Forward-deployed AI engineering
Most AI projects stall somewhere between the demo and the day-to-day. A forward-deployed engineer closes that gap by working inside your team: in your standups, your tools and your data. They find the tasks worth automating, build the system, and stay until the people using it trust it.
What you get
- An engineer embedded in your team, working in your tools
- A ranked list of AI opportunities, scored by hours saved and risk
- Production AI features built in your codebase
- Evaluation suites that test the model against your real cases
- Monitoring, cost tracking and alerts once it's live
- Docs, runbooks and a handover your team can run with
A good fit if
- You have a backlog of AI ideas and nobody with time to build them
- A pilot worked in a demo but never reached your staff or customers
- Your data or workflows are too specific for an off-the-shelf tool
Tools we use
Hosted and open-weight language models · Python and TypeScript · Retrieval and vector search · AWS, Azure and Google Cloud
How an engagement runs
- 1
Embed
An engineer joins your standups, your chat and your tools, and learns how the work actually gets done, not how the process doc says it does.
- 2
Find the work
We map where the hours go and rank the tasks where AI pays off soonest. You approve the list before anything gets built.
- 3
Ship it
We build in your stack, test against your real cases, and put it in front of the people who will use it. Then we tune it from what they do.
- 4
Hand over
Your team gets the code, the docs and the runbooks. We stay on for support and the next item on the list, or step back. Your call.
Questions we hear
How is this different from hiring a consultant?
A consultant hands you a plan. A forward-deployed engineer writes the code, ships it, and supports it in production. You end up with working software rather than a slide deck.
Where does the code live?
In your repositories and your cloud accounts, from the first commit. Nothing is built somewhere you would have to migrate out of later.
Do you work on site?
We work remotely by default and come on site in Edmonton when being in the room helps. Either way, the engineer is in your channels and meetings like any other teammate.
Other practices
- AI agents and automationAgents and workflows that take repetitive work off your team: inboxes, documents, support and reporting.
- AI strategy and readinessA clear look at where AI fits in your business, what it will cost to run, and what to build first.
- Growth marketingSEO, content, campaigns and automation that bring in customers and show you what's working.
What would your team stop doing if it could?
Tell us where the hours go. We'll tell you straight whether AI, better software or better marketing is the fix, and what it would take.