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AI development

AI Development Company in Toronto

The best AI Development Company in Toronto, at the best available price.

$0 upfrontPay per accepted checkpointSenior engineer, no agency markup

Most of what gets sold here as AI development is a team of five with one person who has shipped, and a bill that reflects the other four. This is the opposite arrangement: the engineer who scopes it is the engineer who builds it, the price is fixed before anything starts, and you pay nothing until a checkpoint is delivered and you accept it.

Toronto is Canada's largest technology labour market and its financial centre, with the major banks, insurers and a dense startup scene around the University of Toronto and MaRS. Buyers here are often banks, or companies selling to them, so security reviews and data residency questions come early.

Toronto's AI scene is deep in research talent, but shipping a product still needs production work: retrieval, evaluation, guardrails and cost control. That is the work we do.

What you get

  • One senior engineer end to end: the person on your first call architects it, writes it and hands it over
  • LLM features, retrieval over your own documents, agents that call real tools, and voice where it earns its place
  • Deployed in your own cloud account in a regional data centre, or on your own hardware where residency demands it
  • Fixed price and fixed scope agreed in writing before work starts, invoiced per accepted checkpoint
  • Code and infrastructure in your repository and your accounts, written to make us replaceable on purpose
Working builds from $1,000. Full production systems from $12,000.

Nothing payable upfront. You hold every dollar until a checkpoint is delivered and accepted, and thirty days of defect correction is included. Final scope and price are settled on a call before any work begins.

Invoiced in USD or CAD, payable by Wise or bank transfer.

Request a callback

You speak to the engineer who does the work. No sales rep, no deck.

No spam and no sales team. You talk directly to Neeraj.

Toronto, Ontario

Who builds here

Banks, insurers and fintechMaRS Discovery DistrictVector Institute and University of TorontoEnterprise SaaS
Best fit in Toronto

Software Development Company

Many Toronto companies need senior engineering capacity that can pass a bank-grade vendor review, which is exactly what a dedicated engineer working in your repository provides.

Architecture diagram of orchestrated AI agents with an MCP harness: a product on web, mobile or Slack sends a request to a central orchestrator that runs the flow step by step, consults a model router across Claude, GPT, Gemini and open-weights models, and hands work to a research agent, an action agent and a review agent. Every tool call passes through one MCP harness that enforces permissions, retries and logs before reaching the CRM, the database, email and calendar, or your internal API. Evals, tracing and replay, and cost per request run alongside.
One orchestrator runs the flow, and every tool call goes through the same MCP harness, so permissions, retries and logs live in one place.
How you pay

Get it built at $0.

That is not a discount. It is when you pay. The work is split into checkpoints with acceptance criteria written down before anything starts, and each checkpoint is invoiced only after you have seen it and accepted it. No deposit.

$0 to start
You hold every dollar until a checkpoint is delivered and you accept it. No approval, no invoice.
Fixed cost, unlimited features
Or hire the team outright: one fixed monthly cost, unlimited feature development, any stack.
The engineer takes your call
The person on your first call is the one who architects and writes it. No account managers, no bench time.

A US agency quotes $50,000 to $150,000 for the same build and asks for 40 to 50% of it before a line is written. Account managers, project managers, sales commission and bench time. None of it appears in your product.

How it works

Three stages, nothing hidden.

01

Twenty-minute call

You talk to the engineer who will build it. We scope the problem, and if this is the wrong fit for you, you get told so on that call rather than three weeks into a proposal.

02

Fixed proposal in 48 hours

Fixed price, fixed timeline, defined deliverables, in writing. No hourly billing, no open-ended scope, and no change-request business model.

03

Checkpoints until it ships

Working software at each checkpoint, with acceptance criteria agreed before that checkpoint starts and an invoice only after you accept it. Direct access throughout, not a ticket queue.

Working in Toronto

What actually applies here.

Regulation and data

Private companies in Ontario fall under the federal privacy law, PIPEDA, and federally regulated financial institutions also answer to OSFI, whose guideline on third-party risk shapes what banks ask of their vendors. Health information custodians in Ontario are covered by PHIPA. Canada's proposed federal AI law, AIDA, died when Parliament was prorogued in early 2025, so there is no national AI statute yet. Ontario now requires employers to disclose in public job postings when AI is used to screen or assess applicants.

Contracting and payment

You contract with an individual consultant based in India. Invoices in CAD or USD, paid by Wise or bank transfer. Your accountant treats an overseas supplier in the usual way, and any paperwork they need is provided before work starts.

Working hours

Four or more hours of daily overlap with Eastern time, calls in your morning, and same-day replies on working days.

Can our data stay in Canada?

Yes. We deploy into Canadian cloud regions in your own account, and models can run there too, so prompts and data do not leave the country.

Can you work with Ontario health data?

Yes, under the agreement your privacy officer requires for PHIPA, with data kept in Canada and every access logged.

Why would we use an overseas engineer rather than a local integrator?

Often you should use both. An integrator holding the prime contract and the local relationship, with a specialist doing the AI and data layer underneath, is a common and sensible structure here. What you should not do is pay integrator rates for engineering that one person is actually doing.

Can the system run entirely inside our own infrastructure?

Yes, and in this region that is frequently the requirement rather than the preference. Model serving on your own hardware or in your own cloud account in a regional data centre, with no outbound calls, up to fully air-gapped.

Who owns the code?

You do, entirely. It ships into your repository on your own cloud accounts, documented so your team or your next hire can carry it without us, and all our access is removed at handover with written confirmation.