Data Annotation
Precise labels for images, video, text, audio and documents, following your guidelines exactly.
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AI Data Services
Human-powered training data for smarter AI
Annotation, data collection, transcription and model evaluation — delivered by trained teams with multi-layer quality checks, so your models learn from data you can trust.
Multi-layer QAReviewer passes, gold tasks and audits
Scalable teamsRamp up from pilot to production
ConfidentialNDA, access control, secure transfer
Tool-agnosticYour platform or ours
What We Offer
Everything your AI pipeline needs
Pick one service or combine them into an end-to-end data pipeline — from raw collection to labelled, reviewed, ready-to-train datasets.
AI Data Collection
Custom speech, image, video and text datasets captured from real people with informed consent.
Learn moreTranscription & Localization
Accurate, time-stamped transcripts, captions and translations for ASR training and media.
Learn moreData Labeling & Classification
Large-volume categorisation and tagging with consensus workflows for reliable ground truth.
Learn moreLLM & Chatbot Data
Prompt–response writing, conversation data and instruction datasets for generative AI.
Learn moreAI Model Evaluation
Human rating of model outputs — relevance, accuracy, safety and preference ranking (RLHF).
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Why BARG
Quality you can measure, pricing you can plan
We start every engagement with a small paid or free pilot, agree on clear guidelines and accuracy targets, and only then scale. You get predictable quality, transparent progress reports and a single point of contact.
Our team is based in Nellore, India, which gives you cost-effective, dedicated capacity with strong English communication and native speakers of several Indian languages.
What you can expect
- Written guidelines and calibration before production starts
- Gold-standard questions and second-pass review on every batch
- Consensus labelling for subjective tasks
- Weekly progress and quality reports
- Flexible volumes — from a few thousand items to large ongoing projects
- One dedicated project manager for your account
How We Work
From pilot to production in four steps
A simple, transparent workflow that keeps quality high as volumes grow.
Scope & Guidelines
We review your data, use case and edge cases, then write or refine the annotation guidelines with you.
Pilot Batch
A small pilot measures accuracy and speed, so you can approve quality before committing to volume.
Scale Production
Trained annotators work in your tool or ours, with daily throughput tracking and quick feedback loops.
QA & Delivery
Reviewed data is delivered in your format (JSON, CSV, COCO, YOLO and more) with a quality report.
Data Types
We work with every kind of data
Images
Video
Audio & Speech
Text
Documents & Forms
Conversations
Multilingual content
LLM outputs
Security
Your data stays protected
We treat every dataset as confidential. Security measures are agreed with you upfront and can be tailored to your organisation's requirements.
How we keep data safe
- NDAs signed with the company and every team member on your project
- Role-based access — annotators only see the data they need
- Work directly inside your secure platform or VPN when required
- Encrypted file transfer and no local copies on personal devices
- Data deleted or returned at project completion, as agreed
AI Data FAQ
Common questions from AI teams
What annotation tools do you work with?
We can work inside your own platform or in-house tool, or use established annotation tools on our side. Tell us your setup and we will adapt to it.
Can we start with a small pilot?
Yes. Every project starts with a pilot batch so you can check accuracy, speed and communication before scaling up.
How do you measure quality?
We agree on accuracy targets up front and track them using gold-standard tasks, second-pass review and regular audits, with results shared in each report.
Which languages do you support?
English plus several Indian languages including Telugu, Hindi, Tamil and Kannada. Contact us for other languages and we will confirm availability.
How is pricing calculated?
Pricing depends on task complexity and volume — typically per item, per hour of audio, or per annotator-hour. We share a clear quote after reviewing sample data.
Have a dataset in mind?
Share a sample and your requirements — we will propose a workflow and run a pilot to prove quality.