AI Consultant in Toronto: Prices Published

The AI consulting firm that shows its work.

Nezam AI is an AI consulting firm headquartered in Toronto. We design, build, and operate AI systems inside working businesses: property management companies, brokerages, trades, and service operations across the GTA. Our prices are published, our production figures are on this site, and you own the code from day one.

Most of what is sold as AI consulting never becomes a system.

Toronto is full of AI consultants. Some of the operators who call us have already paid one, and what they have to show for it is a strategy document, a stalled pilot, or a chatbot nobody uses. The failure modes are consistent enough to list.

Proposals that will not name a price until the third call, then land somewhere you could never have budgeted for
Strategy decks that map your operation in PowerPoint and leave before anything runs
Pilots that impress in the demo and die on contact with your real phone line, your real inbox, your real data
A subscription to someone else's software, marked up and presented as consulting
Nobody accountable in month four, when the software on the other end of the integration changes and the system quietly stops working

What we build.

We are a build firm, not an advisory. The audit decides the order, the build ships in weeks, and everything below is running inside real businesses now, wired into Buildium, AppFolio, Follow Up Boss, HubSpot, Zoho, Salesforce, Slack, and the rest of the stack our clients already pay for.

Voice agents that answer every call. A phone line that picks up on the first ring at any hour, works out what the caller needs, handles it or routes it by your rules, and writes the summary into your systems before the caller hangs up. In production today on property management and brokerage lines.
CRM and follow up automation. Leads captured, deduplicated, qualified against your criteria, and chased until they answer or say no. The follow up discipline stops depending on who was busy that week. Running in production for GTA trades operators.
Workflow automation across your stack. The retyping between your platform, your inbox, and your accounting is a system boundary problem, not a staffing problem. We wire the workflows across the software you already pay for so it behaves like one system instead of four tabs.
Back office and accounting automation. Reconciliation, categorization, and reporting assembled automatically, with a person approving anything that moves money. Month end shrinks. The approval stays human, on purpose.
Custom platforms. When the right tool does not exist, we build it: most recently a direct booking platform for a hospitality operator. Custom is the last resort, not the first pitch, and the audit is where we tell you which one you are.
Search and AI search visibility. Being found in Google and being named by ChatGPT, Claude, and Perplexity are now two different jobs. We do both in the same engagement, and run this work in production for a Canadian rental platform.

How engagements work, and what they cost.

The model is four steps, and the prices are published because making you sit through a proposal to hear a number wastes your time and ours. The full list, with the reasoning behind each band, is in what AI consulting actually costs.

Discovery. Free, always. 30 minutes. Thirty minutes on what the operation runs on and where the hours go. If the honest answer is that you should not buy anything from us yet, that is the answer you get.
Audit. $3,000 to $5,000. 2 weeks. We map how the operation actually runs, find five to ten places where AI takes real work off your team, and hand back a prioritized plan with what each would cost. You own the document and can take it anywhere.
Build. $8,000 to $15,000 single system, $15,000 to $30,000 multi system. 4 to 10 weeks. Fixed scope, quoted against the audit. One workflow end to end, or a system that spans your CRM, your accounting, and your phone line.
Operate. $2,500 to $5,000 a month standard, $5,000 to $10,000 premium. Monthly. We run what we built, monitor it, fix what drifts, and ship something new every month. Cancel any month; the code is already yours.

Two honest asterisks. Every system also carries a running cost for the software it sits on, billed to you directly, and we quote it before you sign, not in month four. And the audit is where the build price stops being a guess, which is why we sequence it first: what the audit answers.

What we do that this market will not.

Every load bearing claim on this page is checkable: the prices, the production numbers, and the work we turn down.

Almost every firm in this category hides pricing behind a contact form and a discovery call. We publish the whole rate card, and we publish the reasoning: a real audit is ten to thirty hours of a senior engineer's time, and you can divide any quote, ours included, by a plausible number of hours and see what you are actually buying. The full price list and the logic behind it are in what AI consulting actually costs.

We publish production figures, and we frame them the way an operator would want them framed. When we say 26 percent of new leads in a two week CRM window arrived through a voice agent, we say it as a share of source, not a lift claim, because there is no pre deployment baseline and pretending otherwise would be marketing. A firm that will not show you measured numbers from a running system is asking you to be the first test.

We turn work down, in writing, on every page of this site. Nezam does not take engagements whose purpose is cutting headcount. That refusal costs us deals, which is exactly why it means something: a positioning line that never loses you money is a slogan. It also changes what gets built, because a system designed to take the 2am calls and the retyping off your team is a different system from one designed to replace them.

And we stay. The standard failure of consulting is that the incentive ends when the invoice clears. Our default engagement shape ends in Operate: we run what we built, monitor it, fix what drifts, and ship something new every month. You own the code from day one, so staying with us is a decision you make again every month, not a lock you signed into. The shape of the whole engagement is in the audit, build, operate model.

Measured, in production, here.

The figures on this site come from systems we run for a Toronto property management and brokerage operation. In a June production sample the voice agents answered 277 calls with zero missed, and 74 of those calls came in after hours, the volume a voicemail box used to absorb. In a two week CRM window, 34 of 130 new leads arrived through the voice agent, 26 percent of the total and the second largest lead source in the business, stated as a share of source because there is no pre deployment baseline to claim a lift against. On the brokerage side, 120 of 167 calls ended with an actionable lead captured. How each number was measured is in the impact study.

