AI Agents Company in Toronto: Custom Agents Built and Run in Canada

The distinction that matters is between an assistant that talks and an agent that acts. An agent is given a goal, a set of tools it is allowed to call, and a set of rules about when it must stop and ask a person. It reads the request, chooses the tool, performs the action, writes the result back, and leaves an auditable trail of what it did. Building one is mostly integration and evaluation work, not prompt writing.

In practice the agents we build for Canadian businesses fall into four families:

• Voice agents — answer the phone, qualify the caller, book or reschedule, take a message, escalate an urgent call to a human line.
• Intake and scheduling agents — collect the information a new patient, client or job needs, validate it, and write it into the practice-management or field-service system.
• Follow-up agents — confirmations, reminders, recalls, no-show recovery and review requests, sent on the channel the customer actually uses.
• Back-office agents — reconcile records between systems, prepare paperwork, route documents, and flag exceptions for a person to approve.

Each of those is built on the same production platform, with the same logging, guardrails and Canadian hosting. The AI agents and deployment page covers the architecture and integration surface in more depth.

Maya matters commercially, but she matters more as evidence. Running a voice agent in production for Canadian clinics and trades means we own the parts of this work that are genuinely hard: latency budgets, misheard phone numbers, double-booking races, calendar sync that has to stay honest, after-hours routing, consent disclosure at the start of a call, and what happens when a model gets something wrong at two in the morning. Those lessons go straight into every custom agent we build.

Maya connects to practice-management and calendar systems including NexHealth (Dentrix, Open Dental, Eaglesoft), Cal.com, Google Calendar and Microsoft Outlook, plus Clio, HubSpot, Stripe and Canadian SMS providers. Sector detail lives on the dental clinics page and the trades and home services page.

Maya's published plans are Starter at CAD 299 per month for up to 150 calls, Growth at CAD 499 per month for up to 400 calls, and Enterprise on custom pricing for multi-location or regulated deployments.

The failure mode this addresses is well documented. MIT's 2025 NANDA report, "The GenAI Divide: State of AI in Business 2025", found that roughly 95% of enterprise generative-AI pilots delivered no measurable business impact, and that buying from specialised vendors and forming deployment partnerships succeeded far more often than internal do-it-yourself builds. The bottleneck was rarely model quality; it was the last mile between a demo and a system people actually use.

So we structure engagements to make that last mile the deliverable rather than the afterthought:

• Fixed fee, agreed before work starts. No open-ended hourly billing, and no discovery phase that quietly becomes the project.
• Production or it does not count. The deliverable runs in your environment against your data, with an evaluation framework attached.
• We operate what we build. Monitoring, tuning and incident response continue after go-live, because agents drift when the business changes.
• Compliance designed in. Canadian hosting, tenant isolation and consent handling are part of the first commit, not a remediation project later.

For larger organisations that already have a systems integrator, we work alongside them through the Enterprise AI Factory model rather than competing for the whole programme. Many engagements may be SR&ED-eligible; eligibility is determined by the CRA, and nothing here is tax advice.

Which number applies depends on how much certainty you already have. If the workflow, the systems and the success measure are clear, you can start at Pilot to Production. If the organisation has a list of ideas and no ranking, the Readiness Sprint is cheaper than discovering the answer mid-build. If the constraint is senior AI judgement rather than delivery capacity, the Fractional AI Lead retainer is usually the right instrument.

Subscription products sit below all of that: Maya starts at CAD 299 per month. A full breakdown of what drives price up or down — integration count, compliance review, data quality, number of edge cases — is on the forward-deployed AI cost guide, and the delivery model itself is explained on forward-deployed AI for Canadian business.

Concretely, that means data residency in Canadian regions rather than a US default; row-level access controls so one client's records are never reachable from another's session; consent disclosure at the start of a recorded call; retention windows agreed with you rather than assumed; and audit logs that show which agent took which action against which record. Our own security posture is aligned with SOC 2 practices, and we describe it that way deliberately — we do not claim an attestation we do not hold.

British Columbia clients have a separate consideration under BC PIPA for call recording, and Quebec's Law 25 adds its own obligations. The PIPEDA and PHIPA guide sets out what a Canadian business should ask any AI vendor before signing, including the questions we would expect a privacy officer to put to us.

The discovery call is a working session, not a pitch. We ask what happens today when the phone rings or the form is submitted, who touches the record next, where the process breaks, and what a good outcome would be worth. You leave with a straight read on whether an agent is the right tool — including when it is not, which happens often enough that we say so.

From there the sequence is consistent: scope and price the work, connect to a test environment, build against real cases, evaluate against a held-out set of real calls or records, run supervised in production, then hand over with monitoring in place. Nothing goes live to your customers until it has been measured against examples you recognise.

We are based at 2967 Dundas St. W. in Toronto's Junction and deliver across the Greater Toronto Area, with the same delivery model available remotely anywhere in Canada. Local pages cover what we do in each municipality:

On the industry side, dental and medical practices are where our production experience is deepest, followed by trades and home services, where the cost of a missed call is immediate and measurable. Legal, professional services and regulated enterprises typically start with intake and document workflows rather than voice.

Rule-based automation is excellent when the input is already structured and the path is fixed — a form submission creating a CRM record, for instance. It fails when the input is a person on the phone who says "I think my appointment is Thursday, but it might be the week after, and can my daughter come at the same time?" Nothing in that sentence maps to a trigger.

A chatbot handles the language but stops at the answer. An agent goes further: it resolves the ambiguity, looks up both appointments, checks availability, proposes a slot, books it, sends the confirmation, and escalates if anything looks wrong. The engineering that makes that safe — tool permissions, refusal conditions, confirmation steps before irreversible actions, and an evaluation set that catches regressions — is the actual work.