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.

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197 current initiative(s)

AI initiative registry
ID	AI Initiative	Stage	Description	Sector	Region	AI Bucket	SME
66	Optical Character Recognition Data transcription tool (See B6, B26)	Pilot	Built a proof of concept tool to facilitate data transcription and validation from hand-written field notes. Tested on ~100 year old salmon...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Computer Vision	Bird, Tom
68	Stereo camera image analysis	Pilot	Tools built in python to automate image analysis and fish measurement tasks. Applications include a conveyor belt camera and underwater towe...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Computer Vision	Rooper, Chris
80	Various Built-In AI Features (Co-pilot, ChatGPT, etc)	Pilot	Using built-in AI features and functions in regular workflow operations. This includes LLM's such as ChatGPT, Microsoft Copilot, Gemini, and...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI Generative AI (text, images, code)	Quan, Eric
70	Data Validation Tool (See B6, B22)	Pilot	Use large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support Robotic Process Automation with AI	Bird, Tom
71	News topic detection tool	Ideation	Use large language models and topic clustering to read topics emerging in the news and detect which of those topics is relevant to DFO, as w...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI Knowledge Management	Bird, Tom
72	Extracting impacts data from regulatory documents	Ideation	Use OCR pdf readers, topic detection and language models to detect specific data elements inside written text documents, for extraction and...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Language Understanding (NLP)	Bird, Tom
73	Statistical Downscaling for the Ocean Working Group (SD-Ocean)	Ideation	The Canada-wide working group is open to researchers and practitioners in academia, government, and the non-profit sector. The WG will foste...	Ecosystems and Oceans Science	Pacific	Infrastructure and Enablement AI Governance and Ethics	Holdsworth, Amber
74	Pacific Plankton Monitoring: Imagery and automated classification	Pilot	• Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, Pl...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Computer Vision	Sastri, Akash
75	Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon	Ideation	The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be de...	Ecosystems and Oceans Science	Pacific	Automation and Decision Support Predictive Analytics	Thomson, Richard
76	Chumputer Vision - salmon scale age predictive AI (See B8)	Ideation	Deep Machine Learning and Convolutional Neural Network application for the predictive application of age assignment of Chum salmon by way of...	Ecosystems and Oceans Science	Pacific	Perception and Understanding Computer Vision	Wischniowski, Stephen
77	Emulator for OPP port models and for relocatable ocean modelling system	Ideation	Use machine learning to develop an emulator (or similar) for the OPP port models, which would be used to produce forecasts via inference. Th...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI Simulation and Digital Twins	Dunphy, Michael
78	Okanagan sockeye life cycle model	Pilot	Using LLM (ChatGPT) to support the development of a statistical lifecycle model for Okanagan sockeye. LLMs are not developing the models but...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI Generative AI (text, images, code)	Thompson, Patrick
79	Biological models to support prioritzing salmon stocks under future climates	Ideation	This project fits retrospective, life stage-specific models in a data-driven analytical framework to evaluate functional responses to climat...	Ecosystems and Oceans Science	Pacific	Cognitive and Generative AI Simulation and Digital Twins	Thompson, Patrick
246	GeoAI	Ideation	Overview: Potential GeoAI‑Impacted Programs and Processes GeoAI (the integration of geospatial data, AI, and machine learning) is being exp...	Chief Digital Officer	Not region specific	Automation and Decision Support Predictive Analytics	Merner, Erick
240	The Current	Development	Don't let your harvested data get stuck in still water. Navigate new data streams with AI automation, augmentation and information enableme...	Fisheries Management	Not region specific	Perception and Understanding Multimodal AI	Bird, Tom
231	Smart Assyst	Ideation	Assyst is point of entry to all CDOS service requests and it covers many of the ITIL and ITSM practices which is the foundation of any IT or...	Chief Digital Officer	National Capital Region	Interaction and Engagement Conversational AI and Virtual Assistants	Laplante, Stéphane
229	DFO PB LLM Service	Pilot	Provide an approved DFO internal LLM as a service in a PBMM environment. After our team performed a year-long pilot project providing an unc...	Chief Digital Officer	National Capital Region	Cognitive and Generative AI MLOps and Model Management	Korol, Oksana
228	SILScanner	Pilot	Deploy on DFO's PBMM Cloud a proof of concept application that uses optical character recognition (OCR) to digitize and validate Stream Insp...	Chief Digital Officer	National Capital Region	Perception and Understanding Computer Vision	Bird, Tom
227	Github Copilot	Pilot	GitHub Copilot is being piloted at DFO aimed at enhancing developer productivity and exploring the operational value of AI-assisted coding....	Chief Digital Officer	National Capital Region	Infrastructure and Enablement Generative AI (text, images, code)	Balbona, Joseph
226	DFO AI - Pipeline	Pilot	DFO Pipeline Analyzer is a private Azure DevOps extension designed to assist development teams in diagnosing and resolving pipeline failures...	Chief Digital Officer	National Capital Region	Infrastructure and Enablement MLOps and Model Management	Mehdi, Ghizal
224	Remote Observation of Watercraft on Roads	Pilot	The Aquatic Invasive Species Program is proposing to launch a pilot initiative aimed at addressing a critical knowledge gap in our understan...	—	Ontario and Prairie	Perception and Understanding Computer Vision	Klein, David
222	Automated assessment of Crowd Source Bathymetry	Pilot	The Community Hydrography team is working with the University of New Brunswick (UNB) on a tool-kit that will automate the assessment of larg...	Ecosystems and Oceans Science	Ontario and Prairie	Automation and Decision Support Robotic Process Automation with AI	Klein, David
221	Automated Paper Chart Solution	Pilot	CHS is working closely with software provider CARIS to test and implement automated solution to generate Paper Charts from digital data sour...	Ecosystems and Oceans Science	Ontario and Prairie	Automation and Decision Support Robotic Process Automation with AI	Klein, David
220	Development of an underwater videography and AI system for studying fish passage effectiveness	Pilot	Designed to train existing DFO tools with information on fish passage effectiveness and develop an SOP for training videography-based AI mod...	Ecosystems and Oceans Science	Ontario and Prairie	Perception and Understanding Computer Vision	Klein, David
219	Fish-Habitat Associations	Ideation	Extraction of relevant habitat association info and strengths based on vetted literature input to AI for synthesis. Goal to improve equival...	Ecosystems and Oceans Science	Ontario and Prairie	Cognitive and Generative AI Knowledge Management	Klein, David

