Before GBC, I installed solar panels on residential homes and worked in the service industry for years: communications, events, management. People sometimes treat those jobs as one-track career paths. I treated them as places to learn things that actually matter: how to lead a project when the conditions aren't what you planned for, how to communicate with people who are counting on you, and how to build something that holds up when you're not around to watch it.
I moved back to Canada because of what this country values: looking out for the people around you rather than treating your own story as the main event. I want to make a positive difference for everyone, not just for myself. It's the reason I built something that specifically serves the sector doing the most important work.
I grew up serving people in soup kitchens and handing out clothing and resources to people in need. Those organizations, and the people running them, shaped how I understand what meaningful work looks like. The project management program at GBC gave structure to instincts that were already there.
I want them to feel confident when I say I can make their work more efficient while keeping what makes their organization unique.
Connor Jarvis · FounderI wasn't paying serious attention to AI in 2022 or 2023. The tools weren't capable enough to actually change how people work, and I knew it. That changed in 2024. I started experimenting in my own work and education, and once I understood what the tools could actually do, I started sharing it with students. That's how the Learning Labs started: free sessions to help people build a genuine understanding of AI before companies started requiring it of them.
What I kept seeing, as the space grew louder, were tools designed to remove people from their own work entirely. The pitch was that automation would lessen the burden. But when all the writing is handled by AI, there's no voice left, no authenticity in what gets produced. The organization loses the thing that made the work worth reading in the first place. A grant application can be faster to write and still sound exactly like the organization that wrote it. That's the difference I'm trying to make.
I want to work with nonprofits because they're doing the most important work while operating under the heaviest constraints. The research I've gathered describes organizations managing programs on skeleton teams, rebuilding grant applications from scratch each funding cycle because there's never time to document the last one, and watching institutional knowledge walk out the door every time someone leaves. They're not looking for a technology project. They want someone who understands what their team actually does, can find the specific workflows eating the most time, and can build something that gives that time back without asking them to become AI experts in the process.
Working with me follows four stages. Each one has the same goal: your team leaves the engagement understanding what was built and able to keep building without me.
Before anything gets built or agreed on, I need to understand where your team is and what's actually costing them time. This conversation has one job: figure out whether there's a real fit.
Every organization has different pressure points. This step maps yours specifically — which workflows eat the most time, where AI can genuinely help, and where it won't. You get a written report with clear recommendations before any build work begins.
The build isn't something I do alone and hand over. Your team is part of it; we work through each workflow together, and I explain what's happening and why at each step. By the time we're done, they've seen how it was built, not just what it does.
Written workflow documentation, an AI workspace configured to your organization's voice, and 30 days of async support. Everything is yours. A successful engagement is one where you come back six months later to show me a workflow your team built without me.
As a Project Management student at George Brown Polytechnic, I combine what I've been taught with everything I've been learning on my own. Both are happening at the same time, which means applying new AI techniques to the established methods. I've run 20+ Learning Labs for students and educators across the GTA, belong to the PMI Toronto Chapter, and I've built the AI workflows I teach into my own business before asking any client to trust them.
Based in Toronto, I work with organizations across the GTA. Being a solo founder means you work directly with me and don't get handed off to someone else. It also means I know my limitations precisely. I won't make a promise I can't deliver on.
