Private infrastructure
AI workloads run within infrastructure your organization controls.
Private sovereign AI infrastructure
Your data should stay yours.
So should your AI.
Corsantic deploys private AI infrastructure inside your organization, allowing your team to use powerful AI models without sending sensitive data, client information, or proprietary knowledge to third-party AI APIs.
Own the infrastructure. Control the data. Run AI on your terms.
Your controlled environment
Protected input
Your data
Private compute
AI models
DataModelsCompute
Every AI prompt has to run somewhere
Where is your data going?
When employees send proprietary information, customer data, documents, or internal knowledge to external AI services, that information leaves infrastructure directly controlled by your organization. Private AI changes the path.
Typical cloud AI
Control changes hands
Company data
↓
Public internet
↓
Third-party API
↓
Third-party infrastructure
Your workload is processed in an environment governed and operated by another provider.
Corsantic private AI
Control stays with you
Company data
↓
Your controlled environment
Your infrastructure
↓
AI model
Your sensitive AI workload stays inside the environment your organization controls.
A Canadian imperative
Canada is moving toward sovereign AI.
Canada’s national AI direction identifies domestic compute, operational control, and infrastructure governed by Canadian law as strategic priorities. The federal government has committed more than $2 billion to expand sovereign AI compute capacity.
Corsantic brings that principle inside the enterprise: dedicated AI infrastructure deployed directly into environments organizations control.
Why Corsantic
Control at every layer.
Private AI is more than data residency. It is control over the infrastructure, models, and operating decisions behind every workload.
Data stays under your control
Run sensitive workloads without routing every prompt through an external AI API.
Infrastructure you control
Dedicated compute is deployed within your organization’s environment.
Model independence
Choose leading open models and the right architecture for each workload.
Canadian sovereignty
Build around Canadian organizational, regulatory, and sovereignty requirements.
Lower long-term costs
Reduce reliance on recurring per-token charges for high-volume inference.
From exposure to control
A managed path to private AI.
Map the data
We identify your AI providers, sensitive workflows, data flows, model requirements, privacy considerations, and current costs.
Build the environment
We design, procure, and configure dedicated GPU infrastructure and integrate the right open models into your systems.
Manage the stack
We maintain the software stack, monitor performance, update models, and continuously optimize reliability and economics.
For information-sensitive organizations
When your data matters, control matters.
Patient and clinical information
Privileged client documents
Financial and customer information
Citizen and operational information
Client financial information
Claims and personal information
Confidential client IP
Proprietary code and internal IP
The economics of ownership
Privacy doesn’t have to cost more.
For sufficiently high-volume workloads, locally hosted open models can reduce dependence on recurring proprietary API charges. Cost becomes another reason to take control—not the reason to give it up.
Calculate your AI economics
Potential inference savings
Up to 80–90%
By replacing recurring proprietary API usage with right-sized, locally hosted open models.
Actual savings depend on workload, utilization, model selection, and hardware configuration.The case for private AI
Read the Canadian context.
Primary sources on sovereign compute, organizational accountability, and privacy-protective AI adoption.
Government of Canada
Canada’s National Artificial Intelligence Strategy
Why sovereign compute, data, and infrastructure are becoming foundations of Canada’s AI direction.
Read the strategy ↗ ISED CanadaCanadian Sovereign AI Compute Strategy
Canada’s plan to expand domestic compute capacity and safeguard Canadian data and intellectual property.
Read the strategy ↗ Privacy Commissioner of CanadaPrivacy and Artificial Intelligence
Canadian guidance and regulatory work at the intersection of artificial intelligence and privacy.
Explore the guidance ↗ Canadian privacy regulatorsPrivacy-Protective Generative AI Principles
Responsibilities for collection, use, disclosure, safeguards, accountability, and retention.
Read the principles ↗AI infrastructure assessment
Where does your AI data go today?
Corsantic can assess how your organization uses AI, identify where sensitive information leaves your environment, and determine which workloads could move onto private infrastructure.
Data flowsAI providersAPI usageSensitive workloadsModel requirementsCompute requirementsPrivacy considerationsInfrastructure costs
Canadian-built. Based in Toronto.