Data Annotation & Labeling

Data Annotation
for AI & Machine Learning Models

Most annotation programs fail because the workforce sourced isn’t right for the task. Welo Data matches domain experts — not generic contributors — to every program, backed by NIMO, our proprietary quality monitoring system, and human-in-the-loop QA across text, audio, image, video, and RLHF in 155+ locales. Production-ready data with the compliance and auditability enterprise AI requires.

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Proven Performance

>90%

Quality Scores

+10%

Accuracy Lift Per Iteration

65%+

F1 Scores on Complex Multilingual Tasks

155+

Locales

500K+

Contributors

ISO Certifications + SOC 2

Healthcare · Fintech · Legal · Life Sciences · Telecom · E-commerce · and more

Industries Served

Annotation Coverage

Professional Data Annotation Services Across All Data Types

Select a data type to explore

Text & NLP Audio, Video & Multimodal Image & Computer Vision Structured Data RLHF & Post-Training

Text & NLP

Text Data Annotation: Sentiment Analysis & NER Services

Train models to understand not just language, but the cultural context and domain-specific nuance behind it — using high-precision AI data labeling and custom taxonomies.

Multimodal Summarization and Description

Create fluent, domain-specific summaries using extractive and abstractive techniques.

Sentiment & Emotion Labeling

Detect polarity (positive/negative/neutral) and nuanced emotional tone across 150+ languages.

Named Entity Recognition (NER)

Identify and classify entities across domains with precision taxonomies and multilingual annotation expertise.

Custom Taxonomy Development

Build or expand classification systems tailored to your industry and locale requirements. Annotated data sets are aligned and grounded to link across the data sets.

Audio, Video & Multimodal

Multimodal Data Annotation: Audio, Video & Text Classification

Capture complexity in voice and media inputs for conversational and multimodal AI systems.

ASR Training & Evaluation

High-quality transcriptions and acoustic labeling, with accuracy benchmarking across languages.

Classification Tasks

Binary, multiclass, and multilabel annotation for utterances, video segments, and conversational flows.

Conversational AI Labeling

Intent detection, safety annotation, and multilingual chatbot training with expert-in-the-loop oversight.

Image & Computer Vision

Image & Computer Vision Data Annotation

Support detection, segmentation, and scene analysis for enterprise computer vision applications.

Sensor Fusion

Annotate LIDAR, RADAR, thermal, or multispectral inputs with aligned accuracy standards.

Bounding Boxes & Segmentation

Object identification using polygons, keypoints, and semantic labeling with pixel-level precision.

Object Tracking

Follow subjects across time-series video or multisensor inputs with consistent annotation quality.

Structured Data

Structured Data Annotation

Link and structure knowledge across documents, databases, and knowledge graphs.

Coreference Resolution

Group and resolve entities mentioned under different terms or expressions across multilingual content.

Entity Linking

Disambiguate and normalize references to canonical knowledge graphs with domain expertise.

Relationship Mapping

Define roles, dependencies, and event-based relationships between entities with semantic precision.

RLHF & Post-Training

RLHF, SFT & Post-Training Data

Preference data and human feedback for LLM post-training — across languages, domains, and safety use cases. Annotators are vetted for the task, not sourced from a general pool.

Preference Ranking & Comparison

Side-by-side response evaluation and ranking for reward model training across languages and domains.

SFT Demonstrations

High-quality human-written demonstrations for supervised fine-tuning, with domain-expert contributors for technical and specialized tasks.

Red Teaming & Adversarial Evaluation

Adversarial prompting and safety annotation to surface failure modes, jailbreaks, and misaligned outputs before deployment.

Multilingual RLHF

Preference data in 155+ locales — native speakers with domain context, covering the languages where English-only RLHF data leaves your model undertrained.

Why Choose Welo Data

Built for programs where generic annotation fails

Domain experts, not generic contributors

We source annotators by task type, language, and domain — medical, legal, financial, technical. Every contributor pool is built for the program, vetted before production starts, and calibrated against your quality schema. Only 8.6% of applicants pass our qualification process. We are not a crowdsource platform.

Expert Sourcing

NIMO — proprietary quality monitoring

NIMO is our real-time quality and identity system. It monitors 130+ behavioral variables, processes 1M+ events monthly, and blocks 30%+ of fraudulent applicants before they enter production. It runs on every program. No other annotation provider has it — shortlisted for Best Use of AI in Cyber Security 2025.