66
Optical Character Recognition Data transcription tool (See B6, B26)
Built a proof of concept tool to facilitate data transcription and validation from hand-written field notes. Tested on ~100 year old salmon observations and present-day salmon stream inspection logs to determin ethe cost/feasibility/effectiveness of implementing such a tool in Salmon monitoring contexts. (Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format) Computer vision (azure document intelligence),

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
68
Stereo camera image analysis
Tools built in python to automate image analysis and fish measurement tasks. Applications include a conveyor belt camera and underwater towed stereo camera system Computer vision tools (Python, Viame)

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
80
Various Built-In AI Features (Co-pilot, ChatGPT, etc)
Using built-in AI features and functions in regular workflow operations. This includes LLM's such as ChatGPT, Microsoft Copilot, Gemini, and various others that are integrated directly into the applications already currently being used. Large Language Models

Pilot Ecosystems and Oceans Science Cognitive and Generative AI Generative AI (text, images, code)
70
Data Validation Tool (See B6, B22)
Use large language models to help detect errors in data transcribed using optical character recognition. Apply validation rules to propose corrections and normalize data into a standardized format. (Digitizing non-machine-readable (handwritten) documents and extracts characters into a digital format) Llama 3.0 Large Language Model

Pilot Ecosystems and Oceans Science Automation and Decision Support Robotic Process Automation with AI
71
News topic detection tool
Use large language models and topic clustering to read topics emerging in the news and detect which of those topics is relevant to DFO, as well as what knowledge DFO has available to address those topics. Large Language Models

Ideation Ecosystems and Oceans Science Cognitive and Generative AI Knowledge Management
72
Extracting impacts data from regulatory documents
Use OCR pdf readers, topic detection and language models to detect specific data elements inside written text documents, for extraction and analysis in a cumulative impacts context. Large lanugage models and topic clustering tools

Ideation Ecosystems and Oceans Science Perception and Understanding Language Understanding (NLP)
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 AI Governance and Ethics
74
Pacific Plankton Monitoring: Imagery and automated classification
• Monitoring of zooplankton and phytoplankton in the water column with shipboard and benchtop plankton imaging instruments (UVP, ZooScan, PlanktoScope). • Application of automated classification of survey and preserved sample image data sets to complement and enhance spatial and temporal resolution of monitoring in Canada’s EEZ and offshore NE Pacific. Development of and regular optimization of automated image classification models using AI: deep learning (residual networks) and machine learning (random forests) methods.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
75
Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon
The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be developed to predict salmon behaviour as functions of ocean conditions. classical machine learning models, including linear regression, Ridge regression, and Random Forest

Ideation Ecosystems and Oceans Science Automation and Decision Support Predictive Analytics
76
Chumputer Vision - salmon scale age predictive AI (See B8)
Deep Machine Learning and Convolutional Neural Network application for the predictive application of age assignment of Chum salmon by way of scale images. Chum salmon has been selected as the gateway species due to its relatively easy scale pattern interpretation, this will foster the pathway forward for Chinook, Coho Sockeye and Herring as future targets for AI age interpretation. Deep Machine Learning and Convolutional Neural Network within a Python predictive algorithm

