AI initiative registry
Every initiative listed in the registry can be consulted here, without an account. Each record shows its progress, its milestones and the history of its decisions. Requests still under triage do not appear: they join the registry once reviewed.
Infrastructure and Enablement
Supporting systems and services that make AI possible and scalable.
What is “Infrastructure and Enablement”?
This category includes the foundational tools, practices, and systems that support the development, deployment, and scaling of AI across an organization. These are not use cases in and of themselves, but they enable and govern AI use cases to exist safely, ethically, and efficiently.
| Subcategory | Description | Examples |
|---|---|---|
| Data engineering and pipelines | Collecting, cleaning, and organizing data | Automated ingestion from ocean sensors |
| MLOps and model management | Deploying and monitoring models in production | Retraining models, performance tracking |
| AI governance and ethics | Ensuring responsible AI use | Bias auditing, privacy controls, explainability tools |
- Key indicator
- If the work supports AI adoption, scaling, or trustworthiness — rather than delivering an AI function directly — it fits here.
- Focus
- Pipelines, platforms, governance, compliance, scalability, and lifecycle management.
Filter 1
12 current initiative(s)
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249
AI PlatformBuild a secure, scalable AI platform that extends the Enterprise Data Hub (EDH) and enables DFO teams to develop, deploy and govern AI solutions that will accelerate insights, support scientific discovery and uphold the highest standards of data quality, security, and ethical use.
Development Chief Digital Officer Infrastructure and Enablement
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230
Copilot Studio platform implementationWith the growing interest from CDOS and the rest of the department on custom AI Chat Bots and Citizen Development, there is an opportunity to increase IT enablement through the use of low code solutions. Since the department has already invested indirectly in the Power Platform, it makes sense to extend that investment into the proper implementation of Microsoft Copilot Studio which is another tool from the Power Platform rapid development platform.
Ideation Chief Digital Officer Infrastructure and Enablement
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227
Github CopilotGitHub Copilot is being piloted at DFO aimed at enhancing developer productivity and exploring the operational value of AI-assisted coding. Stats: (90-day period) - 27,584 lines of code were accepted - 17,801 prompts were accepted - Potential savings of $144K ($50/hour developer) based on 40 developers
Pilot Chief Digital Officer Infrastructure and Enablement
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226
DFO AI - PipelineDFO Pipeline Analyzer is a private Azure DevOps extension designed to assist development teams in diagnosing and resolving pipeline failures using AI. When a pipeline run fails, this task automatically triggers, extracts the provided error details, and queries a secure AI API to generate a human-readable explanation of the failure along with actionable troubleshooting steps. It will assist developers to make appropriate steps in right direction as they are getting suggestion with-in pipeline logs. Suggestion also provide corrected version of pipeline Key features: Runs only on pipeline failure (condition: failed()) Fully agent-agnostic: Works on self-hosted and Azure-hosted agents, across Windows, Linux, and macOS Provides clear error analysis and resolution guidance directly in pipeline logs Keeps your data secure by using your own OpenAI or other AI API key Fully private and scoped to your Azure DevOps organization We have working prototype of DFO-AI pipeline Analyzer by communicating with OpenAI securely. In next steps we are also exploring to integrate with our self-hosted AI Models (open-source via Ollama), currently in discussion
Pilot Chief Digital Officer Infrastructure and Enablement
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225
Data Innovation – Pacific Salmon Strategy InitiativeDiscover innovative data and artificial intelligence (A.I) projects addressing complex salmon data challenges made possible through strategic investments from the Pacific Salmon Strategy Initiative (PSSI). PSSI initiatives harness the power of advanced data and A.I. technologies like machine learning, computer vision, and natural language processing to revolutionize how to support salmon conservation and rebuilding efforts in the modern data and digital era. By integrating advanced data and A.I. technologies with program activities such as habitat restoration, ecosystem planning, sustainable fishery management practices, and collaborative efforts in Science, the PSSI leverages modern tools to enhance planning and data-driven decision-making. Together, these data and A.I. efforts create high quality and more accessible data and enable better insights and actions to protect and restore Pacific salmon and its ecosystems.
Ideation Infrastructure and Enablement
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155
A VPN-accessible data science environmentSet up a CDOS-managed Linux desktop to allow a safe and powerful data science environment where Scientists can sagely test data science tools on Protected B data prior to securing larger investment or engagement from CDOS, or without the need to deploy expensive cloud tools.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement
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112
ECCC exchanges on use of AI for ocean modellingExchanges with ECCC on implementation of machine learning methods for operational ocean forecasting, including potential uses for DFO models.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement
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111
Digital Twins of the Ocean Task TeamNational exchanges on topics relating to ocean modelling for development of Digital Twins of the Ocean, including use of AI for modelling and products.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement
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110
Mercator Collaboration on Digital Twins of the OceanKnowledge exchanges with ECCC and Mercator Océan International on use of AI for ocean modelling, in the context of Digital Twins of the Ocean.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement
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109
Advancing Support Systems to Understand the Ocean using AIA workshop will be hosted to identify international best practices and key considerations for using AI technologies to understand and predict the ocean.
Pilot Ecosystems and Oceans Science Infrastructure and Enablement
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73
Statistical Downscaling for the Ocean Working Group (SD-Ocean)The Canada-wide working group is open to researchers and practitioners in academia, government, and the non-profit sector. The WG will foster growth of a transdisciplenary research cluster at the forefront of the rapidly-developing field by sharing tools, devloping a network of practitioners, and working through specific examples (hackathons). The recent rapid growth in Artificial Intelligence (AI) provides a set of Machine Learning (ML) tools for statistical downscaling
Ideation Ecosystems and Oceans Science Infrastructure and Enablement
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37
OCDS AI PortalThe Office of Chief Data Steward (OCDS) currently has in its possession multiple proof-of-concept AI models developed that demonstrates the potential of AI in fisheries and oceans management. Due to a lack of deployment processes, the models currently sits idle in our repository. This initiative aims to develop a portal where the models can be deployed in a proof-of-concept fashion to enhancement DFO's understanding of AI and drive the cultural change needed to promote the adoption of AI at DFO. The portal has been completed and is accessible at: https://ocds-ai-portal.canadacentral.cloudapp.azure.com/ The portal was shared in the DFO kiosk at the 2025 GC data conference for engagement. It has so far welcomed 360 users, received over 2K views an
Pilot Strategic Policy Infrastructure and Enablement