AI & Machine Learning Company in Quebec City

Un proof of concept ciblé tourne entre 35 000 et 80 000 CAD sur six à dix semaines, couvrant l'audit des données, un modèle de référence, et une démo hébergée bilingue. A scoped AI proof of concept runs CAD $35,000 to $80,000 over six to ten weeks. A custom production ML model (claims triage, fraud scoring, document extraction in French) typically lands at CAD $110,000 to $260,000 including MLOps, monitoring, and a Loi 25 Privacy Impact Assessment. Full production AI systems with RAG, multiple models, fine-tuning on French corpora, and AMF-grade documentation range from CAD $220,000 to $1M. Quebec City rates sit below Toronto and Montreal because the talent market is tighter on supply but less inflated on price. We deliver fixed-fee proposals in French and English, not open T and M.

Loi 25 (formerly Bill 64) is the most stringent privacy regime in North America. It requires a Privacy Impact Assessment for any project handling personal information, mandates explicit consent for automated decision-making, gives Quebec residents a right to receive an explanation of any automated decision affecting them, requires a designated Person in Charge of Protection of Personal Information, and authorises the Commission d'accès à l'information to issue administrative monetary penalties up to 4 percent of worldwide turnover or CAD $25M. Our discovery phase runs a Loi 25 PIA, every high-impact model ships with a plain-language French explanation interface, and we keep training data inside ca-central-1 or Canada East. Cross-border transfers require a comparative privacy assessment, which we author rather than outsource.

Yes, and this is where most national vendors fail. We tune retrieval and classification pipelines on Quebec French specifically, not just standard French from France, accounting for joual, regionalisms, OQLF-mandated terminology (no anglicisms in regulated user-facing copy), and bilingual switching common in Quebec workplaces. We use Camembert and CamemBERTa as base encoders for many French NLP tasks, layer in Mistral and Llama 3 fine-tunes when generative output is required, and ship evaluation harnesses that test against both Quebec French and Canadian English. Every user-facing surface is reviewed against the OQLF Grand dictionnaire terminologique and against Bill 96 obligations on French as the language of work.

Bill 96 strengthens the Charter of the French Language and requires that French be the language of work for any business operating in Quebec with 25 or more employees, including all software interfaces and internal AI tools. Our delivery default is French-first: French is the primary locale, English is a toggle. All admin consoles, error messages, model output explanations, and audit logs render in French by default, and all training documentation, runbooks, and onboarding materials ship in French. We coordinate translation through OQLF-aware francophone linguists rather than machine translation, because the OQLF inspections look specifically for anglicism patterns that auto-translation produces.

When a Quebec City project requires genuine research depth (novel architectures, rare-event detection in claims, French NLP at the frontier) we scope collaborations with Université Laval's Faculté des sciences et de génie, the IID, or the CRDM rather than overselling in-house capability. Our core team handles applied engineering, MLOps, and productionisation, which is where most Quebec City AI projects actually stall. For standard work (RAG, classical ML, document extraction, computer vision on known backbones) no academic partner is needed. We have introduced Quebec City clients to IID industry partnerships and to Laval's MITACS-funded internship programs when scope and budget make it the right call.

Loi 25 does not strictly mandate Quebec residency but requires a comparative privacy assessment for any transfer outside Quebec. We default to AWS ca-central-1 in Montreal, Azure Canada East (the Beauceville-Vallée-Jonction region inside Quebec), and GCP northamerica-northeast1 in Montreal for storage, training, and inference. For LLMs needing strict in-Canada operation we use Cohere's Canadian endpoints or self-host Llama 3, Mistral, or Camembert on Canadian GPU instances. Cross-border calls to US frontier models are acceptable only when the comparative assessment signs off, which is unusual for AMF-regulated insurers or any health context. We document residency in the model card and the agreement in French and English.

A typical Quebec City insurance AI model (claims triage, fraud scoring, FNOL document extraction, sub-rogation prediction) runs sixteen to twenty-four weeks from kickoff to production, assuming clean historical data and AMF documentation as in-scope. Week 1 to 4 is data audit, the Loi 25 PIA, and baseline. Week 5 to 12 is modelling, iteration, and challenger testing against current adjuster decisions. Week 13 to 19 is MLOps, monitoring, shadow mode deployment, and the internal audit walk-through. Week 20 onward is gradual rollout coordinated with AMF disclosure obligations and a Bill 96 review of all user-facing copy. Add six to eight weeks if French training data needs labelling.

Yes, and Quebec credits stack on federal SR&ED to make this one of the most generous AI R&D jurisdictions in the world. Federal SR&ED returns 35 percent refundable on eligible spend for Canadian-controlled private corporations up to the $3M expenditure cap, and 15 percent non-refundable above. Quebec adds the R&D wage tax credit at 30 percent for CCPCs and the e-business tax credit (CDAE) at up to 30 percent on IT salaries for qualifying activities, and Investissement Québec offers project-based programs for AI specifically. We deliver time-tracked logs, technical narratives in French and English, experiment histories, and failed-hypothesis documentation aligned with the CRA T661 and Revenu Québec RD-1029.7. Final eligibility sits with your SR&ED consultant and Revenu Québec.