Enterprise LLM Foundation
Govern AI use across the three to seven models already in play.
An acceptable-use policy, DLP and compliance integration, and a multi-LLM governance framework, so employees can use AI productively and the organization can prove that use is safe, controlled, and auditable.
We have several AI tools in use. How do we know our data isn't walking out the door?
Most organizations are already running three to seven models across teams, with no shared policy and no visibility into what data goes where. In life sciences that is a compliance exposure, not just an IT one. This project sets the rules, wires the data-loss controls, and gives you one governance framework across every model in play.
Scope
What's included
AI acceptable-use policy
A clear, practical acceptable-use policy that tells employees what is allowed, what is not, and why, written to be followed.
DLP and compliance integration
Data-loss-prevention and compliance controls wired into AI usage, so sensitive and regulated data is protected at the point of use.
Multi-LLM governance framework
One governance framework spanning the three to seven models in play, so policy and oversight don't fragment per tool.
Auditability
The visibility and audit trail to show, to leadership or a regulator, how AI is being used and controlled.
How it works
From kickoff to handoff
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Set the policy
We write a practical acceptable-use policy grounded in how your teams actually work.
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Wire the controls
We integrate DLP and compliance controls so data is protected at the point of use.
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Unify governance
We build one framework across the models in play, with the audit trail to prove it.
Outcomes
What you walk away with
- A practical acceptable-use policy employees can follow
- DLP and compliance controls protecting data at the point of use
- One governance framework across every model in play
- The auditability a regulated life sciences setting requires
Questions
Frequently asked
We don't even know which tools are in use. Can you help?
Yes. Part of the work is inventorying the models actually in play, often more than leadership expects, and bringing them under one framework rather than pretending there's only one.
Does this slow our team down?
Done well, it speeds them up: a clear sanctioned path plus protected defaults removes the hesitation and the risk, so people use AI confidently instead of secretly.