Trusted by teams across Australia, North America and beyond
Sound familiar?
Why Toronto teams call us.
AI-native work in Toronto is fintech grade. Document and research agents for finance, personalisation for media, retrieval over regulated data, all judged against a real security and risk bar.
Toronto is Canada's financial and AI capital. Bay Street banks and the Vector Institute make it the densest commercial AI market in the country.
"We bolted a chatbot onto our product. It works in the demo and falls over with real users."
"Everyone says add AI. Nobody can tell us what to build, what it costs to run, or how we would know it works."
"Our prototype has no evals, no guardrails and no observability. We cannot ship it and sleep."
"Our token bill keeps climbing and we cannot tell which features or models drive it."
"We need an agent that does real work across our systems, not a wrapper around one prompt."
What we do
What an AI-native build actually includes.
Every engagement starts with a 30-minute call. If we cannot tell you something useful in that window, we do not take the work on.
AI-native architecture
We design the product around the model: where AI sits, where plain code sits, and where a human stays in the loop.
Agentic workflows
Agents that take real action across your systems, with safeguards that stop anything expensive or irreversible.
Retrieval that grounds answers
Chunking, hybrid search and re-ranking, plus the evals that prove answers come from your data.
Evals and observability
Tracing and quality monitoring, so regressions are caught before your customers find them.
Model routing and cost control
The large model where it earns its keep, smaller ones where it does not, and budgets wired in from day one.
AI UX that builds trust
Streaming, citations and graceful failure, so people trust the feature instead of abandoning it.
How we engage
Three ways to start. All begin with a call.
AI-Native Sprint
Two weeks to a working, evaluated prototype of your highest-value AI feature, with the architecture documented. Fixed scope, fixed fee.
from C$10K
Get a proposalAI-Native Build
Six to ten weeks to a production AI feature or product: agents, retrieval, evals, observability and cost controls, in your repo.
from C$50K
Get a proposalEmbedded AI team
A squad that builds alongside your engineers and leaves them able to run it. Two to four days a week, quarterly outcomes.
from C$12K/mo
Get a proposalCompliance and data
Built for Canadian rules from day one.
We design for PIPEDA, Quebec's Law 25 and Bill 96 where they apply, and ITSG-33 for public sector work.
We are headquartered in Sydney and work with Toronto teams remote-first, in your timezone, with on-site visits for kickoff and key milestones when needed.
Also in Toronto
Other ways we help Toronto teams.
Questions
What Toronto teams ask.
Straight answers to what Toronto teams ask before they book.
Are you based in Toronto?
We are headquartered in Sydney and work with Toronto teams remote-first, in your timezone, with on-site visits for kickoff and key milestones when needed. We work with teams across Financial District, MaRS Discovery District, King West and Liberty Village.
How fast can you start?
A two-week AI-Native Sprint can start the Monday after the scoping call. Larger engagements usually begin one to two weeks out.
Do you work in CAD and to Canadian rules?
Yes. We contract and price in CAD. We design for PIPEDA, Quebec's Law 25 and Bill 96 where they apply, and ITSG-33 for public sector work.
Which models do you build on?
We are model-agnostic: Claude, GPT, Llama and open-weight models, routed on cost and capability. We do not resell one vendor's stack.
Do you hand it over, or keep us dependent?
We hand it over. Code lives in your repo, the architecture is documented, and your team can run and extend it without us.
Can you build AI that clears a Bay Street vendor review?
Yes. PIPEDA-aligned controls, evals, guardrails and access logs, with Canadian data residency, documented for your risk team.
Can our data stay in Canada?
Yes. We deploy to Canadian cloud regions and document exactly where data, prompts and logs flow.
Do you actually build, or just advise?
Both, and we never advise without being willing to build. If the answer is Apache Superset, we stand it up. If it is a senior hire, we write the spec and sit on the panel.