LabelWorks
Production-grade labels for every data type
A skilled workforce, robust QA, and clear SLAs on every project.
Image & Video Annotation
Object detection, segmentation, classification, bounding boxes, polygons, keypoints, attributes, and frame-by-frame video labeling.
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Text Labeling
Sentiment analysis, entity recognition (NER), intent detection, categorization, content moderation, and document classification.
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Audio & Speech
Transcription, diarization, speaker tagging, keyword spotting, emotion/tone labeling, and language ID.
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Data Structuring
Dataset cleaning, normalization, taxonomy design, annotation guidelines, and file organization for ML pipelines.
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Datasets built for the model you're training
Computer vision datasets
Detection, segmentation and tracking labels for cameras, drones, retail shelves and vehicles — frame-accurate and QA-audited.
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NLP & document datasets
Labeled text for classifiers, chat assistants and moderation systems — sentiment, entities, intents and document types with consistent taxonomies.
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Speech & audio datasets
Transcripts and speaker labels for ASR and voice products — diarized, time-aligned and tagged for tone and language.
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Structured, training-ready data
Cleaned, normalized and organized datasets with taxonomies and annotation guidelines your ML pipeline can consume directly.
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From scoping to delivery,
a process built for quality
Every engagement follows the same four steps, so quality stays high and timelines stay predictable.
Scoping
We clarify goals, taxonomies, and quality thresholds.
Pilot
Small batch to validate instructions and QA.
Production
Scaled labeling with ongoing QC and feedback loops.
Delivery
Clean, well-structured datasets ready for training.
Industries we serve
We deliver labeled data for teams across a range of sectors, adapting taxonomies and QA to each domain.
Healthcare
Fintech
Retail & E-commerce
Mobility
Smart Home / IoT
Media & Entertainment
Healthcare
Fintech
Retail & E-commerce
Mobility
Smart Home / IoT
Media & Entertainment
Production-grade annotations, securely handled
Quality and data security are built into every stage of our workflow.
Multi-stage QA
Review + audit on every batch before delivery.
Clear instructions & gold-standard checks
Detailed guidelines and gold-set benchmarks keep annotators aligned.
Secure data handling and access controls
Controlled access and secure handling of your data end to end.
Data labeling questions?
We've got answers
Image and video (detection, segmentation, classification, bounding boxes, polygons, keypoints, frame-by-frame video), text (sentiment, NER, intent, categorization, moderation, document classification), and audio & speech (transcription, diarization, speaker tagging, keyword spotting, emotion/tone, language ID). We also structure datasets — cleaning, normalization, taxonomy design, and annotation guidelines.
Multi-stage QA with review plus audit on every batch, clear written instructions, gold-standard checks, and reviewer training. Quality thresholds are agreed during scoping and tracked throughout production.
A short scoping call to define goals, taxonomies, and quality thresholds, followed by a small pilot batch to validate the instructions and QA. Once the pilot is approved we move to scaled production and deliver clean, training-ready datasets.
Yes. Capacity is flexible and scales with your needs — elastic resourcing covers spikes and sprints without sacrificing QA.
Pricing and timelines are transparent and agreed up front after scoping, with clear SLAs and proactive communication throughout the project.
Data is handled under secure processes with access controls, and client datasets are used only for the agreed labeling work.