Ideation Ecosystems and Oceans Science Perception and Understanding Computer Vision
77
Emulator for OPP port models and for relocatable ocean modelling system
Use machine learning to develop an emulator (or similar) for the OPP port models, which would be used to produce forecasts via inference. The inference is expected to be both faster and computationally cheaper than existing solutions. The training process would use existing model output from multi-year hindcasts. Success with a fixed location would graduate to developing a relocatable emulator TBD; could be U-Net or CNN, or based on GraphCast

Ideation Ecosystems and Oceans Science Cognitive and Generative AI Simulation and Digital Twins
78
Okanagan sockeye life cycle model
Using LLM (ChatGPT) to support the development of a statistical lifecycle model for Okanagan sockeye. LLMs are not developing the models but are used to brainstorm modelling approaches, debug code, and confirm that written model descriptions in manuscripts are accurate and clear. AI is not being tasked with developing these models. Large Language Models

Pilot Ecosystems and Oceans Science Cognitive and Generative AI Generative AI (text, images, code)
79
Biological models to support prioritzing salmon stocks under future climates
This project fits retrospective, life stage-specific models in a data-driven analytical framework to evaluate functional responses to climate variables across the salmon life cycle and make projections for how stocks will respond to climate change scenarios. This modelling approach is intended to be sufficiently flexible to incorporate variability in data quality. Large language models are being used to brainstorm modelling approaches and debug code. AI is not being tasked with developing these models. Large Language Models

Ideation Ecosystems and Oceans Science Cognitive and Generative AI Simulation and Digital Twins
246
GeoAI
Overview: Potential GeoAI‑Impacted Programs and Processes GeoAI (the integration of geospatial data, AI, and machine learning) is being explored to enhance decision‑making, efficiency, and service delivery by automating spatial analysis, identifying patterns at scale, and enabling predictive insights. 1. Program and Service Delivery GeoAI can support more targeted, timely, and evidence‑based services by: Identifying spatial patterns in environmental, socio‑economic, or ecological data Prioritizing areas for intervention, monitoring, or investment Improving accessibility and equity of services through location‑based insights Examples Risk‑based prioritization of inspections, monitoring sites, or enforcement activities Predictive habitat or species distribution mapping to support conservation or fisheries management Enhanced situational awareness for emergency response or environmental incidents 2. Operational Efficiency GeoAI enables automation and scalability in routine or data‑intensive operations, reducing manual effort and turnaround times. Examples Automated feature extraction from satellite imagery, aerial photos, or LiDAR (e.g., shoreline change, infrastructure, habitat types) Near‑real‑time monitoring of environmental conditions or operational assets Change detection to flag anomalies or emerging risks Operational Benefits Reduced reliance on manual digitization and visual interpretation Faster updates to spatial products and dashboards More consistent and repeatable analytical outputs 3. Business Processes and Decision Support GeoAI can modernize internal business processes by embedding spatial intelligence into planning, reporting, and governance workflows. Examples Predictive analytics to support long‑term planning and scenario analysis Decision‑support tools that integrate geospatial, operational, and administrative data AI‑assisted data quality assessment and metadata generation Process Impacts Improved transparency and defensibility of decisions Better integration of spatial data across programs and systems Enhanced performance measurement and outcome tracking 4. Cross‑Cutting Opportunities Across all domains, GeoAI supports: Data integration: Linking spatial, temporal, and non‑spatial datasets Scalability: Applying consistent analysis across large geographic areas Innovation: Enabling new analytical questions that were previously impractical

Ideation Chief Digital Officer Automation and Decision Support Predictive Analytics
240
The Current
Don't let your harvested data get stuck in still water. Navigate new data streams with AI automation, augmentation and information enablement. The Current is a cloud-hosted platform that enables users anywhere in the department to ingest large volumes of structured and unstructured documents, extract data using optical character recognition and large language models, validate and review results through human-in-the-loop workflows, and relate extracted information using shared concepts and standards. The architecture emphasizes asynchronous processing, modular extraction services, strong traceability, and governance-ready design. The platform supports configurable extraction tasks, versioned models and definitions, auditable review processes, and future discovery of related research outputs and datasets across heterogeneous sources. As the initial use-case, the Text Intelligence and Data Extraction (TIDE) Service has been developed for the Salmon Habitat Restoration (SHARE) System. TIDE is a baseline iteration of The Current that fulfills the minimum viable product requirements of SHARE. TIDE focuses on digitizing, extracting, and modeling data from large unstructured text documents. TIDE establishes the baseline architecture and demonstrates a scalable workflow in Production.

