Create a New Model
Create one Virtual Model with the rules and security you need.
Define rulesSet securityConfigure routingSave model
Who are you building for?
Actualyze is built for teams who move fast. Drop in one endpoint, get full visibility, and customize model behavior without touching your inference provider, so you ship instead of configure.
Change one URL. Your existing OpenAI SDK calls start flowing through the platform instantly with zero code changes.
Virtual Models are OpenAI SDK compatible. Reach models from every major provider and ship AI features with the workflow you already have.
See every request, latency, and error across all your model calls, before a problem becomes an incident.
Define smart endpoints that route to the right model, mask PII, enforce guardrails, and failover automatically — all from config.
HTTPS everywhere, request filtering, PII masking, and tamper-evident audit logs included from day one.
Track AI spend in one place, and route through cost-optimized Virtual Models so the project stays inside its budget.
One endpoint. Full visibility. Up in minutes — no infrastructure to manage.
Start with a simple workflow that is easy to standardize across your business.
Create one Virtual Model with the rules and security you need.
Create a budget so you and your teams know the cost.
Stage, then launch the model to the Marketplace.
Invite your colleagues to the Marketplace. Share the Virtual Model endpoint. Point your existing apps to the model.
Actualyze gives enterprise platform teams full control without becoming a bottleneck. Distribute authority to teams while maintaining the budget visibility, compliance records, and security posture your organization requires.
Run the full AI lifecycle from one place, integrate model providers, govern access and eliminate shadow AI across your org.
Centralized configuration, role-based access, SSO, RBAC, and policy templates that scale across dozens of teams and thousands of daily requests.
Most decisions resolve at the team level. Platform teams set guardrails; engineering teams work autonomously within them.
Track AI spend by team, budget, and model. Set budgets, trigger alerts, and enforce hard caps before finance gets surprised.
Give engineers a governed marketplace of approved models and apps, so they ship fast without opening shadow AI risk.
See every request, latency, and error across all your model calls, before a problem becomes an incident.
Get started with Actualyze today — the foundation for enterprise AI.
Enterprise Use Cases
Keep AI initiatives moving without losing SOX controls, approval trails, and cost accountability across desks and business units.
Typical Deployments
Outcomes
Run AI workflows that touch patient-adjacent and operational data with PII redaction in the request path, department-scoped policies, and exportable evidence.
Typical Deployments
Outcomes
Support many client-facing teams with different risk tolerances while preserving centralized guardrails and margin visibility.
Typical Deployments
Outcomes
Most teams start with one workflow and then standardize it across business units.
Standardize how teams request, validate, stage, and promote models with compliance sign-off baked into the path.
Apply alerts and hard stops by team and budget before spend drifts into monthly surprises.
Reconstruct who used what model, with which policy, and why a route was selected during incident response.
Keep critical AI paths online by testing fallback routes and preserving policy enforcement during provider outages.