The complete solution for fisheries monitoring

Sinay unifies REM, onboard observers, and AI data into one system designed for national programs. Cover everything from deployment to compliance-ready reporting at any scale.

Programs we helped build

OBSCAMe

OBSmer

CEFAS

The problem

Fisheries monitoring breaks down as you go from 10 to 100 vessels

Multiple systems, no single view

REM, onboard observers, logbooks, and external data live in separate formats and tools.

Processing slows with growth

As fleets grow, data and review volume increase. Video analysis, data handling and reporting become bottlenecks.

Data is hard to trust and defend

Different sources require manual reconciliation. Outputs are difficult to validate and defend during audits.

Sinay Fisheries Monitoring

One scalable system for REM, observers, and reporting

Sinay’s monitoring platform replaces fragmented environmental processes with continuous, automated intelligence.

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REM Hours
Industrial-scale data processing
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Days at Sea
On-board observers deployed
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Vessels Equipped
Active operational fleet

One system designed to grow

Our system supports everything from pilot vessels to full fleets without requiring any new configuration. Camera setup, sampling, and processing capacity flex as needed.

AI processing validated by expert observers

We use AI to pre-process REM footage, detect events, and reduce review volume. Trained reviewers validate and annotate data, then combine it with observations & other sources to maintain consistency.

All monitoring data stays in one place

REM data, observer records, logbooks, and external data sources are unified in a single system. It’s standardized, time-aligned, and linked to vessel activity for consistent analysis and reporting.

Data designed for regulatory use

All data is timestamped, vessel-linked, and traceable to source records. Standardized datasets and reports align with regulatory requirements and are ready for audit and submission.

What our customers say

Hear from our customers

Fisheries are what we know. Tech is how we help them.

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in-house observers

Ifremer-certified reviewers and AI specialists ensure consistent, validated data.

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years of field experience

Our species specialists know all about marine mammals, elasmobranchs, and seabirds.

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vessels monitored

Our multi-gear, multi-species programs include gillnetters & trawlers.

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days at sea

We have extensive onboard observation experience across commercial fisheries and monitoring programs.

Frequently asked questions

We’re here to help with all your questions and answers in one place. Can’t find what you’re looking for? Reach out to our support team directly.

What is Remote Electronic Monitoring (REM)?

REM uses cameras and sensors installed on fishing vessels to record fishing activity. The footage is then analyzed — using AI and trained reviewers — to monitor catch composition, bycatch events, and compliance with fishing regulations.

Sinay supports all major commercial vessel types including gillnetters, trawlers, longliners, seiners, and potters. Our REM hardware and platform are gear-agnostic and can be configured for any fishing method.

Our AI pre-screens REM footage to detect and flag key events — catch hauls, bycatch, discards, and species interactions. This dramatically reduces the volume of footage that human reviewers need to watch, while Ifremer-certified observers validate every flagged event for accuracy.

Yes. Sinay currently operates the OBSCAMe program with 110+ vessels and has managed monitoring programs for French and UK authorities. Our platform is designed for fleet-wide deployment with centralized data management and reporting.

Reports are generated in formats required by local regulatory authorities — including Ifremer, CEFAS, and DPMA standards. All datasets are timestamped, vessel-linked, and traceable to source records for full auditability.

Talk to a fisheries monitoring expert

Whether you’re launching a new program or scaling an existing one, our team will assess your requirements and recommend the best approach.