Enterprise AI
Adoption, architecture, governance and controls for organizations bringing AI into daily work faster than their policy can keep up.
AI Shadow Usage Discovery
Inventory every AI tool in use across the organization — sanctioned and unsanctioned.
Enterprise AI Architecture Design
Design the right enterprise AI control stack for the organization — which gateway, which models, which end-user interface, how access control integrates with the existing IdP, and how costs are allocated.
AI Gateway Deployment
Design and deploy an enterprise AI gateway that sits between users and every LLM provider.
Claude for Work / Enterprise Deployment
Full enterprise deployment of Claude — SSO configuration (SAML 2.0 / OIDC with Okta, Entra ID, Google Workspace), domain capture to prevent personal account use.
AI Cost Governance & Model Routing
Budget envelopes per team and per project, alerts before a hard limit is reached, routing rules that send lower-priority requests to cheaper models, and spend reported back to finance by team.
AI Data Loss Prevention & Guardrails
Configure guardrails on the AI gateway to prevent sensitive data from reaching external models.
AI Audit Logging & Observability
Every request captured with the identity behind it, the model, the cost and the response, routed into the log store you already keep, so the audit trail exists before anyone asks for it.
Self-Hosted AI Interface Deployment
Deploy a self-hosted, branded AI interface that routes through the enterprise gateway, so users get a familiar chat experience and their data stays inside the organization's boundary.
Managed Enterprise AI Program
Ongoing AI governance — cost and usage reporting by team, new tool evaluation and risk scoring, policy updates as new models and capabilities launch, quarterly access control review.
AI Vendor Risk Assessment
Structured risk assessment of AI vendors and tools being evaluated or already in use.