FishVue AI
AI-assisted review that fast-forwards analysis while keeping human validation at the helm.
AI Capabilities
Built to reduce review time without reducing accountability.
Move directly to key moments
Reduce time spent on uneventful footage.
FishVue AI uses object-detection models to highlight moments of interest so reviewers can focus on relevant activity instead of scanning full trips end-to-end. This supports faster review while keeping decisions transparent and reviewer-driven.
- Object-detection models surface moments of interest
- Supports faster navigation through long trips
- Designed to help reviewers focus on relevant activity
- Keeps reviewer validation central to outcomes
Controls that tune assisted review
Detections appear on the Interpret timeline.
FishVue AI is designed to fit into Interpret, not sit beside it. Detections load into the same timeline-based environment used for validation and documentation, with controls that help reviewers tune detection behavior and movement through non-detection segments. This keeps analysis centralized and supports consistent reporting workflows.
- AI detections load into FishVue Interpret for review
- Detections can be filtered to focus on what matters
- Playback presets support faster assisted review
- Status monitoring supports predictable workflows
Apply multiple models to one dataset
Avoid fragmented, vendor-by-vendor processing.
FishVue AI is positioned as a unified pipeline for fisheries AI workflows. Data can run through multiple tools in sequence, producing outputs that return to Interpret where reviewers validate results and complete reporting. This reduces operational friction and supports consistent analysis across programs.
- Multi-stage pipeline supports multiple AI tools
- Outputs delivered into Interpret for validation
- Designed to reduce workflow fragmentation
- Supports consistent AI-assisted review delivery
Faster review at fleet scale
Supports up to ten simultaneous feeds.
Multi-camera deployments create large volumes of footage that can overwhelm manual search. FishVue AI supports detection across up to ten camera feeds and integrates results into Interpret so reviewers can move quickly to key moments, confirm details, and complete reporting with less time spent scanning.
- Supports detection across up to ten camera feeds
- Guides reviewers to key moments for validation
- Reduces time spent searching long trips
- Outputs support faster, review-ready reporting
Deployment, Improvement, and Governance
A practical pathway from evaluation to operational use.
Improve performance with every dataset
AQUA enables ongoing model improvement.
FishVue AI is built with an improvement loop, not a one-time model drop. Incoming datasets are profiled and auto-annotated, then human-in-the-loop validation informs retraining using AQUA. Over time this supports smarter inference and a more time-saving review experience inside Interpret.
- Auto-annotation supports scaling training workflows
- Human-validated insights feed retraining
- AQUA training tool supports model refinement
- Designed to improve inference and review efficiency
Built-in connectivity for repeatable processing
Model selection and analysis configuration available.
FishVue AI integration is designed to operate as part of the FishVue ecosystem. Interpret provides configuration for server endpoints and models, tracks analysis status, and supports monitoring for both the server and the data agent. This supports repeatable delivery when datasets are large and timelines matter.
- Automatic AI server discovery with manual override
- AI model selection supported within Interpret
- Analysis status tracked through clear states
- Data agent supports background video upload
- Status monitoring covers server and data agent
Start small, scale as value proves out
Support and training for workflow adoption.
Adoption is treated as a workflow change, not just a feature switch. Materials describe evaluation on client data, scaling usage as efficiencies grow, and guided onboarding and support to help teams integrate AI-assisted review into day-to-day delivery without disrupting reporting expectations.
- Supports evaluation on program-relevant datasets
- Designed to scale usage as efficiency increases
- Remote monitoring and support model described
- Training and onboarding support workflow change
