Data Annotation
Labeled, structured datasets prepared for machine learning, search relevance and internal tooling.
25+ real specialists
In short
- What it is
- Data Annotation is part of eData4You's Data Management service: labeled, structured datasets prepared for machine learning, search relevance and internal tooling.
- Who it's for
- Brands whose catalog or operational data has outgrown manual tracking - too large, too scattered across systems, or selling across channels with different data requirements.
Overview
A model is only as good as the labels it trains on - inconsistent or noisy annotation shows up later as a production blind spot. This is structured labeling across image, text, video, audio and point-cloud data, built to hold up at model-training scale.
Every batch runs through multiple QA passes with inter-annotator agreement scoring before delivery, with a quality metrics report attached, instead of only the labeled file.
Engagement scales up or down with your training cycles, since annotation demand is rarely constant.
Annotation covers every data type used to train AI: images for computer vision, text and NLP, documents and forms, video and audio. We also prepare fine-tuning datasets and provide dedicated annotation staff who work inside your own labeling tools and guidelines.
Without this
- Maintaining accuracy across millions of labeled assets
- Inter-annotator disagreement creating inconsistent labels
- Rare or ambiguous edge cases that create blind spots later
- Balancing labeling speed against quality standards
- Domain expertise gaps in specialized labeling tasks
- Keeping proprietary training data protected during annotation
- Inconsistent labeling degrading model training quality
- Inconsistent named entity tagging across a dataset
- Document processing models trained on inconsistently labeled layouts
What you should know
What's included
Image annotation - bounding boxes, polygons, segmentation, keypoints
Text annotation - NER, intent classification, sentiment, coreference
Video frame-level and temporal annotation
Audio transcription, speaker diarization and emotion labeling
LiDAR and 3D point-cloud annotation
Document layout and field-extraction labeling
Quality metrics reporting with inter-annotator agreement scoring
Bounding box annotation
Named entity recognition tagging
Document layout annotation
How we work
The Accountable Delivery Process
The same four phases run on every engagement, with the same team accountable end to end - not handed off between specialists who never see the whole picture.
Audit
We start with your current setup - listings, storefront, campaigns, workflows - and find what's actually costing you.
Plan
A scoped plan with clear priorities and timelines, agreed before any work starts.
Execute
One accountable team runs the work - the same people who scoped it deliver it.
Report
Regular reporting against the numbers that matter, not vanity metrics.
Engagement models
Project-based
A defined scope, deliverable and timeline. Best for a single launch, migration, or audit-and-fix.
Retainer
Ongoing monthly work against a recurring set of channels or tasks, for teams that need continuous coverage.
Dedicated team
Staff placed directly into your operation, working your hours and systems, when the gap is capacity rather than a defined project.
Why choose eData4You
- One accountable team - the same people who scope the work deliver it
- 17+ years in operation, 100+ global clients
- Distributed across India, North America & Europe for real-time coverage
- Transparent engagement models, no lock-in surprises
Industries we serve
Also covered on this page
Everything below is part of Data Annotation, handled by the same team.
Image Annotation for Computer Vision
Bounding boxes, polygons and segmentation labeled on product imagery to train visual search and recognition models.
Text & NLP Annotation
Named entity tagging, intent classification and sentiment labeling that trains search relevance and review analysis models.
Document & Form Annotation
Layout analysis, field extraction and table structure annotation for intelligent document processing pipelines.
Video Annotation for AI Training
Frame-by-frame object labeling and action tagging on product video content, prepared for AI and computer vision training.
Audio Annotation for AI Training
Speech transcription, speaker labeling and sentiment tagging on voice commerce and customer service audio.
AI Model Fine-Tuning Data Preparation
Clean, labeled datasets prepared and structured for fine-tuning AI models on your specific catalog, tone and use case.
AI Data Labeling & Annotation Staff
Dedicated staff labeling and annotating data for AI training, a seat you can scale up or down as model training needs change.
Frequently asked questions
Frequently asked questions
Bounding boxes, polygons, semantic segmentation, NER, sentiment analysis, video frame labeling, audio transcription and 3D point-cloud annotation.
COCO, YOLO, JSON, CSV or a custom schema, matched to what your pipeline expects.
24-48 hours for up to 1,000 assets, 3-5 business days for 1,000-10,000; larger projects are scoped individually.
Every project runs under NDA with role-based access and full IP assignment to you.
Multi-pass QA and inter-annotator agreement scoring on every batch.
Named entity tagging, intent classification, sentiment labeling and coreference annotation.
Forms, invoices, contracts and most standard business document formats.
Product videos, demo content and any video used for computer vision or AI training.
More from Data Management
More from Data Management
Start the conversation
Let's talk it through
Tell us where things stand with data annotation and we'll respond with next steps, no forms, no waiting in a queue.
- A specialist replies directly, not a support queue
- Whichever channel is fastest for you, call, WhatsApp or email
- No long-term contract to start the conversation