AI agent teams that do real work. Your people stay in charge.
archCTO designs, builds and runs governed AI agents for architecture and engineering firms, bookkeepers, life-sciences and other professional teams across Ontario. They take the repetitive work off your desk and hand you drafts to approve.
The work behind the work, drafted before you sit down.
We start where your team loses the most hours to repeatable steps, then add agents one at a time.
Inbox & enquiry triage
Sort incoming email, qualify new leads, update the customer list and draft replies in your voice.
Quotes, estimates & proposals
Draft scoped estimates from your own fee rules, with a missing-information checklist for review.
Research & compliance notes
Prepare code, zoning, regulatory or policy notes with sources, for a qualified person to confirm.
Document & data extraction
Pull fields from forms, drawings, invoices and PDFs into the system they belong in.
Follow-up & scheduling
Chase missing documents, remind clients and propose meeting times so nothing falls through.
Reconciliation & reporting
Match, categorise and flag exceptions, then summarise the week for the people who decide.
We don’t sell 15-minute AI bots. We build an AI team that fits your business.
Anyone can wire up a chatbot in an afternoon. It rarely survives real clients, real rules and real exceptions. archCTO takes the longer, smarter road: understand the pain, re-engineer the work, deploy what fits, then manage your AI team as it grows.
- 01
We learn your business first
We sit with the people doing the work, time real cases and find exactly where hours, margin and patience are lost.
- 02
We redesign, not just automate
Automating a messy process only makes the mess faster. We rethink the workflow around people and agents together, phase by phase through the archCTO A.G.E.N.T. Framework, to reach the outcome you already want.
- 03
We ship the right solution
The simplest thing that works, inside your own tools, tested on your past cases, with guardrails and a named approver from day one.
- 04
We stay on as your AI manager
Agents need a manager too. Every month we monitor quality and cost, learn from your edits, improve what is live and add new agents when they earn their place.
Strategy→Implementation→AI team managementOne accountable partner, end to end.
A.G.E.N.T.: five phases from idea to measured value.
The same method in every industry. What changes is the domain knowledge, the rules and the people who sign off.
Audit
Map how the work happens today and time a sample of real cases. That becomes the baseline.
Gauge
Score workflows for value, repeatability and risk. Choose one pilot and one success number.
Engineer
Design the agents, their tools and data, and test them on your anonymised past cases.
Navigate
Decide who owns each step, who approves what, and how your team learns to work with agents.
Track
Measure outcomes against the baseline every month, then scale, adjust or stop.
Guardrails we never skip.
Autonomy is earned. Agents start in shadow mode and take on more only as their measured correction rate falls.
Draft-only by default
Agents prepare; people send. Money, legal, compliance and anything external always needs a named approver.
Your data, your accounts
Agents run inside your own Microsoft, Google or cloud tenancy. Canadian hosting regions are available when data residency matters.
Outside content is data, not orders
Emails, web pages and attachments can never instruct an agent to act. That is the first defence against prompt injection.
Every run is logged
You can see what each agent read, drafted and why, and every agent has a kill switch and a manual fallback.
Caps on cost and loops
Rounds, calls, time and spend are capped. When a cap is hit, the work goes back to a person.
Canadian privacy in mind
Designed around PIPEDA principles and the rules of your profession, with access limited to what each agent needs.
Start simple. Move to code only when the work needs it.
Agents in the tools you already pay for
Built on your Microsoft 365 or Google Workspace, your AI workspace (Claude, ChatGPT or Copilot) and a shared tracker such as Notion. Live in weeks, with a low monthly run cost and nothing to host.
- Fastest route to a working pilot
- Your team can see every rule and draft
- Best for small and mid-size firms
Agents as tested code on your cloud
Python agents, APIs and workflows on Azure or Google Cloud, with webhooks, a review portal, CI/CD, monitoring and Canadian regions. For volume, real-time triggers or systems without a ready connector.
