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Content & eLearning · Data Annotations

Data Annotations

High-quality training datasets labeled by subject matter experts.

We label, annotate, and enrich raw data inputs for custom machine learning models and LLM fine-tuning. From text taxonomy classification and computer vision tagging to expert human-in-the-loop (HITL) RLHF assessments, we deliver audited, ground-truth datasets.

Image · Text · Audio

Data Types

Multi-Pass QA

Review Process

NDA

Secure Handling

India-Based

Annotation Team

What's Included

Comprehensive Annotation Capabilities

Text & Semantic Labeling

Named Entity Recognition (NER), intent classification, coreference resolution, and text sentiment tagging to build robust NLP systems.

Multilingual Annotations

Translation alignment, localized dialect transcription, and cross-cultural evaluation for global conversational AI models.

Image & Video Tagging

Bounding boxes, polygon segmentation, keypoint mapping, and semantic object segmentation using advanced labeling toolkits.

RLHF & Alignment Feedback

Reinforcement Learning from Human Feedback (RLHF), response ranking, chatbot red-teaming, and model safety evaluations.

Consensus Quality Control

Double-blind annotation pipelines with automated consensus scoring and senior auditor review checks to minimize bias.

Security Best Practices

Fully isolated workspace environments with strict access controls, RLS keys, and clean metadata scrubbing parameters.

How It Works

Our Delivery Process

01

Schema Definition

Define annotation rules, category definitions, and boundary guidelines.

We collaborate to build comprehensive annotation manuals and validation criteria to align our labeling squads with your targets.

02

Onboarding & Calibration

Assemble specialized domain expert squads and run training pilots.

Labelers are onboarded using sample test batches. We monitor inter-annotator agreement (IAA) metrics and iterate guidelines until agreement exceeds 90%.

03

Production Labeling

Scale labeling runs utilizing consensus check layers.

Multiple labelers analyze each asset. Discrepancies are auto-routed to senior subject matter experts to protect dataset integrity.

04

Auditing & Export

Run quality checks, scrub metadata, and ship clean files.

We run final format validations and deliver training-ready assets mapped strictly to your schema configurations.

What You Receive

Project
Deliverables

Every engagement comes with a clearly defined set of deliverables. No surprises, no scope creep — just high-quality output on time.

Training-ready annotation files (JSON, COCO, YOLO, VOC, or CSV)
Documented labeling guidelines and annotation manual
Consensus and Inter-Annotator Agreement (IAA) reports
Audited worker performance statistics spreadsheets
Quality assurance verification certificates
Secure, access-controlled database export sets
Scrubbed metadata reports removing custom PII flags
Pilot test phase calibration documentation
API schema mapping configurations guide
30-day post-delivery labeling validation warranty
Interactive Estimator

Estimate Your Annotation Project Cost

Select your dataset scale, complexity, and criteria to estimate the investment.

Type of raw data to annotate

Dataset Volume / Record Count

500 records5000 records20000 records

Consensus Level (Labelers per asset)

Request Custom Quote

Enter your contact details below. We will calculate the customized investment quote and timeline based on your selections and email it to you.

  • •Consensus checking parameters included in estimate.
  • •Labelers match domain expert qualifications.
  • •Clean, access-controlled environment logs generated.
FAQ

Common Questions

We curate custom teams matching your subject matter guidelines. For K-12 EdTech datasets, we assign educators with subject experience; for technical code labeling, we deploy senior software engineers.
We implement multi-labeler consensus checkpoints, regular calibration tests, and continuous QA review metrics audited by dedicated project team leads.
Absolutely. All annotation pipelines are conducted on isolated workspaces utilizing Row-Level Security (RLS). We scrub PII automatically before export.
Yes. Our teams are experienced working with leading toolkits including Labelbox, CVAT, Label Studio, and Roboflow, or directly in custom portals.
Get Your Quote

Ready to Start?

Tell us what you need and get a written quote after a free call. We reply within 1–2 working days.

Get Your Custom Quote

Start Your Project

Fill in your details and we'll send a tailored proposal.

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