Already using Claude or Copilot? Move sensitive workflows into a controlled AI layer.
Northwood helps teams identify where general-purpose AI tools are enough — and where proprietary, repeatable workflows need a private, model-portable deployment your organization can control.
Starting pointExisting AI tools
OutcomeControlled deployment layer
MigrationWorkflow by workflow
Where to draw the line between general-purpose and controlled deployment.
General-purpose AI tools can be useful for broad access. Northwood focuses on the workflows where your organization needs more control: proprietary knowledge, repeatable processes, deployment flexibility, permissions, evals, and auditability.
General-purpose AI tools are useful for
·Broad internal access and general Q&A
·Drafting and editing without sensitive context
·Individual productivity workflows
·Public or non-proprietary knowledge tasks
A controlled deployment layer is needed for
↗Workflows that touch proprietary research, code, or customer context
↗Repeatable processes that need auditability and eval coverage
↗Knowledge that cannot appear in third-party logs or training data
↗Workflows where you need to own the infrastructure, model, and deployment
What Northwood helps with
↗Evaluate which workflows should stay in your current AI tools
↗Identify workflows that need a private, controlled deployment layer
↗Define the model strategy, infrastructure path, and permissions model
↗Deploy the first controlled workflow into your own environment
↗Add evals, audit logs, and monitoring for production use
↗Operate and expand the deployment as new workflows are added
Move your most sensitive workflows into a deployment you own.
If your team has already adopted an enterprise AI platform, Northwood can help evaluate which workflows should stay there and which should move into a dedicated workflow layer with stronger control, auditability, and deployment flexibility.