Trusted by teams across Australia, North America and beyond
Sound familiar?
Why Edmonton teams call us.
Edmonton pairs Amii's AI research with heavy energy and agriculture — AI-native work here blends research-grade AI with industrial data.
Edmonton teams build AI-native products like copilots over energy and agtech operational data, agentic automation, and RAG over technical corpora — all needing evals, guardrails and clean grounding data.
We ship in your repo and run our own AI products, blending AI rigour with industrial reliability, designed for PIPEDA and Canadian residency.
Edmonton hosts Amii, one of Canada's three national AI institutes, next to a heavy energy and agriculture base — research depth with industrial demand.
"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 Edmonton teams remote-first, in your timezone, with on-site visits for kickoff and key milestones when needed.
Also in Edmonton
Other ways we help Edmonton teams.
Questions
What Edmonton teams ask.
Straight answers to what Edmonton teams ask before they book.
Are you based in Edmonton?
We are headquartered in Sydney and work with Edmonton teams remote-first, in your timezone, with on-site visits for kickoff and key milestones when needed. We work with teams across Downtown and the Ice District.
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 grounded in industrial data?
Yes — copilots and agents grounded in your operational data, with retrieval and evals to prove they work.
Which models do you build on?
Model-agnostic — routed on cost and capability.
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.