Enterprise control plane

Govern every AI request from model to GPU lane.

One API for approved models, routing policy, AI Token credits, audit evidence, and GPU-backed capacity.

Request enterprise access View quickstart

Policy

route-time controls

Spend

one AI Token ledger

Capacity

public to reserved lanes

simulated route decision

Governed request trace

policy passed

Models

400+

public + private

Policy

ZDR

route-time controls

Ledger

shared AI Token view

Capacity

GPU

public to reserved

01
Identity & request
enterprise-team · support-prod
Workspace and workload context resolved
matched
02
Policy & route
ZDR + US region · aurona/auto-fast
Approved route selected after policy evaluation
passed
03
Ledger & failover
0.026 modeled credits · approved-only
Spend preview recorded and fallback constrained
armed

Enterprise outcomes

One control plane, shared across every AI buyer.

Aurona connects engineering, security, finance, and capacity planning without forcing each team into a separate operating model.

AI platform teams

Approved model and route access

Ship one integration across teams and environments.

Security teams

Policy evaluated before selection

Review identity, region, provider, and retention intent together.

Finance teams

One modeled AI Token ledger

See workload, route, and capacity exposure in one operating view.

Application builders

Fallback and cost evidence

Package AI features without obscuring route economics.

Regulated workloads

Private and approved-only paths

Make deployment review concrete before production traffic.

Control plane

Configure the workspace, then preview the effective route.

The control room and eligibility lab remain interactive simulations. Regional review checks gateway, inference, and tool execution evidence without changing production access, budgets, policy, or capacity.

Enterprise control room

Budgets, capacity, and policy update together

policy passed

Monthly budget usage

64%

capacity

Serverless endpoint

forecast

$27,392

hard stop

not needed

audit export

ready

data policy

zero retention

approval

auto approve

Policy result

Aurona routes traffic through Serverless endpoint with zero-retention policy and audit logging enabled.

Policy object

{
  "workspace": "enterprise-prod",
  "capacity": "Serverless endpoint",
  "budget_used": 64,
  "data_policy": "zero_retention_required",
  "audit_export": true,
  "fallback": "approved_only"
}

Simulated route eligibility

Preview the effective policy before traffic runs.

Combine workspace, member, and API-key scope with AI Token budget, retention preference, regional execution evidence, and GPU capacity readiness. This lab is planning data, not an active security, residency, retention, or production route guarantee.

route eligible

Member policyAPI-key policy

AI Token budget used · 58% of 80% preview ceiling

Retention preference

Regional execution evidence

Regional review requires aligned gateway processing, model inference, and tool execution evidence.

Capacity preference

effective pool

2 routes

selected

aurona/private-reasoning

fallback

aurona/northstar-balanced

Ordered decision trace

01Scope intersection2 providers remain across workspace, member, and API-key policy.passed

02Retention preference2 simulated zero-retention routes remain.passed

03Region execution pathNo regional constraint is applied; route evidence remains planning-only.passed

04Capacity readinessShared, serverless, and dedicated capacity may remain eligible.passed

05AI Token budget22% of the simulated budget window remains.passed

Eligibility receipt

proposed planning response · simulated

{
  "simulated": true,
  "workspace": "enterprise-prod",
  "effectiveProviders": [
    "aurona-core",
    "northstar"
  ],
  "eligibleRouteIds": [
    "aurona/private-reasoning",
    "aurona/northstar-balanced"
  ],
  "selectedRoute": "aurona/private-reasoning",
  "fallbackRoute": "aurona/northstar-balanced",
  "retention": "Zero-retention preferred",
  "capacity": "Any approved",
  "executionRegion": "Any reviewed",
  "budgetUsed": 58,
  "budgetLimit": 80,
  "budgetRemaining": 22,
  "status": "eligible"
}

Simulated workspace change

See the impact before a policy is assigned.

Preview which keys, private apps, route aliases, and capacity paths would need review. Nothing here changes access, budgets, retention, credentials, or GPU allocation.

hold for review

Provider scopeBudget proposal

Capacity scope

checked

affected

keys

apps + routes

Object	Route	Capacity	Impact
key_prod_support API key	aurona/auto-fast	Serverless	unchanged no effective change
key_private_research API key	aurona/private-reasoning	Dedicated GPU	unchanged no effective change
app_case_digest Private app	aurona/fusion	Serverless	unchanged no effective change
route_value_batch Route alias	aurona/ember-value	Shared pool	review provider_removed

Change-impact receipt

proposed planning response · simulated

{
  "simulated": true,
  "workspace": "enterprise-prod",
  "changeSet": {
    "allowedProviders": [
      "aurona-core",
      "northstar"
    ],
    "budgetChange": "unchanged",
    "capacity": "Any approved"
  },
  "status": "hold_for_review",
  "affectedObjects": [
    {
      "id": "route_value_batch",
      "kind": "Route alias",
      "reasons": [
        "provider_removed"
      ]
    }
  ],
  "action": "hold_for_owner_review"
}

Governance and spend

Policy evidence and AI Token exposure, reviewed together.

