Initiative #245

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Object, Classification, Tagging, Organization, and Pattern Understanding Solution (OCTOPUS)

Listed in the registry Development Original language : English

AI Strategic Operating Model (AI-SOM) Phase A — AI Strategy · Upcoming

AI documentation & artifact progress

Pre-phase

PRE Pre-phase

We are here

Phase A — AI Strategy

A.1 Intake & Concept Case

A.1.1 Gather information and generate the Concept Case

Not started : Concept Case
Not started : Statement of Sensitivity (SoS)

Phase B — AI Discovery

B.1 Outcome-Based Roadmap, High-level Architecture, VoAI, and AI assessment

B.2 Comprehensive Stakeholder Meeting (AI Review AIRB)

B.1.1 Outcome-Based Roadmap and feasibility validation

B.1.2 AI Technical Architecture Review

B.2.1 AIRB presentation

Not started : Outcome-Based Roadmap
Not started : High-level Architecture
Not started : ATIP Assessment
Not started : Cyber Assessments (SoS, SA&A, SIP, Audits)
Not started : DERAI — Pilot Assess
Not started : RISK — Cost, People, Technology

Phase C — AI Development

C.1 AI Model/RAG Development Plan

C.1.1 AI Pilot Development

C.1.2 AI model testing, evaluation and fine tuning

Not started : DERAI — Pilot Address
Not started : DERAI — Production Assess

Phase D — AI Delivery

D.1 Product Testing, Development, Approvals & Deployment

D.1.1 Deployment Validation

D.1.2 AI Review Approval

D.1.3 Production Release

D.1.4 Monitor Results

Not started : AI Production Assessment (AIR — final/approved)
Not started : Production readiness assessment
Not started : DERAI Monitoring plan / monitoring configuration
Not started : Operational support and ownership documentation
Not started : Approval records (e.g., CDOS CAB decision), if required

About the initiative

Description of the initiative

This initiative leverages AI technologies to build an Object, Classification, Tagging, Organization, and Pattern Understanding Solution (OCTOPUS) to enhance the analysis of video, image, and audio data, improve monitoring capabilities and support decision-making processes at DFO. The MVP will initially focus on video processing capabilities, with planned expansion to image and audio analysis in FY 2026–27. In addition, the initiative will deliver integrated data annotation and model training tools to support continuous improvement and reuse of AI models.

Problem statement

Scientists and Conservation & Protection teams rely increasingly on large volumes of video, image, and audio data (e.g., vessel cameras, remote sensors, aerial imagery, underwater monitoring). Today, the analysis of this data is largely manual, fragmented, or vendor-dependent, creating significant operational challenges. This initiative creates an opportunity to transform how video, image, and audio data are used by introducing AI-assisted analysis that is faster and scalable when compared to manual reviews.

AI family

Perception and Understanding

AI capability: Anomaly Detection and Environmental Monitoring

Bucket rationale

This project relates to the foundational pieces of taking videos (and later photos) to identify species.

Lifecycle

Ideation

Stage status : Completed

January 28, 2026
Assessment

Stage status : Completed
Approved

Stage status : Completed
Development

Stage status : In progress
Pilot

Stage status : Upcoming
Production

Stage status : Upcoming
Archived

Stage status : Upcoming

Schedule for this initiative

Completed
In progress
Planned
Not applicable
Today

2026 Jan Feb Mar Apr May Jun Jul Aug Sep

Ideation

A similar need?

Nobody has come forward yet. If your team faces the same problem, say so: it helps bring initiatives together and share a solution.

Contacts

Requester: Ibrahim, Omar
Subject matter expert: Ibrahim, Omar
Approver (DG): Ruel, Jean-Francois

Data and tools

Sector: Chief Digital Officer
Region: National Capital Region
Could this initiative be shared with the Treasury Board Secretariat?: Yes
Submitted on: January 28, 2026