Enterprise LLM Foundation
Give your people enterprise AI, on your terms, actually used.
Provision governed enterprise LLM access for employees, ChatGPT Enterprise, Claude, Copilot, or Gemini, with SSO and access control, plus the adoption and enablement that turns licenses into daily, productive use.
Our people use AI on personal accounts with our data in the prompt. How do we give them a safe, sanctioned option?
Shadow AI is the default when there's no sanctioned tool: employees paste company data into consumer chatbots because it helps them work. This project gives the organization a governed enterprise option, provisioned with SSO and access control, and drives real adoption so people actually move off the unsafe path.
Scope
What's included
Enterprise LLM setup
A governed enterprise LLM (ChatGPT Enterprise, Claude, Copilot, or Gemini) set up for your organization, with data handling configured for life sciences.
SSO and access
Single sign-on and access control, so the right people have the right access and provisioning scales cleanly.
Adoption and enablement
Enablement that turns licenses into real use: role-specific guidance, examples, and onboarding so AI becomes part of how the team works.
A sanctioned default
A safe, productive AI option that pulls people off personal accounts and shadow tools.
How it works
From kickoff to handoff
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Provision
We set up the enterprise LLM with the data-handling and access configuration your environment needs.
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Connect SSO
We wire single sign-on and access control so provisioning scales and stays governed.
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Drive adoption
We enable the team with role-specific guidance so the licenses get used.
Outcomes
What you walk away with
- Governed enterprise LLM access with data handling configured
- SSO and access control that scales cleanly
- Real adoption, not licenses nobody opens
- A sanctioned default that displaces shadow AI
Questions
Frequently asked
Which model should we provision?
It depends on your stack, your data posture, and your use cases. We are model-agnostic and will recommend and provision the enterprise LLM, or mix, that fits, often as part of an AI Readiness Audit.
What about governing how it's used?
Provisioning is access; governance is control. LLM Usage Governance adds the acceptable-use policy, DLP, and multi-model framework that keep usage safe and auditable.