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Triumva AI label

Triumva AI label

Agency
Canada flagMoncton, Canada
www.triumva.ca
$19.99/hrExpert96+GDPR

Key Skills

Software

AWS SageMakerAWS SageMaker
Anno-MageAnno-Mage
AppenAppen
ArgillaArgilla
Axiom AI
ClickworkerClickworker
CloudFactoryCloudFactory
CrowdFlowerCrowdFlower
CrowdSourceCrowdSource
CVATCVAT
Data Annotation TechData Annotation Tech
DataloopDataloop
DatatroniqDatatroniq
DatumboxDatumbox
DatasaurDatasaur
DatatureDatature
DataturkDataturk
Deep SystemsDeep Systems
DiffgramDiffgram
DoccanoDoccano
EncordEncord
Figure EightFigure Eight
Google Cloud Vertex AIGoogle Cloud Vertex AI
HastyHasty
HiveMindHiveMind
HumanaticHumanatic
iMeritiMerit
Img Lab
Kili TechnologyKili Technology
LabelboxLabelbox
LabelImgLabelImg
Label StudioLabel Studio
LightTagLightTag
LionbridgeLionbridge
MercorMercor
Mighty AIMighty AI
MindriftMindrift
OneFormaOneForma
OpenCV AI Kit (OAK)OpenCV AI Kit (OAK)
PlaymentPlayment
ProdigyProdigy
Redbrick AIRedbrick AI
RemotasksRemotasks
RoboflowRoboflow
SamaSama
Scale AIScale AI
SlothSloth
Snorkel AISnorkel AI
SuperAnnotateSuperAnnotate
SuperviselySupervisely
Surge AISurge AI
TagtogTagtog
TolokaToloka
TelusTelus
Trilldata Technologies
VoTT
V7 LabsV7 Labs
Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage
TextText
VideoVideo

Top Task Types

Bounding Box
Classification
Prompt Response Writing SFT
Segmentation
Tracking

Company Overview

Triumva AI Label is a division of Triumva, a Canadian AI company dedicated to helping organizations accelerate the development of high-performance AI systems through precise, secure, and scalable data labeling services. Our mission is simple: turn raw data into reliable intelligence. We support companies building computer-vision, multimodal, and LLM-driven products by providing expertly labeled images, videos, and text—delivered with enterprise-grade quality and rigorous security. Our team combines experienced annotators with AI-assisted tooling to deliver fast, consistent labeling at scale. Triumva places a strong emphasis on privacy and information security; our operations follow strict access-control, encryption, and data-handling standards led by a team that includes CompTIA Security+ certified professionals. Triumva AI Label serves startups, research groups, and global enterprises across multiple sectors. We bring the engineering mindset of an AI firm,not a generic outsourcing vendor,ensuring that every dataset we produce is structured for model performance, reproducibility, and downstream automation.

ExpertFrenchEnglish

Security

Security Overview

Security & Privacy Overview Provide an overview of the security measures adopted by your company to safeguard client data and projects. Consider including information about: Physical security measures in your facilities (e.g., CCTV surveillance, secure access to workstations) Cybersecurity policies (e.g., secure network infrastructure, use of firewalls, antivirus software) Employee confidentiality and data handling (e.g., non-disclosure agreements, training on data privacy) Regular audits and compliance checks Describe your company's security measures here... Max. 2,000 characters

Security Credentials

GDPR

Labeling Experience

Instruction-Tuned Prompt + Response Dataset for Corporate LLM

Internal Proprietary ToolingTextPrompt Response Writing SFT
Triumva AI Label developed a high-quality supervised fine-tuning dataset for a company building its internal AI assistant. The team generated and curated 20,000+ prompt–response pairs, covering structured Q&A, reasoning tasks, business workflows, and safety-aligned responses. Each entry passed through a multi-tier review process including quality scoring, bias checks, clarity validation, and safety alignment. The dataset contributed to improved accuracy, reasoning depth, and task compliance of the client’s LLM.

Triumva AI Label developed a high-quality supervised fine-tuning dataset for a company building its internal AI assistant. The team generated and curated 20,000+ prompt–response pairs, covering structured Q&A, reasoning tasks, business workflows, and safety-aligned responses. Each entry passed through a multi-tier review process including quality scoring, bias checks, clarity validation, and safety alignment. The dataset contributed to improved accuracy, reasoning depth, and task compliance of the client’s LLM.

2024
CVAT

Aerial Segmentation Dataset for Land Cover Classification

CVATImageClassificationPolygon
Triumva AI Label performed fine-grained segmentation of drone and satellite images to support land cover classification and environmental monitoring. The project involved annotating 110,000+ high-resolution aerial images with polygons representing vegetation, water bodies, roads, rooftops, and terrain types. Strict QC workflows ensured annotation consistency across varying geographies and environmental conditions. Deliverables included both masks and metadata optimized for training geospatial AI models.

Triumva AI Label performed fine-grained segmentation of drone and satellite images to support land cover classification and environmental monitoring. The project involved annotating 110,000+ high-resolution aerial images with polygons representing vegetation, water bodies, roads, rooftops, and terrain types. Strict QC workflows ensured annotation consistency across varying geographies and environmental conditions. Deliverables included both masks and metadata optimized for training geospatial AI models.

2023 - 2024
CVAT

Video Tracking for Autonomous Robotics

CVATVideoObject DetectionSegmentation
Triumva AI Label worked on a complex computer-vision dataset involving multi-object tracking for a robotics navigation solution. The team labeled 92,000+ video frames, tracking pedestrians, obstacles, vehicles, and environmental elements to support motion prediction and path-planning models. The project included frame-to-frame object continuity checks, temporal QA validation, and cross-annotator consistency reviews to ensure robust model accuracy.

Triumva AI Label worked on a complex computer-vision dataset involving multi-object tracking for a robotics navigation solution. The team labeled 92,000+ video frames, tracking pedestrians, obstacles, vehicles, and environmental elements to support motion prediction and path-planning models. The project included frame-to-frame object continuity checks, temporal QA validation, and cross-annotator consistency reviews to ensure robust model accuracy.

2023 - 2024
CVAT

Product & Shelf Detection Dataset for Retail Vision AI

CVATImageBounding BoxClassification
Triumva AI Label annotated a large-scale dataset to train a retail vision model capable of detecting products, shelf positions, pricing tags, and out-of-stock events. The project included multi-class bounding boxes and pixel-level segmentation across diverse store layouts. Our team delivered over 450,000 labeled images, applying strict QA with multi-step validation and consensus review. The annotations supported model development for automated shelf monitoring and real-time inventory analytics.

Triumva AI Label annotated a large-scale dataset to train a retail vision model capable of detecting products, shelf positions, pricing tags, and out-of-stock events. The project included multi-class bounding boxes and pixel-level segmentation across diverse store layouts. Our team delivered over 450,000 labeled images, applying strict QA with multi-step validation and consensus review. The annotations supported model development for automated shelf monitoring and real-time inventory analytics.

2023 - 2024