AI consulting in Toronto for mid-market firms
An AI consultant who ships a system,not a strategy deck.
Bottleneck Labs is a Toronto AI consultancy that builds custom AI systems for mid-market firms, typically 20 to 500 people, in six-week engagements at a flat rate. We do not sell strategy decks, pilots or licenses. Every engagement ends with software your team uses on Monday.
Most AI consulting firms arrive with something they already built and look for a place to install it. We arrive with a team, a stack and 50+ hours of watching how your firm actually works, then build to the shape of your problem. The system goes on top of or beside the tools you already run, never in place of them unless you want it to be.
We work with firms in Toronto and across Ontario, and remotely across Canada. The first conversation is a diagnosis, not a pitch. If the answer is that you do not need us, we will say so.
The conditions this work is for.
The pilot that never became production
A proof of concept impressed everyone in a demo and then sat there, because nobody scoped the boring 80 percent: permissions, data quality, the exceptions your senior people handle by instinct. We scope that part first, which is why the six weeks are six weeks.
One person is the system
Someone in your firm spends most of their day answering questions only they can answer, or maintaining a spreadsheet only they understand. They cannot take a real vacation. When they retire, the knowledge leaves with them.
Work that is too important to keep doing by hand
Proposals, compliance checks, reports, intake. The work matters, so your most expensive people do it, which means they are not doing the work only they can do.
Tools that made the problem worse
You bought the platform, paid for the seats, and the team quietly went back to email and Excel. Software people refuse to use is not a technology problem, it is a fit problem.
The coaching team got their week back.
Real estate coaching platform. Toronto.
A Toronto engagement, start to finish. Three people doing manual review full time, a two to three week turnaround, and knowledge that lived in their heads.
Priced against your budget, not our hours.
- Flat rate, scoped in writing before we start. No hourly billing, no overrun charges, no mid-project upsell.
- Engagements run $12K to $100K or more. The number depends on what we are building, not on how long it takes us.
- Pricing is tied to a line item in your budget. If you spend a known amount on proposal writing or contract review each year, that number is the target. If the system does not move it, we failed.
- Six weeks from kickoff to a working system, with 50+ hours spent inside your firm before anyone writes code.
Scope and price are written down after the first two phases and reviewed by you. If we cannot agree on both, we do not start.
What people ask before they hire us.
What does an AI consultant actually do?
A useful one finds the specific place your firm loses time or money, proves AI can move that number, and then builds and ships the system that does it. The deliverable is working software plus the documentation to run it, not a roadmap. If a consultant's engagement ends with a presentation, you have bought research, not a system.
How much does AI consulting cost in Toronto?
Our engagements run $12K to $100K or more, flat rate, scoped in writing before we start. The range is wide because it depends on what we are building, not on how many hours we bill. Pricing is anchored to the budget line the system is supposed to shrink, so you can check the arithmetic yourself.
How long does a project take?
Six weeks from kickoff to a working system in most cases. The first two weeks are spent inside your firm watching people work, because the rules that matter are usually the undocumented ones. Bigger builds run longer, and we tell you that during scoping rather than after.
Do we need a data team or clean data first?
No. Most firms we work with have data scattered across four systems and a shared drive, which is the normal starting condition, not a disqualifier. Part of the engagement is making that mess queryable. You do not need to run a data cleanup project before you are allowed to start.
Should we build or buy our AI solution?
Buy when your process is genuinely standard and a vendor already serves it well. Build when your advantage is the way your firm does the work, because a platform will force you back to the average and you will lose the thing that made you worth hiring. Most mid-market firms need a small custom layer sitting on top of bought tools, not one or the other.
What happens after the engagement ends?
You own the system and the code. There is no per-seat license and no lock-in, and we hand over documentation written for the people who will run it. Firms who want ongoing work keep us on a defined scope, but nothing breaks if they do not.
AI for law firms
Contract review, precedent search and intake, built on your firm's own documents and standards.
AI for real estate
Deal documents, offering memoranda, listing workflows and market research, built on your own deal history.
AI for professional services
Engineering, accounting, agencies and consultancies. Proposals, compliance, reporting and internal knowledge.
Tell us where the work is stuck.
The first conversation is a diagnosis, not a pitch. If you do not need us, we will tell you that instead.
Start a conversation