- 24/7 triggers and higher volume
- Any model, any API, full audit trail
- Hybrid with the workspace option
Go-live is the start, not the finish line.
Agents drift, rules change and your business grows. After launch we manage your AI team the way a good manager runs any team: watch the work, coach it, report results and plan what comes next.
Monitor
Quality, failures and run cost reviewed on a set rhythm, with alerts when something drifts.
Learn
Your edits to agent drafts are compared and turned into better rules, after you confirm them.
Improve
Prompts, tools and playbooks are versioned, tested and released with a change log.
Report
A monthly report on time saved, quality and cost against the original baseline.
Plan
A regular roadmap session on what to automate next and what to retire.
Grow
New agents join the team one at a time, only when the numbers say they will pay back.
The right tool at every layer, with guardrails across all of them.
We stay vendor-neutral, so you are never locked into one model or platform.
Agents meet people inside the tools they open every day, so adoption does not depend on a new app.
The simplest pattern that works: a workflow first, one agent with tools next, a coordinated agent team only when the work needs it.
Models are interchangeable parts. Each step gets the model that fits its quality, cost and data rules, and can be swapped later.
Agents are only as good as the data they read. We connect trusted sources and measure results in dashboards leaders already use.
When an agent outgrows a workspace, we ship it as tested code on your cloud, with Canadian regions available.
Product names and logos are trademarks of their respective owners. They show platforms archCTO works with and do not imply endorsement or partnership.
Where agents are already earning their place.
Anonymised, and labelled honestly: live, in design, or a blueprint.
A local partner for AI agents in Toronto, the GTA and across Ontario.
We know the rules Ontario businesses work under, from the Ontario Building Code and municipal zoning to CRA deadlines and Canadian privacy law, and we design agents around them. Meet us on site or online.
- Toronto
- Mississauga
- Brampton
- Vaughan
- Markham
- Richmond Hill
- Oakville
- Burlington
- Hamilton
- Kitchener-Waterloo
- Guelph
- London
- Ottawa
- Barrie
- Oshawa & Durham
Straight answers before you start.
What is an AI agent team?
A small group of AI agents, each with one job (for example triage, estimating, research or review), coordinated so work moves from one to the next. A person approves anything that matters before it leaves the business.
How is this different from using ChatGPT, Claude or Copilot directly?
Chat tools answer when someone asks. Agents do a defined job on a schedule or trigger, read and write in your systems, follow your rules, and leave a log. We use the same models underneath, chosen per task.
Do you work with businesses across Ontario?
Yes. archCTO is based in Ontario and works with firms across Toronto and the GTA, Hamilton, Kitchener-Waterloo, Ottawa, London and the rest of the province, remotely and on site when it helps.
Where does our data go?
Agents run in your own accounts, with the least access they need. When data residency matters we use Canadian cloud regions, and client data is never used to train public models.
How do we start?
With a fixed-scope pilot on one workflow. We measure today’s baseline, build the agent, run it in shadow mode beside your team, and end with a written go or no-go.
Which tools do you build with?
Whatever fits your business: Microsoft 365, Google Workspace, Notion, Jira and your CRM or accounting system on the work side; ChatGPT, Claude, Gemini (including Google AI Studio) and open models for reasoning; n8n, Make.com, Zapier or Python for AI workflow automation; and Azure or Google Cloud when it needs to run as code.
Do you build AI workflow automation with n8n, Make.com or Zapier?
Yes. We often start with n8n, Make.com or Zapier because they are quick to build and easy for your team to see. We add ChatGPT, Claude or Gemini steps where judgement is needed, and approval gates, cost caps and logging so the automation is safe to run on real client work.
What is an AI manager?
An AI manager looks after your AI agents the way a manager looks after a team: watching quality and cost, learning from your edits, fixing what drifts, reporting results every month and planning which agent to add next. archCTO plays that role after go-live, so your agents keep improving instead of quietly breaking.