These panels use simulated enterprise data to show the operating model. They are not billing records, security guarantees, or contractual limits.

Policy engine

Request-time control objects

simulated

Identity

SAML SSO, domain rules, workspace roles

team · app · environment

Access

model allowlists, route permissions, app catalogs

model · route · provider

Data

retention preference, region pinning, vendor restrictions

request · log · output

Rules

priority matching, block, mask, warn, reroute, review

prompt · response · app

Budget

credit caps, alerts, commitments, review holds

team · workload · route

Audit

request trace, policy action, token ledger, export

security · engineering · finance

AI Token ledger

Modeled workload exposure

preview

Customer support

12.4K modeled credits

84% · within plan

aurona/auto-fast

Code agents

8.96K modeled credits

71% · within plan

aurona/fusion-code

Research workflows

5.28K modeled credits

53% · within plan

aurona/fusion

Private analytics

3.72K modeled credits

62% · review

aurona/fusion-private

Trust workflows

Make enterprise review concrete before production traffic.

Aurona presents policy configuration and review evidence in one place while keeping legal, security, and retention approval with the customer.

Retention policy

Route only through provider and private-lane choices that match configured workspace intent.

Regional routing

Pin modeled route options and logging scope to approved regions during planning review.

Audit export

Review route decisions, spend evidence, provider selection, and policy results together.

Environment separation

Keep development, staging, production, and sensitive workloads on distinct keys and budgets.

Vendor review

Prepare provider, access, data-flow, and control evidence for security and procurement teams.

Workload attribution

Connect modeled cost and capacity evidence to a workspace, application, team, or route.

Capacity maturity

Grow from public models to a reserved GPU lane.

Each stage is a planning path, not a capacity or performance commitment. Keep the application contract stable while workload evidence matures.

01
Public provider pool
Managed model access
experiments + general production
02
Serverless endpoints
Elastic GPU-backed inference
bursty apps + evaluation jobs
03
Preferred lanes
Provider and model priority
scaled customer-facing workloads
04
BYO capacity
Contract and meter mapping
existing vendor commitments
05
Reserved GPU lane
Private capacity planning
sustained or sensitive workloads

Procurement

A review packet for technical and commercial teams.

The surfaces below describe review workflows and modeled evidence; they do not create contractual terms.

Commercial

Modeled credit structure, invoicing workflow, payment controls, and usage reporting.

preview package

Reliability

Health evidence, incident workflow, fallback behavior, and support-path review.

preview package

Implementation

Quickstart, routing guide, migration examples, and solution-design review.

preview package

Security review

Policy configuration, audit exports, access controls, and vendor-review notes.

preview package

Implementation path

From first API call to governed production.

Read implementation docs

01
Connect
Move an OpenAI-compatible call behind an Aurona workspace key.
02
Map policy
Define approved providers, region intent, budgets, aliases, and fallback.
03
Launch route
Use an exact model, Auto route, Fusion panel, or private lane preview.
04
Review telemetry
Inspect route evidence, spend, latency, provider health, and fallback events.
05
Plan capacity
Model committed credits or reserved capacity after workload evidence exists.

Aurona Enterprise

Plan governed AI access, credits, routes, and capacity in one control plane.

Start enterprise review

Govern every AI request from model to GPU lane.

Governed request trace

One control plane, shared across every AI buyer.

Approved model and route access

Policy evaluated before selection

One modeled AI Token ledger

Fallback and cost evidence

Private and approved-only paths

Configure the workspace, then preview the effective route.

Budgets, capacity, and policy update together

Preview the effective policy before traffic runs.

See the impact before a policy is assigned.

Policy evidence and AI Token exposure, reviewed together.

Request-time control objects

Modeled workload exposure

Make enterprise review concrete before production traffic.

Retention policy

Regional routing

Audit export

Environment separation

Vendor review

Workload attribution

Grow from public models to a reserved GPU lane.

Public provider pool

Serverless endpoints

Preferred lanes

BYO capacity

Reserved GPU lane

A review packet for technical and commercial teams.

Commercial

Reliability

Implementation

Security review

From first API call to governed production.

Connect

Map policy

Launch route

Review telemetry

Plan capacity

Plan governed AI access, credits, routes, and capacity in one control plane.