Development Fisheries Management Perception and Understanding Multimodal AI
231
Smart Assyst
Assyst is point of entry to all CDOS service requests and it covers many of the ITIL and ITSM practices which is the foundation of any IT organisation - and it has the potential to support most if not all of the ITIL and ITSM practices. The most recent versions of Assyst now have deeply integrated AI functionalities that are embedded in all parts and stages of the IT support process. It includes: A natively integrated Chat Bot for technicians and clients, AI ticket assignment, integration to MS Teams, recommended solutions, automated FAQ generation, natural language system search, risk prediction, conversational coding for Assyst developers, smart ticket assignment and escalation, summarization of knowledge articles, and more Activating and configuring those AI functionalities would require an investment in the Assyst system in order to make it AI ready. There is currently a lot of waste in the various CDOS ITIL practices due to a lack of investment in our ITSM tools. Modernizing Assyst to make it AI ready and turning on many of the newer AI features would joinlty contribute to reduce much of the waste incurred during the delivery of our CDOS services to the organization. It would also be a strong showcase both for CDOS and our clients of the power of AI integrated to a complete service process instead of the common and simple use case of AI conversational agents that may only produce limited and siloed value.

Ideation Chief Digital Officer Interaction and Engagement Conversational AI and Virtual Assistants
229
DFO PB LLM Service
Provide an approved DFO internal LLM as a service in a PBMM environment. After our team performed a year-long pilot project providing an unclassified internal GenAI models for 14 teams to develop their custom chatbots, we have collected feedback and identified gaps in the availability of GenAI at DFO. One of the biggest gaps was the need for a secure model to be used with private or classified data. Our cloud platform is certified up to PBMM, so we are working to identify, deploy and approve an internal large language model (LLM), as well as make it available to DFO users through API. IT security team is involved in helping us secure and certify the model for use at DFO.

Pilot Chief Digital Officer Cognitive and Generative AI MLOps and Model Management
228
SILScanner
Deploy on DFO's PBMM Cloud a proof of concept application that uses optical character recognition (OCR) to digitize and validate Stream Inspection Logs (SILs). The PoC was originally developed on SSC's cloud infrastructure. It is now being deployed in DFO PB cloud infrastructure. BLADES initiative and IT security teams are involved.

Pilot Chief Digital Officer Perception and Understanding Computer Vision
227
Github Copilot
GitHub 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 Generative AI (text, images, code)
226
DFO AI - Pipeline
DFO 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 MLOps and Model Management
224
Remote Observation of Watercraft on Roads
The Aquatic Invasive Species Program is proposing to launch a pilot initiative aimed at addressing a critical knowledge gap in our understanding the spread of aquatic invasive species. Invasive species can attach to boats, trailers, and related equipment—a process commonly referred to as the "stowaway pathway"—which enables their unintentional spread across ecosystems when watercraft are transported between water bodies. The AIS Program is seeking to understand watercraft movement into Canada via international land border crossings. Currently, the extent of this "stowaway" pathway remains largely unquantified. To address this, the pilot will deploy remote camera systems at select border entry points to capture imagery of incoming vehicles. Leveraging machine learning, the system will automatically identify and flag images containing watercraft. This data-driven approach will provide actionable insights to inform strategic decisions on the timing and placement of watercraft inspection and decontamination resources. This initiative may represent a significant step toward enhancing our ability to proactively manage aquatic invasive species risks at key entry points.

Pilot Perception and Understanding Computer Vision
222
Automated assessment of Crowd Source Bathymetry
The Community Hydrography team is working with the University of New Brunswick (UNB) on a tool-kit that will automate the assessment of large volumes of crowd source data. AI routines will allow for automated QC, and drafting of Navigation Warnings.

Pilot Ecosystems and Oceans Science Automation and Decision Support Robotic Process Automation with AI
221
Automated Paper Chart Solution
CHS is working closely with software provider CARIS to test and implement automated solution to generate Paper Charts from digital data sources. AI routines will improve speed and accuracy of solutions (machine learning) as software is refined to ensure product specifications are respected (as they are used for official navigation).

Pilot Ecosystems and Oceans Science Automation and Decision Support Robotic Process Automation with AI
220
Development of an underwater videography and AI system for studying fish passage effectiveness
Designed to train existing DFO tools with information on fish passage effectiveness and develop an SOP for training videography-based AI models in support of fish passage projects.

Pilot Ecosystems and Oceans Science Perception and Understanding Computer Vision
219
Fish-Habitat Associations
Extraction of relevant habitat association info and strengths based on vetted literature input to AI for synthesis. Goal to improve equivalency models used in regulatory decisions. Possible partnership with McMaster University.

Ideation Ecosystems and Oceans Science Cognitive and Generative AI Knowledge Management