Vancouver's applied agentic AI partner.
Train your team — or build the system.
Paul Save — ex-Microsoft, ex-Best Buy, ISO/IEC SC 42 AI standards expert. Pick the path.
Upskill your team with hands-on agentic workflows.
90-minute primers or full-day on-site builds. Your team leaves with deployed agents on your own data, not slides.
Deploy custom AI agents into your existing infrastructure.
Workflow audit to deployed agent in under 14 days. Consulting, custom builds, and process automation — with governance baked in.
Paul Save has been working in data science and machine learning since 2016 — full-time on AI Operations since founding CDSI in 2024.
Past Kaggle competitor across multiple machine learning competitions, including a top-10% finish (Bronze Medal) on an NLP classification challenge. 20+ conference presentations on AI, ML, and product topics — selected venues include Microsoft MLADS, Microsoft MVP Global Summit, AWS Initiate, Central 1 Momentum, and ProductCamps in Vancouver, Seattle, and Portland.
Shipped Microsoft Teams platform integrations that cut partner onboarding from 3 weeks to 1 day. Built a 0-to-1 multi-tenant ML platform on AWS at Central 1 Credit Union, with churn models exceeding 90% accuracy and 70% precision across Canadian credit unions.
Currently building iD8 — a multi-agent AI development platform with 50+ MCP tools, state-of-the-art memory systems, and production-grade governance primitives. Author of MarkCrawl, an open-source web crawler that ranked #1 in a published 7-tool benchmark for speed, extraction quality, and cost.
Expert on ISO/IEC JTC 1/SC 42 Artificial Intelligence — contributed to international standards on AI governance and safe deployment.
I speak about the work while I'm doing it.
Eighteen-plus engagements since 2013 — AI, responsible ML, data platforms, product leadership. All sourced, all dateable.
| Topic | Venue | Date |
|---|---|---|
| Mastering the Art of Pricing with Bayesian Inference | ProductBC · Microsoft Vancouver | MAY 2024 |
| Mastering the Art of Pricing with Bayesian Inference | ProductCamp Vancouver | APR 2024 |
| Individual Journeys in AI (panel) | ProductCamp Vancouver | APR 2024 |
| How to Win at a 6,000+ Team Hackathon | ProductCamp Vancouver | APR 2023 |
| AI/ML Product Leaders · Responsible AI + ChatGPT | ProductCamp Vancouver | APR 2023 |
| A PM Perspective on Writing a Stunning Resume | UBC Graduate Student Society | NOV 2022 |
| Big Tech or Startup — What's best for your PM career | ProductCamp Vancouver (main stage) | JUN 2022 |
| AI PM Virtual Breakout · Responsible AI | Microsoft MLADS | NOV 2021 |
| Product Management Masterclass | Acetech | MAR 2021 |
| Getting a Job in Data during COVID-19 | BCIT · BABI 9500 Capstone | JUL 2020 |
| Becoming a Data Science PM — Tales from the Trenches | ProductCamp Vancouver | MAR 2020 |
| Building a Data Lake in AWS | AWS Initiate Victoria | NOV 2019 |
| Personalizing the member experience with predictive analytics | Central 1 Momentum · Toronto | SEP 2019 |
| Machine Learning for Product Managers | ProductCamp Portland | MAR 2019 |
| Machine Learning — Why the Hype | ProductBC | JUL 2018 |
Start with a few lines on the problem.
Project context, rough scope, what you've tried. I reply within two business days. If it's a fit, we book a scoping call. If not, I'll point you at someone who's a better match.