AI Agent Development Company in Montreal

We are not headquartered in Montreal. We work with Montreal clients in AI research, aerospace, pharma, and gaming on remote engagements with four to five hours of daily ET overlap. QServices is a remote-first software consultancy serving Quebec and Canadian businesses in AI agent development.

What Montreal buyers typically need from AI agent development

Montreal sits at the intersection of serious AI research and regulated industry work. That combination shapes what AI agent projects look like here.

• AI research organizations: Prototype agents that connect frontier models to internal data pipelines, with evaluation frameworks before any production deployment.
• Aerospace companies (Bombardier, CAE, Pratt & Whitney): Document processing agents for engineering specs, maintenance records, and submissions to Transport Canada.
• Pharma and life sciences: Agents that surface clinical trial data or automate regulatory document workflows, with audit trails satisfying Health Canada requirements and PIPEDA obligations.
• Gaming studios (Ubisoft, EA, WB Games): Agent-assisted content pipelines, QA automation, and player behavior analytics.

Quebec Law 25 adds a compliance layer every project must address. Any AI agent handling personal information about Quebec residents requires a privacy impact assessment, documented consent mechanisms, and a named privacy officer. French language requirements under the Charter of the French Language mean user-facing interfaces and internal tools must support French. We factor both into the architecture from the start, not as an afterthought. The Commission d’accès à l’information du Québec (CAI) is the enforcement body for Law 25.

How we work with Montreal clients

Our engineering team is in India (IST, UTC+5:30). Montreal runs on ET (UTC-4 in summer, UTC-5 in winter), a 9.5-hour gap during EDT. In practice, our team shifts part of the day so that 9 a.m. to 1 p.m. ET overlaps with our afternoon in India. That gives us four to five hours of live synchronous time each working day.

A typical week looks like this: a standing call Monday mornings ET to align on priorities and clear blockers; async updates every Wednesday with recorded demos and a written status note in the shared project workspace; a structured sprint review every two weeks on Teams or Zoom. Pull requests go through code review within 24 hours. For milestone reviews, we can send a senior engineer for an on-site session in Montreal, though most clients prefer recorded walkthroughs to avoid the travel cost.

We work in English. All documentation, code comments, and client-facing artifacts are in English unless a bilingual deliverable is explicitly scoped and budgeted at the start.

Relevant work in similar markets

We have not shipped an AI agent for a Montreal-based client specifically. Here is our closest real work.

For a Canadian investment management platform (Melegacy), we built a Microsoft Copilot Studio chatbot that pulls ML-powered stock predictions from Nasdaq historical data and lets users manage legacy sharing with nominees and charities inside a single agent. The governance pattern here, where an agent surfaces regulated financial data under defined human review checkpoints, is directly applicable to pharma or financial services clients in Montreal working under PIPEDA.

For an IT services company, we built Smart PM: an Azure AI Foundry agent connected to Azure DevOps, MS Teams, and Fireflies.ai that captures meeting transcripts, auto-creates backlog items with Fibonacci story points, and drives real-time Power BI sprint dashboards. The traceability model, from conversation to documented requirement to tracked delivery, maps directly to aerospace or pharma project management needs in Montreal, where a missed step in a regulated workflow is not a minor issue.

In both engagements, the Human-in-the-Loop (HITL) design was not optional. Regulated data requires a human review checkpoint before the agent can act on it. That is the default architecture we bring to Montreal clients in aerospace and pharma, where a missed compliance step costs far more than a slower process.

What AI agent development costs for a typical Montreal project

We price in USD. Typical AI agent projects run USD $15,000 to $85,000, delivered in 6 to 12 weeks. Here is how scope maps to cost:

• Focused agent (USD $15,000 to $30,000): Single-purpose agent, one or two integrations, internal use only. Covers design, build, testing, and a 30-day post-launch period.
• Production agent (USD $30,000 to $85,000): Multi-step agent with Human-in-the-Loop review workflow, three to five integrations, and a production-grade evaluation framework.
• Enterprise build (USD $85,000 and above): Multi-agent architecture, Quebec Law 25 compliance documentation, third-party security review, and an ongoing maintenance retainer.

Quebec Law 25 compliance adds roughly 15 to 25 percent to a project budget. Each non-trivial system integration adds USD $3,000 to $12,000. Our standard hourly rate is USD $35, senior architects at USD $65. Monthly maintenance retainers run USD $2,000 to $4,000. Full pricing detail is at AI agent development pricing.

How to start working with us

Most Montreal engagements start with a conversation about the specific use case and the compliance context, particularly around Quebec Law 25 and any PIPEDA obligations. Three steps from there: book a 30-minute discovery call; receive a written scoping document with timeline, tech stack, and a fixed or capped budget within five business days; then schedule a project kickoff with access to the shared project workspace. The lead form is below.

Can you work with Montreal companies remotely?

Yes. Our team overlaps with Montreal’s ET morning from 9 a.m. to 1 p.m. ET each working day. We use Microsoft Teams or Slack for communication and async video for demos and reviews.

For data residency under Quebec Law 25, we architect the solution using Canadian Azure regions (Canada Central, Canada East) when clients require personal data to stay within Canada. For pharma clients with PIPEDA obligations, we scope the data residency and audit architecture at the start of the project, not as an add-on. If your project involves French-language user interfaces, we flag translation and testing scope during the discovery call. Learn more on our AI agent development service page.