AI running on your own server —
your data never leaves your hands
NexAgent deploys AI systems on servers in Vancouver or Greater Vancouver. Customer data stays on your infrastructure, not on a public cloud, and meets Canadian privacy law requirements.
What is private AI deployment?
Private AI deployment means running AI on your own servers or in a Canadian data center — not using shared public cloud services like ChatGPT or Claude's API. Customer files, medical records, and legal documents never leave your infrastructure. For Vancouver law firms, clinics, and financial businesses handling sensitive data, this isn't optional — it's the only compliant approach. NexAgent installs the latest open-source AI models (Llama 3, Mixtral, and others) on your hardware with full encryption, access controls, and a complete audit trail. You own everything — the data, the model configuration, and all outputs.
Private vs. Cloud AI: The Real Difference
Cloud AI services are convenient but create data risks. Private deployment is secure and compliant.
- Limitation
Data Sovereignty
Data leaves your infrastructure
- Limitation
Compliance Risk
PIPEDA, HIPAA concerns
- Limitation
Long-term Cost
$0.01-0.10 per API call (compounding)
- Limitation
Model Customization
Limited to vendor's base model
- Advantage
Data Sovereignty
Data never leaves Vancouver/BC
- Advantage
Compliance Risk
Fully PIPEDA & HIPAA compliant
- Advantage
Long-term Cost
Fixed capex + modest opex
- Advantage
Model Customization
Full fine-tuning and custom training
Private AI Deployment Value
Private AI Deployment Questions
Is private AI deployment difficult to maintain? Do I need an in-house ML team?
No. NexAgent handles deployment, updates, monitoring, and optimization. Our Vancouver-based team provides 24/7 support and proactive management. You don't need internal ML expertise. We provide dashboards and APIs so your existing development team can integrate private AI into applications without becoming MLOps experts. Most clients dedicate 0.5 FTE for support coordination—that's it.
What hardware do I need for private AI deployment in Vancouver?
It depends on model size and query volume. Small models (7B parameters) run on modest GPU servers ($10-20K capex). Larger models (70B+ parameters) require enterprise GPU clusters. We assess your needs and recommend cost-optimal hardware. Many Vancouver businesses co-locate servers in local data centers (like Equinix Vancouver) rather than buying on-site—we help with either approach. Budget typically ranges $15K-$80K for hardware, $2-5K monthly for infrastructure + support.