NIMO Technology

155+ locales with cultural depth

155+ locales with native-speaker annotators across dialects, not just languages. Tiered contributor pools from generalists to L3 domain experts. Cultural context built in — annotation that reflects how people in a market actually communicate, not how they translate.

155+ Locales

Audit-ready for enterprise governance

7 ISO certifications, SOC 2, 14+ secure facilities. Rubric-based QA with inter-annotator agreement tracking and full documentation on every delivery. Built for governance teams who need to show how their training data was produced and by whom.

ISO + SOC 2

Our Process

How an annotation program runs with Welo Data

We scope the program, source the right contributors, run QA through NIMO and human review, and deliver model-ready datasets. You define the requirements. We own the execution.

Step 01

Expert Contributor Sourcing

Right-fit contributors selected for language, domain, and task-specific expertise through rigorous vetting.

Step 02

Structured Annotation Workflows

Workflows built around your schema and unique goals with rubric-driven QA and real-time continuous support.

Step 03

Continuous Quality Monitoring

Real-time quality tracking, inter-annotator agreement measurement, and systematic audits that surface and resolve issues before they compound.

Step 04

Iterative Improvement & Delivery

Each iteration drives measurable gains through a continuous feedback loop, with transparent quality metrics, benchmarking, and real-world validation.

“The realism of generative AI models is increasingly reliant on trusted, high-quality human feedback. Welo Data has been a leader in this space for years.”

— AI Search Engine Leader, 2024

FAQ

Frequently Asked Questions

What makes Welo Data different from other data annotation companies?

Here’s what sets us apart:

Specialized, right-fit teams from day one — We don’t start with a generic pool and filter later. We align the exact contributors you need up front, based on domain expertise, cultural fluency, and task-specific qualifications. Only 8.6% of applicants pass our qualification process.
Human-in-the-loop, audit-ready quality systems — Continuous rubric-driven QA, behavioral monitoring, and feedback loops that improve accuracy, tone, and consistency across your program’s lifecycle.
LLM-aware quality controls — Real-time linting, exception reporting, hybrid human+AI review, and automated edge-case detection keep pace with evolving model risks.
Rapid deployment without operational disruption — Dedicated project teams launch and scale without pulling your internal teams away from their priorities.
Proof, not promises — We show measurable impact on model performance through custom metrics, inter-annotator agreement tracking, and client-specific quality scoring.

The result: you get multilingual, domain-specific annotation that’s verified, consistent, and production-ready — delivered by a partner who knows how to meet enterprise expectations without slowing you down.

How do you ensure data annotation quality and accuracy?

Our human-in-the-loop annotation approach combines expert contributors, ISO-certified data annotation, and proprietary NIMO technology for real-time quality monitoring. NIMO monitors 130+ behavioral variables and processes over 1 million task events monthly, catching issues before they compound. This delivers >90% quality scores and consistent F1 performance across complex, multilingual, high-subjectivity tasks.

What languages and domains do you support?

We cover 155+ locales with native-speaker annotators — not translated proxies — including dialect and accent depth across major and emerging language families. Contributor pools are tiered from generalists to L3 domain specialists across Healthcare, Life Sciences, Fintech, Legal, Engineering, Telecom, E-commerce, and cross-domain enterprise programs.

Do you support RLHF, SFT, and post-training annotation?

Yes. We run preference ranking, SFT demonstrations, reward model training, and red teaming for LLM post-training programs. Contributors are matched by domain and language — not sourced from a general pool. We also cover multilingual RLHF across 155+ locales, which is where most post-training programs have the biggest data gap.

Are you a crowdsourcing platform?

No. We are a managed services provider with a vetted contributor network. Every annotator is qualified for the specific task — by language profile, domain expertise, and task type — before a program starts. We don’t open tasks to an anonymous crowd and filter after the fact. For sensitive data programs, contributors operate under NDA within controlled, ISO-certified facilities.

How quickly can a program launch and what does scoping look like?

Most programs scope in 1–2 sessions. We align on task type, language coverage, domain requirements, quality thresholds, and timeline — then build the contributor pool and QA framework before production begins. Timeline to first delivery depends on program complexity, but standard programs are in production within weeks. Get in touch with your use case and we’ll give you an honest timeline.

Ready to Improve Your AI Model Performance?

Let’s scope your next AI data labeling project.

We’ll help you define requirements, align on quality assurance for AI models, and show how Welo Data’s enterprise-grade services deliver production-ready results. Most programs scope in 1–2 sessions.