Azure AI Foundry Implementation Company in Montreal

QServices is not headquartered in Montreal, but we build Azure AI Foundry applications for Quebec companies in AI research, pharma, aerospace, and gaming on remote engagements with roughly four hours of daily overlap with Eastern Time. QServices is a remote-first software consultancy serving Montreal and Quebec businesses on Microsoft Azure.

What Montreal buyers typically need from Azure AI Foundry

Montreal's technology sector spans AI research, aerospace, pharma, and gaming with distinct requirements for each vertical. Based on the engagements we run for clients in similar markets, the most common project types look like this.

• AI research to production: Montreal is one of Canada's leading AI research centres. Organizations here frequently need Azure AI Foundry to move experimental models into production with proper evaluation harnesses and observability rather than raw API calls.
• Pharma document intelligence: Life sciences companies in Quebec need AI systems that can query regulatory filings, clinical data, and internal knowledge bases. Quebec's Law 25 (Act respecting the protection of personal information in the private sector, as modernized in 2022) requires privacy impact assessments, data minimization practices, and explicit consent flows for any AI system handling personal information. This is a real design constraint we account for in scoping, not a box to check after delivery.
• Aerospace project coordination: Aerospace firms managing multi-team, multi-vendor programs benefit from AI assistants that surface relevant engineering documentation and integrate with project management tools, similar to what we built for the Smart PM case study below.
• Gaming and interactive content: Montreal's studios are exploring AI-assisted content systems where Azure AI Foundry's built-in safety and evaluation layers matter for keeping outputs within acceptable bounds.

Law 25 compliance affects the architecture of any Montreal project that touches personal data. We document the data flow, identify which Azure regions store what, and produce the privacy impact assessment artifact your legal team needs before go-live.

How we work with Montreal clients

Our delivery team is in India. Montreal runs on Eastern Time, which puts us 9.5 to 10.5 hours ahead depending on daylight saving. The practical overlap window is 8:00 AM to 12:00 PM ET daily, when our team is in late afternoon IST. We treat that window as the time for standups, design reviews, and anything that genuinely requires a synchronous decision.

The rest of the day is async. We default to Microsoft Teams for communication since most of our clients are already on the Microsoft stack. Decisions are documented in writing so nothing depends on a follow-up call. Code reviews happen in GitHub pull requests with written commentary, not verbal walkthroughs. Sprint demos are recorded and posted within the hour for stakeholders in different schedules.

For projects above approximately CAD $80,000, or when the client requests it, we are open to milestone visits for kickoff workshops or user acceptance testing. We have not built a Montreal office and will not claim otherwise. What we have is a delivery process refined over 15 years of remote engagements that does not require co-location to produce working software.

Relevant work in similar markets

We have not delivered a project specifically for a Montreal client. The two Azure AI Foundry engagements we have completed both came from enterprise software companies. Neither was in aerospace or pharma directly. We will be straightforward about that.

For an IT services company, we built an AI project management assistant using Azure AI Foundry, Azure AI Search, Power Automate, MS Teams, Microsoft Graph API, and the Azure DevOps API. The system captured meeting transcripts automatically, created backlog items with Fibonacci story point assignment, and produced real-time sprint velocity dashboards in Power BI. It replaced manual note-taking and task allocation that was consuming hours per sprint cycle.

For an enterprise software company, we built a knowledge management bot on Microsoft Copilot Studio and Azure AI Foundry using Azure AI Search over the company's internal document corpus. The bot answered both document-specific queries and broader general knowledge questions from a single interface.

The aerospace and pharma verticals in Montreal will bring domain requirements we have not yet seen from a Montreal client specifically. What transfers directly from these engagements is the Azure AI Foundry delivery approach: evaluation harness configuration, observability setup, and the Azure consumption cost controls that most organizations skip on their first Foundry project. See our Copilot Studio service page for related Microsoft AI work.

What Azure AI Foundry costs for a typical Montreal project

Engagements run between USD $25,000 and USD $120,000. We price in USD. Currency conversion between USD and CAD is your team's concern and does not factor into our rates.

• Small scope (USD $25,000–$45,000, 8–10 weeks): Single use case, one Azure AI Search index, basic evaluation harness, one system integration.
• Medium scope (USD $45,000–$80,000, 10–14 weeks): Multi-agent setup, two or three system integrations, production-grade observability, compliance documentation for Law 25 privacy requirements.
• Full platform (USD $80,000–$120,000, 14–16 weeks): Enterprise rollout across multiple use cases, full evaluation pipeline, regulated industry compliance review, staff training.

For pharma clients subject to Law 25, budget an additional USD $5,000–$15,000 for the privacy impact assessment phase depending on the number of data flows in scope. Azure consumption costs at scale are separate from our fees and are consistently underestimated on first Foundry projects. We scope these explicitly before the engagement starts. Full cost breakdown at our Azure AI Foundry pricing page.

How to start working with us

Three steps:

1. Discovery call (30 minutes): We discuss your use case, existing Azure setup, timeline, and any Law 25 or French-language obligations that affect solution design. Morning ET slots are available.
2. Scoping document: We send a written scope covering architecture, deliverables, milestones, and a fixed-fee or time-and-materials estimate within five business days.
3. Project start: Upon agreement, we assign a delivery team and begin the first sprint within two weeks.

Use the contact form below to book a discovery call.

Do you work with Montreal companies remotely?

Yes, and we have operated fully remote since 2010. For Montreal clients, the day-to-day arrangement is: daily overlap from 8:00 AM to 12:00 PM ET, async updates via Teams for the rest of the day, weekly sprint reviews on video, and a shared board that gives your team real-time visibility into what is in progress.

On data residency: Azure supports Canadian regions (Canada Central in Toronto, Canada East in Quebec City). We configure all Azure AI Foundry deployments to pin data to the appropriate Canadian region and document the complete data flow for your Law 25 privacy impact assessment. If your legal team requires a data processing agreement before the engagement starts, we can work through that in the scoping phase. We do not have a registered entity in Quebec, so contracts are signed with our India entity under standard offshore professional services terms.