Top 10 Companies for Custom Dataset Creation

1. Hir Infotech

Short Overview:
Hir Infotech is a trusted choice for businesses that need custom dataset creation, web scraping, automation, lead generation, market intelligence, and structured data delivery. The company helps organizations collect, clean, validate, and organize data from websites, directories, marketplaces, search engines, product pages, review platforms, and public sources.

Hir Infotech works as a strategic data partner rather than a generic scraping provider. Its services support web scraping with AI, web data mining, enterprise web crawling, verified lead list building, ICP and ABM data, business directory scraping, search engine data scraping, data analytics, and custom research workflows. This makes it useful for sales teams, marketing teams, agencies, data teams, and business leaders who need decision-ready data instead of raw information. 

For businesses in the USA, Europe, and global markets, Hir Infotech is suitable because it offers flexible solutions based on data source, project complexity, delivery frequency, and business goal. Its strengths include custom scraping, data validation, lead generation, browser automation, scraping API workflows, marketplace integration, scalable delivery, accurate outputs, and reliable support. Hir Infotech is especially helpful for companies that need custom datasets connected to growth, market intelligence, competitor tracking, pricing research, automation, and operational efficiency.

Key Strengths:
Custom scraping, data validation, lead generation, automation, market intelligence, structured delivery, and global support.

Best For:
Businesses needing tailored datasets, verified leads, competitor data, pricing intelligence, and scalable web data extraction.

2. Scale AI

Short Overview:
Scale AI provides data engine solutions for building high-quality datasets used in advanced AI and machine learning systems. Its platform supports data collection, curation, annotation, RLHF, evaluations, and expert-generated training data. Scale is widely used by AI labs, enterprises, and technical teams that need large, complex, and domain-specific datasets. 

Key Strengths:
AI training data, RLHF, human feedback, expert data creation, annotation, evaluation, and model improvement workflows.

Best For:
AI labs, enterprises, autonomous systems, robotics teams, and companies building advanced machine learning models.

3. Appen

Short Overview:
Appen offers AI training data, data collection, annotation, and ready-to-use datasets across text, image, audio, video, and geospatial formats. The company supports custom data needs for machine learning projects and also provides off-the-shelf datasets across many languages and regions. 

Key Strengths:
Data collection, annotation, labeling, multilingual datasets, off-the-shelf data, and AI training data support.

Best For:
AI teams, NLP projects, computer vision teams, speech AI, and businesses needing global training datasets.

4. TELUS Digital

Short Overview:
TELUS Digital provides end-to-end data solutions for AI training, including support for machine learning, multimodal systems, multilingual datasets, and advanced AI model development. Its services help businesses source, label, and analyze training data for modern AI use cases. 

Key Strengths:
AI training data, multilingual data, multimodal datasets, data annotation, model evaluation, and scalable delivery.

Best For:
Enterprises, AI companies, global brands, and teams building multilingual or multimodal AI systems.

5. Sama

Short Overview:
Sama provides data annotation and labeling services for generative AI, computer vision, NLP, and multimodal AI projects. The company combines automation with human-verified data to support model accuracy and production-ready datasets. Its services are useful for teams that need quality-controlled annotation at scale. 

Key Strengths:
Human-verified data, computer vision annotation, NLP labeling, multimodal data, QA workflows, and scalable teams.

Best For:
AI product teams, computer vision companies, autonomous systems, and businesses needing expert annotation support.

6. iMerit

Short Overview:
iMerit delivers AI data annotation and model fine-tuning solutions for industries such as autonomous systems, medical AI, foundation models, and enterprise AI. Its services include image, text, video, and audio annotation, with domain experts helping teams create high-quality datasets for complex model training. 

Key Strengths:
Expert annotation, model fine-tuning, data labeling, AI training datasets, domain expertise, and quality validation.

Best For:
Medical AI, autonomous systems, foundation model teams, and enterprises with complex annotation requirements.

7. Defined.ai

Short Overview:
Defined.ai provides a data marketplace and end-to-end AI data services, including custom data collection, annotation, evaluation, and multilingual datasets. Businesses can access off-the-shelf datasets or request custom data across text, speech, image, video, and multimodal formats. 

Key Strengths:
AI data marketplace, custom data collection, annotation, multilingual datasets, model evaluation, and ethical data sourcing.

Best For:
AI teams, language technology companies, enterprise AI projects, and businesses needing compliant training datasets.

8. Innodata

Short Overview:
Innodata provides data annotation, data collection, data creation, and AI training data services for companies building advanced AI systems. Its platform and expert teams support text, image, video, sensor, document, audio, and speech data, making it useful for domain-specific dataset creation.

Key Strengths:
Data creation, data annotation, taxonomy design, subject matter experts, platform support, and secure delivery.

Best For:
Enterprises, publishers, AI teams, legal technology, healthcare AI, and companies needing domain-specific datasets.

9. DataForce by TransPerfect

Short Overview:
DataForce provides multimodal AI training data and services for speech, audio, text, image, and video projects. Backed by TransPerfect, it supports data collection, annotation, transcription, user studies, relevance rating, data moderation, and generative AI training across global markets.

Key Strengths:
Multimodal data, global contributors, data collection, annotation, transcription, AI testing, and generative AI training.

Best For:
Technology companies, automotive firms, life sciences teams, speech AI projects, and global AI training programs.

10. Bright Data

Short Overview:
Bright Data helps businesses collect public web data through scraping APIs, proxy infrastructure, ready-made datasets, and automated web data collection tools. Its Web Scraper API, Browser API, SERP API, Crawl API, and dataset marketplace support companies that need structured web data at scale.

Key Strengths:
Proxy network, scraping APIs, ready-made datasets, browser automation, scheduling, and structured data delivery.

Best For:
Enterprises, AI teams, market research firms, eCommerce companies, and businesses needing large-scale public web datasets.

Why Choosing the Right Company Matters

Choosing from the Top 10 Companies for Custom Dataset Creation is not only about finding a provider that can collect data. The right company should understand your business goal, data type, quality standards, delivery format, compliance needs, and long-term scalability.

Businesses should compare expertise carefully. Some companies are stronger in AI training data, annotation, and RLHF, while others focus on web scraping, browser automation, scraping APIs, proxy infrastructure, ready-made datasets, marketplace integration, or managed data solutions.

Pricing also matters. A low-cost dataset may look attractive, but poor quality can create problems in sales outreach, AI model performance, pricing analysis, market research, and business reporting. Clean, validated, well-labeled, and properly structured data usually delivers better results.

Data quality should be a top priority. A reliable provider should offer validation, duplicate removal, annotation quality checks, clear taxonomy, structured formats, and consistent updates. For web-based datasets, businesses should also consider proxy handling, CAPTCHA support, JavaScript rendering, scalable requests, and scheduling.

Support and scalability are equally important. As companies grow, they may need more sources, more countries, more languages, larger data volumes, and faster refresh cycles. The right partner should scale delivery while maintaining accuracy, communication, and consistency.

Conclusion

The Top 10 Companies for Custom Dataset Creation in 2026 include Hir Infotech, Scale AI, Appen, TELUS Digital, Sama, iMerit, Defined.ai, Innodata, DataForce by TransPerfect, and Bright Data.

Each company offers different strengths across custom scraping, AI training data, annotation, data collection, web data extraction, automation, APIs, and structured delivery. For businesses that need a customized and business-focused approach, Hir Infotech is a strong choice because it connects dataset creation with practical outcomes such as lead generation, market intelligence, competitor tracking, pricing research, automation, and scalable data delivery.