On-premises AI & private deployment
Local AI Toronto.
Your infrastructure.
Explore on-premises AI solutions and private AI deployment with WEBSITETOON. Choose where your models run and how your business data is handled.
Keep control of your deployment
Local AI: your data, your decisions.
Cloud AI can be useful, but it is not the only deployment option. For sensitive records, proprietary research, and internal workflows, on-premises AI gives your team more control over where processing happens.Our local AI lab develops and deploys solutions around your environment. Model choice, integrations, access controls, and operational practices all affect privacy, quality, and performance.Local deployment can support your data-governance goals; it does not automatically establish PIPEDA, PHIPA, or other regulatory compliance.Our local AI solutions
Build around the work that matters.
Start with a useful business problem, then choose the model, hardware, and integration that fit.01
Private LLM deployment
Run selected language models on your infrastructure. Explore document search, knowledge assistants, and applications using models such as Llama and Mistral.02
On-premises AI assistants
Build assistants around business knowledge and workflows, with access controls and data handling designed for your environment.03
Document processing
Analyze, extract, and classify information from documents within a locally managed processing environment.04
Private AI code assistants
Evaluate coding assistance that works with your codebase and keeps deployment under your team’s control.05
On-premises computer vision
Explore local image recognition, object detection, and visual inspection for appropriate business use cases.06
AI infrastructure design
Plan hardware, model selection, optimization, capacity, and ongoing operations around the workloads you need.07
Model fine-tuning & customization
Adapt suitable models to your terminology and use cases, with data preparation, evaluation, and training scope agreed in advance.Local AI vs cloud AI
Choose the tradeoffs—not the hype.
The right choice depends on your workloads, data policies, resources, and operational needs.| Consideration | Local AI | Cloud AI |
|---|---|---|
| Data handling | Managed within your chosen environment; integrations need review. | Depends on provider terms, settings, and regional availability. |
| Costs | Hardware, energy, maintenance, staffing, and deployment. | Usage fees or subscriptions, plus integration costs. |
| Performance | Depends on model, hardware, and workload. | Depends on service, network, model, and workload. |
| Offline operation | Possible when all required dependencies are local. | Hosted services generally require connectivity. |
| Customization | Depends on model licensing and available resources. | Depends on provider features and restrictions. |
| Privacy & compliance | Your team controls deployment and must implement appropriate safeguards. | Provider controls and contracts must be assessed for your requirements. |
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Why WEBSITETOON
Research, deployment, and business context.
Our local AI lab and proprietary tools support a practical approach to on-premises AI—from model selection and customization to infrastructure planning.Across WEBSITETOON, we have served 2,000 businesses and operate from three locations. Leading Canadian companies, regulatory bodies, and cities choose our company.WEBSITETOON is led by an ISO member (membership, not ISO certification).Frequently asked questions