AI Agent Development Company in Edmonton

We quote in Canadian dollars against a signed statement of work, fixed fee, and the honest answer is a range because scope drives the number. A scoped proof of concept covering one agent, three to five tools, an evaluation suite, an action log view and a hosted demo behind single sign-on typically runs CAD 40,000 to 95,000 over six to ten weeks. A production agent with guardrails, a human approval console, observability, integration into a system of record and the governance documentation your privacy officer needs typically runs CAD 150,000 to 400,000. A multi-agent platform with role-specialized agents, shared memory, custom evaluators and integration into core systems such as SAP, Dynamics 365, Epic or a plant historian runs CAD 400,000 to 1,000,000 and up. Senior engineering rates in Edmonton run meaningfully below Toronto and Vancouver and far below San Francisco and New York, and for a United States buyer the exchange rate compounds that. Alberta's general corporate income tax rate is 8 percent, the lowest of any province, and eligible research and development work can draw federal SR&ED plus Alberta's Innovation Employment Grant worth up to 20 percent of qualifying expenditures. We deliver the time tracking and technical narratives those claims require.

Bill C-27, the Digital Charter Implementation Act, carried the Artificial Intelligence and Data Act. It was still in committee when Parliament was prorogued on January 6, 2025, which killed it, and it was not reintroduced before dissolution. AIDA is not law and nobody should be sold compliance with it. What does bind you is everything else. Privacy law applies to the data the agent touches: Alberta's Personal Information Protection Act for most private sector activity in the province, the federal PIPEDA for federal works and undertakings such as banks, telecommunications carriers and interprovincial transport as well as personal information crossing provincial or national borders, and the Health Information Act for health information. Public bodies fall under the Protection of Privacy Act and the Access to Information Act. Sector regulators matter more than any general AI rule: a federally regulated financial institution is inside OSFI's technology and cyber expectations under Guideline B-13 and, from its 2027 effective date, the revised Guideline E-23 on model risk management published September 11, 2025. Beyond that, we build to ISO/IEC 42001, the AI management system standard published in December 2023, and to NIST AI RMF 1.0, released January 26, 2023.

With an evaluation suite that exists before the agent does, because demo quality and production quality diverge fast once inputs stop being the ones you chose. We start by writing down the task the agent is replacing and the error rate a human currently produces on it, since a system that is wrong less often than the process it replaces is a different conversation than one measured against perfection. From there we build three layers. Trajectory tests check whether the agent selected the right tools in the right order, which catches reasoning failures that a correct final answer can hide. Outcome tests check the end state in the target system, graded against a fixed answer key built with your subject matter experts rather than by a model marking its own work. Adversarial tests cover prompt injection through retrieved documents, contradictory instructions, missing data, tool timeouts and the ambiguous requests real users send. Each of the three runs on every build, not once before launch, and regression on a previously passing case blocks release. We also instrument production: sampled human review, disagreement logging wherever a reviewer overrides the agent, and a drift alarm on tool-call distribution. The number that decides go-live is agreed in the first month, in writing, so nobody negotiates the bar after seeing the result.

Yes, and in the Heartland it is the normal request rather than an exception. The architecture we use keeps a hard boundary. The agent lives on the business network. It reads from the operational side through a one-way or read-only path, typically a historian replica, an OPC UA gateway configured read-only, or an exported data lake, and it never holds credentials that can write to a control system. Zone and conduit design follows ISA/IEC 62443 so the security architecture matches what your control systems engineer already defends. Where policy forbids any hosted model call, the entire stack runs on client hardware: self-hosted Llama, Mistral or Qwen weights on on-premise GPUs, orchestration on LangGraph inside an isolated network segment, retrieval against internal procedure and drawing repositories, and guardrail classifiers running locally as well. The trade is capability headroom against frontier models, which we manage with retrieval grounding, task decomposition into steps a mid-size open model handles reliably, and fine-tuning on internal documents with LoRA. Any action that leaves the read-only envelope, such as raising a work order or notifying a crew, goes through a named human approver and is logged.

The practical options are AWS ca-central-1 in Montreal or ca-west-1 in Calgary, Azure Canada Central in Toronto or Canada East in Quebec City, Google Cloud northamerica-northeast1 in Montreal or northamerica-northeast2 in Toronto, on-premise hardware in your own Edmonton facility, or a Canadian managed provider. For Edmonton workloads ca-west-1 in Calgary is the nearest region by a long way, roughly 300 kilometres south, which is the right default when an operator is waiting on a response. Cohere is a Canadian model provider and is worth evaluating where sovereignty is the deciding factor. We are straight with clients about the cost of the constraint: model selection inside Canadian regions is narrower and newer frontier models land later than in the large United States regions. Where a client can accept cross-border processing we run a privacy impact assessment, confirm the contractual and disclosure position under PIPA or the Health Information Act, and document it before writing code. Where they cannot, we self-host and accept a smaller model. Residency, retention and deletion behaviour are written into the design document and into the data processing agreement so the answer exists before anyone asks.

It changes the parts of an agent project that fail over video. Risk classification, human-in-the-loop tier assignment and stakeholder mapping depend on argument and interruption, and those go badly on a scheduled call with a muted room. We run discovery and architecture reviews in person at our Edmonton office or at yours, we can be at a site in Fort Saskatchewan, Nisku or Acheson the same morning, and we hire locally out of the University of Alberta, NAIT and MacEwan rather than flying staff in and billing the travel. There is no time zone gap to manage with your team because there is no time zone gap. Our Chandigarh team covers the overnight window: India keeps a single time zone and does not observe daylight saving, so Chandigarh sits 11.5 hours ahead of Edmonton in summer and 12.5 hours ahead in winter, and a 9:00 AM Edmonton standup lands at 8:30 PM there in July. Work you approve at the end of a Mountain Time day has moved before you open your laptop the next morning. Founded in 2018, Codazz has delivered 500 or more projects and employs more than 200 engineers across Edmonton and Chandigarh. You can reach us at +1 (403) 604-8692.