We study how Canadian small businesses, newcomers, and nonprofits actually adopt technology — then we turn those findings into better programs, open-source tools, and practical guidance that the entire ecosystem can use.
We build tools in the open. Every project starts with a real problem faced by the communities we serve — and the code, data, and findings are published on GitHub so anyone can use, adapt, or contribute to them.
Organizations managing strata and condo documents need to answer questions across hundreds of pages of bylaws, minutes, and financial reports. Manual search is slow and error-prone. This RAG-powered conversational interface lets users ask natural language questions and receive AI-generated answers with source citations — eliminating the need to dig through lengthy documentation.
View on GitHub →Organizations dealing with mixed document types — native PDFs and scanned images — face a choice between expensive OCR-only pipelines and inaccurate text extraction. This hybrid service intelligently combines native PDF text extraction with OCR only when needed, optimizing for cost, speed, and accuracy. It includes smart table extraction, document categorization, and batch processing.
View on GitHub →People using wearable health monitors generate data scattered across multiple apps and devices with no unified view of their progress. This dashboard extracts data from health monitors and presents it through a clear, intuitive interface — allowing users to track their daily health metrics, spot trends, and take action on their well-being in one place.
Repo Coming SoonSecurity events need to be processed in real time to detect threats before damage is done. Traditional batch processing introduces dangerous delays between event occurrence and detection. This system uses Apache Kafka for high-throughput streaming and AI-powered processing to analyze security data in real time — enabling instant threat detection and automated response.
Repo Coming SoonGood research starts with good values. These principles guide every study we undertake, ensuring our work is both rigorous and genuinely useful to the communities we serve.
Research participants are not data points — they are collaborators. We co-design studies with the communities we serve, ensuring that research questions reflect real needs rather than academic curiosity. Participants review findings before publication and have a voice in how the research is applied. This approach draws on participatory action research traditions and is central to how TechMind operates.
All of our research outputs — reports, datasets, assessment tools, and implementation guides — are published under open licenses. We believe that publicly funded research should be publicly available, especially when it concerns the digital well-being of underserved communities. Our work is freely accessible on GitHub and through our website with no paywalls or registration requirements.
We measure the success of our research by whether it changes practice, not just by citation counts. Every study we publish includes a clear "so what" section with practical recommendations for small business owners, service providers, and policymakers. Our implementation research, for example, includes ready-to-use configuration templates and training curricula alongside the academic analysis.