Pricing / Transparent starting points
Private AI economics depend on workload, infrastructure, integrations, security, availability, and organizational scale. Pricing begins with an assessment that defines those variables.
AI Infrastructure Assessment
From $25,000A paid assessment that evaluates priority use cases, workflow requirements, model performance, current AI costs, ROI and payback, data and integrations, security, architecture, hardware, schedule, and production acceptance criteria.
Typical duration: two to three weeks.
Private enterprise AI implementation
$250,000–$500,000+A typical implementation range—not a fixed package price. A fixed implementation proposal is produced after assessment based on the approved architecture, integrations, controls, workflows, and organizational scope.
Scoped separately and prepaid. The bill of materials is developed from workload and production requirements.
Scoped separately according to infrastructure, service levels, model maintenance, workflow requirements, and support scope.
What shapes the range
The assessment converts the major cost drivers into a technical plan, economic model, delivery schedule, acceptance criteria, and fixed implementation proposal.
Compute, network, hosting model, capacity, concurrency, availability, backup, and recovery requirements.
The number and complexity of enterprise systems, data sources, identity providers, repositories, and internal APIs.
Identity, permissions, isolation, logging, retention, approval, escalation, and administrative controls.
The quantity, complexity, risk, and acceptance requirements of the tools and agents being implemented.
Users, business units, entities, locations, enablement needs, and operating responsibilities.
Delivery timing, availability targets, operational support, maintenance, and response requirements.
Economic evaluation
A private deployment may reduce or replace some per-user AI subscription costs for the workflows it covers. It may also create value through deeper customization, enterprise integration, data control, governed automation, and model choice.
Savings are not guaranteed. The economic case depends on user count, utilization, model requirements, subscription costs, infrastructure, operating support, and the value of the workflows being supported.
Transparent first step
The assessment establishes technical feasibility and a fixed implementation proposal before you commit to infrastructure or a production build.
Schedule an AI Infrastructure Assessment