio)?
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Yes. PromptGlass inspects prompts and uploads to Local LLMs (Ollama, LM Studio) for personal data, health data, card numbers, secrets, source code and your own custom terms, then allows, coaches, redacts or blocks according to policy.
Why do local models matter for AI governance?
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They avoid every network control. Data may stay on the device, but licensing, provenance and acceptable-use rules still apply, and the endpoint agent is the only practical way to see them.
Does PromptGlass work with Local LLMs (Ollama, LM Studio) if we self-host?
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Yes. Every sensor reports to PromptGlass Cloud or to a self-hosted PromptGlass deployment on your own Kubernetes cluster, including air-gapped environments.
Monitor other AI tools
Local LLMs (Ollama, LM Studio) is a trademark of its respective owners. PromptGlass is not affiliated with or endorsed by them.
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