What is actually different about deploying AI in a Toronto business.

Not the talent pool, not the ecosystem. What is different is the law your systems operate under and the shape of the operations here. Four things we build for from day one, not as an afterthought:

PIPEDA is a design constraint, not a paragraph in the proposal. A voice agent records calls and captures personal information, which puts it squarely inside Canada's federal privacy law. Callers need to know, consent needs a basis, and every piece of captured data needs a home you can point to when someone asks. We design the disclosure, the retention, and the data map into the build, because retrofitting privacy after launch is how systems get turned off.
CASL applies to your follow up automation. Every automated text and email chasing a lead is a commercial electronic message under Canadian anti spam law, which means consent, sender identification, and a working unsubscribe on every message, wired in before the first send. US built automation templates routinely ship without any of this. We wire it in from the start, because we operate under the same law you do.
Ontario tenancy law draws a hard line through property workflows. In property management builds, automation handles intake, drafting, tracking, and reminders. It never serves a notice, never files with the Landlord and Tenant Board, and never makes a call with legal effect. Those stay with a person, on purpose, and we design the boundary so the system physically cannot cross it rather than promising it will not.
Canadian data residency, when it matters to you. Some of our clients, especially those touching tenant or client records, want data held in Canadian regions. Where that is a requirement we architect for it, and where a tool cannot meet it we say so before you buy the tool.

The operator profile we serve is specific too: GTA businesses of five to fifty people, phone heavy, running two to six pieces of software that were never introduced, where the owner is still the routing layer. That is who these systems are designed around.

Where we work.

We are not a generalist shop that will learn your industry on your invoice. The verticals below are where we work. Our production systems run today in property management, real estate, and the trades, and each page describes how the same builds land in that operation: property management, real estate, plumbing, electrical, HVAC, law firms, and marketing agencies. If your business is none of these but runs on phones, intake, and a stack of software that does not talk to itself, the shape of the work is the same, and the discovery call is free.

Who this is for.

Owner led companies in the GTA. Five to fifty people, where the owner still answers the phone and the operation runs on a stack of software that has never been introduced to itself. This is most of who we work with.
Operations drowning in intake. Property managers, brokerages, trades, and service businesses where the work arrives by phone and inbox faster than the team can route it, and the honest bottleneck is capture, not decisions.
Businesses that want one accountable partner. You want the firm that scoped it to be the firm that built it to be the firm that answers when it breaks. That is the model. No handoff to a subcontractor you never met.
Who we are wrong for. Enterprises that need a transformation program, engagements whose real goal is cutting staff, and businesses where an off the shelf tool at a couple hundred dollars a month is the right answer. We tell you the last one on the discovery call, because selling you a build you do not need costs us the referral that was worth more.

Questions, answered straight

What does an AI consultant cost in Toronto? Our prices are published. The discovery call is free, an AI readiness audit runs $3,000 to $5,000, a custom build runs $8,000 to $15,000 for a single system and $15,000 to $30,000 when it spans several, tool selection and implementation runs $5,000 to $12,000, and ongoing operation runs $2,500 to $5,000 a month standard or $5,000 to $10,000 premium. The reasoning behind each band, including the second bill most proposals leave out, is in what AI consulting actually costs.

What does an AI consultant actually do? The useful ones do three things: map where AI takes real work off your team, build the systems, and keep them running after launch. The audit is watching how the operation actually runs, because what people describe and what happens on a Tuesday are different processes. The build is senior engineering against a fixed scope. The part most firms skip is the third one, and it is where systems live or die.

How are you different from a big consultancy or an AI agency? A national firm sells strategy by the hour and hands the build to a delivery team you will never meet, at engagement sizes that start where our largest builds end. We are the people who build it. The engineers who scope your system are the engineers who ship it and the ones who answer when something drifts in month four. If you need a thousand person transformation program, we are the wrong firm and will say so.

Why not just hire someone in house? For some businesses that is the right call, and the audit will tell you so. The honest problems are that senior AI engineering talent is scarce and expensive for a company our clients' size, the work is lumpy, an intense build then months of quiet, and one hire gives you one person's skill set. We wrote about the version of this that does work in your most important AI hire is already in the building.

Do you only work with Toronto businesses? Toronto is home and the GTA is where we can sit in your office and watch the phones. But the firm runs across three cities, Toronto for HQ, Cairo for engineering, Dubai for delivery, and we take on clients across Canada remotely. The builds are wired into cloud software either way; what changes is how often we are physically in the room.

How long until something is live? The audit takes two weeks. Builds run four to ten weeks depending on how many systems they touch, and the phones are usually first because that is where the measurable loss is. We test against your real call patterns and your real data before anything goes live alone, which is slower than a demo and the reason it survives contact with the real operation.

Will this replace my team? No, and we refuse engagements where that is the goal. Nezam does not take on work whose purpose is cutting headcount. AI should give people back their time, not take their jobs, so what we build takes the after hours calls, the retyping, and the routing off the people you already have. If you want a vendor to help you cut staff, we are the wrong firm, and we would rather tell you here than on the call.

We are a small business. Are you the right fit? Sometimes. Below a certain size the honest answer is a good off the shelf tool at a couple hundred dollars a month, and when that is true we say it on the discovery call and point you at the tool. The threshold question is whether enough hours are leaking to pay back a real build. We wrote the honest version of that math in can a small business afford an AI consultant.