Organizations are under growing pressure to use data for analytics, research, AI and other secondary purposes, but assessing and managing privacy risk in anonymized or de-identified data remains difficult to do well, hard to scale and challenging to document. Even when organizations understand the need to assess re-identification risk, inference and other privacy risks, they often lack a practical way to apply rigorous methods consistently across datasets and decisions. The challenge becomes even greater when a risk assessment identifies areas of concern: teams then need to specialized expertise to understand what is driving the risk, decide which transformations may reduce it, apply those transformations without destroying the value of the data, reassess the dataset to determine whether the risk has been reduced enough for the intended use, and automatically produce the necessary robust evidence to support the assessment results. Join us for a fireside chat-style webinar on June 23rd at 11 am EDT. Dr. Khaled El Emam, CEO and Founder of Woodway Assurance, and Carole Piovesan, Co-Founder and Principal of INQ Consulting, will discuss and showcase how new AI-assisted approaches can help teams move through the full cycle of privacy risk assessment, data transformation, reassessment and evidence generation. Such AI agents make it easier for data analysts and business users to understand the risks in their data and to be guided through the steps to reduce and to manage that risk. This kind of AI sidekick democratizes re-identification risk assessments that work across jurisdictions.

OneTrust Data Guidance has published an article by Woodway Assurance Founder and CEO Khaled El Emam examining how new guidance from Ontario’s Information and Privacy Commissioner brings greater clarity and structure to anonymization practices for AI and secondary data use. The article explores key issues including re-identification risk, public versus non-public data sharing, quantitative risk assessment and inference evaluation — and explains how organizations can take a more practical, defensible and scalable approach to responsible data use.

On May 20, 2026, Woodway Assurance hosted a webinar examining the growing challenges organizations face in demonstrating that anonymized data meets evolving privacy requirements for analytics, research and AI. 

Strong privacy frameworks are the key to unlocking health data at scale for AI. Join us in Barcelona for this half-day briefing, on June 12^th from 1 to 5 pm, focused on anonymization strategies for building AI-ready health datasets. The workshop is delivered by Khaled El Emam, Founder and CEO of Woodway Assurance, and Lisa Pilgram, Head of Operations, Ottawa Medical AI Research Institute, Postdoctoral Fellow, University of Ottawa, and Clinician Scientist, Charité – Universitätsmedizin Berlin. Executives will learn how risk-based anonymization methods satisfy regulatory requirements and accelerate model development, enabling confident data reuse across multiple jurisdictions. The briefing will cover techniques for meeting the anonymization / de-identification requirements in the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA).

On April 20, 2026, PwC and EviData^TM by Woodway Assurance brought together leaders working across AI, privacy, risk and governance for a timely discussion about what it will take to move from AI ambition to responsible implementation.

Woodway Assurance today is unveiling a new EviData™ feature designed to help organizations better understand, assess and address anonymization risk in response to requirements in Quebec privacy regulations and expectations under the E.U.’s General Data Protection Regulation (GDPR). The company will launch the new capability later today at an event in Toronto co-organized with PwC Canada focused on AI risk, privacy and governance.

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For organizations operating nationally in Canada, Quebec’s anonymization requirements have added a new layer of complexity to data use for analytics, research and AI. In particular, the Quebec anonymization regulations introduce new concepts to the definition of identifiability in a Canadian context, although they have been part of the expectations under the EU’s General Data Protection Regulation (GDPR). For example, concepts such as “inferences” need to be defined and evaluated in data to demonstrate that they meet the anonymity requirements. In practice, many organizations still struggle to interpret these requirements, apply them consistently and produce the necessary evidence for governance, review and approval. Join us on May 20th, 2026 at 11 am EDT for a webinar that will explain what the anonymization requirements mean in practical terms, with a focus on understanding and assessing inference and other privacy risks in anonymized data. Drawing on current regulatory developments and real-world implementation challenges and solutions, we will show how organizations can take a more rigorous and scalable approach. Participants will see how new technologies and standards can help automate these assessments and gives teams a more complete view of privacy exposure, including inference considerations.

On April 8th, 2026, Woodway Assurance hosted a practical webinar focused on what good de-identification looks like and how LLMs can support the review and analysis of privacy documents in the context of data sharing. 

Across data access and data-sharing initiatives, teams rely on a growing set of documents to demonstrate good privacy practices — from de-identification methodologies to data-sharing agreements and risk assessment reports. Join us on April 8 at 11 a.m. ET for a practical webinar on what a good de-identification process looks like and how LLMs can support the review and analysis of privacy documents in the context of data access and sharing. We’ll show how LLMs can strengthen the development and review of these documents, improving quality, consistency and completeness while accelerating the process. We’ll also demonstrate new technology that enables a fully automated re-identification risk assessment.

ARCHIMEDES, a national health data platform led by the University of Ottawa Heart Institute (UOHI), McGill University and the University of Ottawa,  announced today a strategic partnership with technology company Woodway Assurance to integrate its EviData software to expand secure, compliant data access and advanced analytics capabilities for users across the ARCHIMEDES platform. 

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