infrastructure
PF TECH builds the back-office systems, training, and tools that let non-profits focus on what they do best. Embedded operations support. Structured AI training. Purpose-built technology.
Three Streams. One Multiplier.
We don't just give you a tool and walk away. Our methodology combines technology, strategy, and team enablement to build sustainable impact.
The Mission Multiplier Program
Small-group coaching cohorts where non-profit professionals build practical AI and operational skills — together. Launching April 2026.
Embedded Back-Office Operations
A boutique portfolio of under 10 Canadian non-profits working with PF TECH on an ongoing basis. We embed into your operations — bookkeeping, payroll, grants, HR admin. This is co-creation, not consulting.

Built by the sector. Owned by you.
A guardrails-first back-office framework for non-profits. Every transaction is verified against accounting standards and your policies before it posts — not after.
Bring your own AI subscription, or we deploy a chat agent in Teams, Google Chat, or Slack.
Empowering the Change-Makers
Our team has been proud to support the operational and technical excellence of these impact-driven organizations.


















“The sector's administrative burden is an engineering problem, not a funding one. Non-profits aren't struggling with their mission — they're struggling with infrastructure that was never designed for them. We're building that infrastructure.”
Greg Zatulovsky, CPA
Founder & CEO
CPA Ontario Emerging Leader
Built with partners. Refined in the real world.
Every PF TECH tool starts as a real problem inside a Strategic Partner organization. We embed, identify the gap, build with our partners, test it live, and release it to the broader community. You're not getting theory — you're getting infrastructure that has already been running inside organizations like yours.
Values First
Built by non-profit leaders, for non-profit leaders.
Safe & Secure
PIPEDA-compliant. Canadian data residency. Enterprise AI endpoints only. No model training on your data.






