Enterprise AI infrastructure and governance provider

Lower the total cost of enterprise AI. Turn every investment into measurable value.

Connect global cloud and local models through one governed foundation. Reduce duplicated procurement, attribute spend, manage data risk, and run enterprise Agents on AIPay AgentOS.

Build governed AI infrastructure. Evolve into an AI-native enterprise.

Global models

Local models

Governance control plane
Identity
Cost & value
Security audit
Employees
Business systems
AgentOS

The enterprise does not need another disconnected AI tool

It needs an operating foundation that can run AI continuously, control cost, and explain value.

01

Duplicate procurement

Teams purchase overlapping capability while capacity sits idle.

02

Unattributed spend

Invoices exist, but ownership, purpose, and outcomes remain unclear.

03

Data exposure

Sensitive contracts, customer data, and code may reach models without policy controls.

04

AI stays individual

Tools remain personal productivity aids instead of governed operating infrastructure.

Start with cost

Understand total AI cost before changing the operating model

The calculator establishes a discussion baseline and does not promise savings or ROI.

Enterprise AI cost review

Build a first monthly cost baseline from current inputs

people
USD
%
USD
hours
USD

Current monthly cost structure

$1,610

Subscriptions$750
API usage$500
Administration$360
Potential idle subscriptions$263
Priority review amount

$623

Estimated from potential idle subscriptions and administration time. This is not a savings guarantee.

Discuss these results

From fragmented usage to governed enterprise AI infrastructure

01

Unify access

Connect global and local models through a governed catalog and individual identities.

02

Govern resources

Manage access, budgets, quotas, and model routing in one operating layer.

03

Audit usage

Apply detection, masking, blocking, alerting, and traceability controls.

04

Run Agents

Connect knowledge, tools, and systems on AgentOS with approvals and exception handling.

AgentOS

Bring Agents into real enterprise workflows

Connect enterprise knowledge, data, tools, and systems while governing Agent identity, access, model calls, cost, human approvals, and execution history.

  • Independent identity and ownership for every Agent
  • Human approval for critical actions
  • Execution records for model and tool calls
  • Cost and exceptions in one governance view
Explore AgentOS
Knowledge
Business data
Tools
AgentOS
Identity
Approval
Cost tracking

Deployment

Balance control, launch speed, and workload placement

Control first

On-premises

Run inside enterprise infrastructure. The enterprise owns operations and data while AIPay provides deployment and contracted support.

View deployment
Speed first

AIPay managed

AIPay operates the environment and upgrades while enterprise administrators govern users, policy, budgets, and reporting.

View deployment
Place each workload

Hybrid

Keep sensitive workloads and local models inside while connecting suitable global capabilities by policy.

View deployment

Standard services

Start with a clearly bounded service

Standard services are priced in USD and support USDT on TRON. Deployment and custom Agent work begin with scope and quotation.

Enterprise AI Cost Diagnostic

Establish a practical cost baseline before changing tools, contracts, or architecture.

$25

2 business days

View delivery and payment
Recommended starting point

Team AI Pilot Launch

Launch a focused 14-day pilot with clear operating rules and a measurable review.

$110

14 days, up to 20 participants

View delivery and payment

Training and Support Pack

Add structured enablement, configuration guidance, and review sessions to an active AI initiative.

$220

4 remote sessions within 30 days

View delivery and payment

From paying for AI to making AI pay off

Use one architecture conversation to identify the highest-value next step

Bring your team size, current models and tools, and primary cost or risk concern. We will use them to frame an appropriate governance and deployment path.

Talk to an AI Architect