Common Door
The connective layer where complex operations actually move.
Common Door designs and builds operational software for organizations whose work depends on coordinating people, data, and decisions across fragmented systems. Our focus is the layer between those systems — the integrations, workflows, and supervisory infrastructure that turn scattered tools into something operators can rely on.
We use applied AI where it earns its place: drafting, extracting, summarizing, and routing under human supervision. The point is not to replace operators but to compress the time between their judgment and the action it produces. Efficient operations are the actual subject of the work.
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Integration and workflow design
Connecting fragmented systems into coherent operational flows. We map how work actually moves through an organization, then build the connective tissue that lets information arrive in the right place, in the right shape, at the right time.
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Agentic infrastructure
The supervision layer where AI agents do real work safely under human oversight. Clear boundaries, reviewable steps, predictable behaviour — the scaffolding that lets autonomy be useful without becoming a liability.
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Data and decision tooling
Turning operational data into the inputs operators need at the moment of decision. Less reporting after the fact, more of the right context surfaced where the decision is actually made.
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System architecture
For organizations not served well by off-the-shelf software. We design systems that fit the real shape of the work, integrate cleanly with what already exists, and remain legible to the people responsible for them.
We build with humans in the loop by default. Automation handles the parts that benefit from being fast and repeatable; people stay where judgment matters. The systems we ship are auditable by design — what happened, who decided, on what evidence — because operations that can’t be reviewed eventually become operations that can’t be trusted.
Our work is built for the people doing the work, not for the people buying the software. That means short feedback loops with operators, interfaces that respect the rhythm of a real shift, and a willingness to remove things that don’t earn their place. We’d rather ship one quiet improvement that holds than a feature that demos well and decays in production.
We deploy in environments where data residency and accountability matter. Canadian hosting, clear data boundaries, and a posture that treats sensitive information as sensitive by default. The point is to make the responsible path the easy one.