Govern AI usage like an enterprise asset
From a single account to an entire enterprise — identity, permissions, budget, guardrails, and audit, unified. Teams stay in control, usage stays transparent.
AI for teams, all under control
Not a pile of scattered API keys — a unified governance control plane.
Enterprise, workspace & roles
Enterprise / workspace / API key structure — Owner, Admin, Member, and workspace owner responsibilities are clearly defined.
Members & permissions
Invite members by email, assign roles, and authorize workspace access.
Member & API key budgets
Set budget caps for members and API keys — over-limit calls are blocked according to the configured guardrails.
Safety & prompt guardrails
Combine model blocklists, IP allowlists, budgets, and prompt-injection detection at the workspace and API key levels.
Policy-based model control
Configure model access and budget policies per workspace or API key — keep calls within the configured scope.
Usage & call logs
Review requests, Token usage, spend, and status by workspace, model, member, and API key.
Three dimensions. Every boundary clear.
ModelGo's enterprise permission model works across three independent dimensions — identity tier, role assignment, and policy control. Each layer is judged separately so access is always precise and auditable.
Enterprise & workspace structure
Create workspaces under one enterprise account. Each workspace manages its members, budgets, API keys, and logging settings.
Role Assignment
Owner and Admin manage the enterprise. Members work within authorized workspaces, while workspace owners manage resources in the workspaces they are responsible for.
Policy Control
Global guardrails protect a workspace. Member guardrails set personal budgets; API key guardrails can inherit or configure model, IP, budget, and prompt-injection policies.
Your content. You decide what gets logged.
Request and response content is available only when workspace I/O logging is enabled. Log forwarding is configured separately.
Usage at a glance, drillable to every call.
The console aggregates requests, Token usage, and spend by workspace, model, member, and API key, with call logs for request-level investigation.
Auditable · Traceable · Reconcilable
Audit & security
Critical management changes are recorded in the audit log.
Billing records & reconciliation
Usage and billing records support workspace-level review and reconciliation.
You control how data is recorded and flows
Data control
Input and output content is shown only when workspace I/O logging is enabled. External forwarding is configured separately.
Secure key storage
API keys stored as digests only — redacted in lists, revocation is instant.
Credential encryption
Sensitive credentials encrypted at rest — forwarding endpoints verified to prevent SSRF.
Designed for ongoing operations, not just the first call
Beyond model access — covering the daily cycle of config, usage, reconciliation, and audit.
Configure
Create workspaces, assign budgets, and configure model access and API keys.
Monitor usage
Track spend and Token usage across workspaces, models, members, and API keys.
Reconcile
Review usage and billing records by workspace, model, member, and API key.
Audit
Critical operations fully logged and traceable.
Bring AI into enterprise procurement and governance
AI product / SaaS teams
Embed AI across multiple workspaces — set workspace budgets, review billing records, and keep spend visible.
Internal automation teams
Roll out AI in finance, support, and ops — budgets, audit logs, and model governance keep usage controlled.
Developer / tool platforms
Expose AI to downstream applications through a unified API, with workspace isolation, guardrails, and budget controls.
High-concurrency teams
Usage views and call logs help teams monitor high-frequency workloads.
A permission system that grows with your team
Use solo, or create an enterprise account when ready — add workspaces, invite members, and assign roles. Keep access and usage boundaries clear as your team grows.