From computing power to a meaningful use.
Your business can benefit from AI in an environment you control. We design architecture around your uses, hardware and confidentiality requirements.
Searching internal documentation, assisting a team or integrating a model into a business tool requires more than a powerful computer. You need to understand the data, access rights, expected answers and operating constraints.
We study local AI, GPU server or private cloud options according to your environment. Sizing depends on the model, number of users and intended tasks. A focused first use helps check answer quality and performance before expanding the solution.
Choose the scenario closest to your needs.
A document assistant can connect a question with passages from accessible documents. We prepare sources, their organization and validation criteria to assess the answers produced.
We examine possible models and available resources. The choice must consider memory, computing, storage and the number of requests to handle.
A private architecture requires defining where data resides, which services communicate and who can use the tools. External dependencies are documented before deployment.
Describe the task and select authorized data for the trial.
Configure the model, search and required access.
Compare expected results with the answers obtained and prepare ongoing operations.
Together, we select what is useful. The quote details the work, required access and any external costs.
Data, users and tasks to test are defined before choosing the architecture.
Answer quality, access and performance are observed on representative cases.
You know the components, dependencies and conditions for developing the solution.
Open a question to learn more.
It depends on the architecture and its integrations. A locally running model can be connected to external services. We inventory flows and dependencies to define what stays in your environment.
Not necessarily. We start with the need and available resources. A trial helps estimate required memory, computing and capacity before investing in hardware.
Yes. Answers need evaluation even when the assistant searches your own documents. Sources, permissions and human validation are part of the operation to prepare.
A private AI project is built around the business’s documents, users and constraints. We support teams in Montréal, on the South Shore and in Montérégie in defining a pilot and comparing hosting options.
Montréal, South Shore and MontérégieDescribe the task, the documents involved and your current environment.
Describe my needsOr call 514 816-0585