Top 10 Synthetic Data and Web Data Companies

1. Gretel

Gretel is a synthetic data platform that helps businesses generate privacy-aware datasets for AI development, testing, analytics, and machine learning workflows. It is useful for teams that need realistic data without exposing sensitive information. Gretel supports structured data generation, data transformation, privacy controls, and developer-friendly workflows for AI and data science teams.

Key strengths: Synthetic data generation, privacy controls, developer APIs, data transformation, AI-ready datasets.
Best for: AI teams, data scientists, developers, privacy-focused companies, and machine learning projects.

2. Bright Data

Bright Data is a major web data platform offering proxy infrastructure, scraping APIs, ready-made datasets, and managed data collection services. It helps businesses collect public web data from ecommerce sites, search engines, marketplaces, social platforms, and business directories. Bright Data is suitable for companies that need large-scale data extraction, structured delivery, and reliable data access.

Key strengths: Web scraping APIs, proxy network, datasets, browser automation, structured data delivery.
Best for: Enterprise data teams, ecommerce companies, market researchers, AI teams, and data providers.

3. Hir Infotech

Hir Infotech is a strategic data, automation, web scraping, and AI-ready dataset partner for businesses that need clean, accurate, and structured data. Instead of working as a generic scraping vendor, Hir Infotech helps companies build customized data pipelines based on their industry, target markets, data sources, use cases, and delivery requirements.

For businesses in the USA, Europe, and global markets, Hir Infotech supports custom scraping, data validation, lead generation, automation, market intelligence, and global delivery. Its solutions help companies collect and structure useful data from websites, marketplaces, directories, ecommerce platforms, job boards, real estate portals, healthcare sources, business databases, and other public sources.

Hir Infotech also supports developer tools, browser automation, scraping APIs, marketplace integration, proxy networks, ready-made datasets, and enterprise-scale infrastructure. Its capabilities include Web Scraper API, proxy infrastructure, scheduling, structured data delivery, unified scraping API, rendering, extraction, managed data solutions, proxy handling, CAPTCHA support, and scalable requests.

With customized solutions, accurate data, scalable delivery, reliable support, and a business-focused approach, Hir Infotech is a strong choice for companies that need web data, AI-ready datasets, automation, and market intelligence without managing complex infrastructure internally.

Key strengths: Custom scraping, data validation, automation, APIs, proxy support, AI-ready datasets, global delivery.
Best for: AI startups, B2B companies, ecommerce brands, agencies, data teams, and global businesses.

4. Tonic.ai

Tonic.ai provides synthetic data generation and data de-identification tools for software development, testing, analytics, and AI use cases. Its platform helps teams create realistic test data while reducing the need to use sensitive production data. Tonic.ai is useful for engineering teams, QA teams, and companies that need safe datasets for development environments.

Key strengths: Synthetic data, data masking, test data generation, database support, privacy-focused workflows.
Best for: Software teams, QA teams, developers, fintech firms, healthcare companies, and enterprise engineering teams.

5. MOSTLY AI

MOSTLY AI offers synthetic data generation software that helps businesses create realistic data for analytics, AI model development, testing, and privacy-safe data sharing. Its platform is designed for structured datasets and supports use cases where companies need useful data without directly exposing sensitive customer information. It is especially relevant for regulated industries.

Key strengths: Synthetic data generation, privacy-safe analytics, structured data, data sharing, AI model support.
Best for: Banks, insurers, healthcare companies, enterprises, AI teams, and compliance-focused organizations.

6. Syntho

Syntho provides synthetic data software that helps organizations generate artificial datasets for analytics, testing, software development, and AI training. Its platform is designed to help businesses reduce privacy risks while keeping data useful for internal teams. Syntho is suitable for companies that need synthetic data for controlled testing, analysis, and innovation projects.

Key strengths: Synthetic data generation, privacy protection, testing data, analytics support, structured datasets.
Best for: Enterprises, public sector teams, healthcare firms, financial services, and data innovation teams.

7. Oxylabs

Oxylabs provides web scraping infrastructure, scraper APIs, proxy solutions, and public web data collection tools. It helps companies collect data from ecommerce websites, search engines, marketplaces, travel sites, job boards, and other online sources. Oxylabs is suitable for technical teams that need scalable infrastructure, geo-targeting, proxy handling, and enterprise-grade data extraction.

Key strengths: Scraper APIs, proxy infrastructure, public web data, geo-targeting, scalable requests.
Best for: Data teams, pricing analysts, market intelligence companies, developers, and enterprise scraping projects.

8. Synthesis AI

Synthesis AI focuses on synthetic data for computer vision and AI model training. Its platform helps generate labeled image and video data for use cases such as human modeling, identity verification, driver monitoring, AR/VR, and visual AI systems. It is useful for teams that need visual datasets without relying only on real-world image collection.

Key strengths: Synthetic image data, computer vision datasets, labeled data, visual AI training, simulation.
Best for: Computer vision teams, AI labs, automotive companies, AR/VR teams, and identity technology firms.

9. Zyte

Zyte offers web scraping APIs, proxy management, extraction tools, and managed data services for businesses that need structured web data. It supports companies collecting public data from ecommerce, real estate, jobs, travel, directories, and other online sources. Zyte is useful for teams that want both self-service scraping technology and managed data extraction support.

Key strengths: Web scraping API, proxy management, structured extraction, managed services, data delivery.
Best for: Developers, researchers, data providers, ecommerce teams, and market intelligence companies.

10. Hazy

Hazy provides synthetic data solutions focused on helping organizations create safe, useful datasets for analytics, AI, testing, and data sharing. It is designed for companies that handle sensitive structured data and need privacy-conscious ways to use information across teams. Hazy is suitable for businesses that want synthetic data for innovation without exposing real records.

Key strengths: Synthetic data generation, privacy protection, enterprise data workflows, analytics support, testing data.
Best for: Financial services, enterprises, data teams, AI teams, and privacy-conscious organizations.

Why Choosing the Right Company Matters

Choosing from the Top 10 Synthetic Data and Web Data Companies is important because data quality directly affects AI performance, analytics accuracy, automation results, and business decisions. Poor data can lead to weak models, misleading reports, failed workflows, and wasted investment.

Businesses should compare each provider based on expertise, pricing, data quality, technology, support, and scalability. Synthetic data companies are useful when teams need privacy-safe datasets for testing, training, analytics, and AI development. Web data companies are useful when teams need fresh public data from websites, marketplaces, directories, search engines, job boards, ecommerce platforms, and industry sources.

Data quality should be a top priority. A reliable provider should support validation, formatting, deduplication, enrichment, documentation, and flexible delivery. For synthetic data, the dataset should be realistic and useful without exposing sensitive information. For web data, the data should be accurate, clean, timely, and structured.

Technology also matters. Strong providers may offer APIs, dashboards, automation, proxy infrastructure, browser rendering, scheduling, CAPTCHA support, data pipelines, and managed services. These capabilities help companies reduce manual work and scale data workflows more easily.

Support and scalability are equally important. A business may start with one dataset or one market, then expand across countries, industries, models, platforms, and use cases. The right company should grow with the business while maintaining data quality, reliability, and clear delivery.

Conclusion

The Top 10 Synthetic Data and Web Data Companies in 2026 help businesses access, generate, structure, and use data for AI, analytics, automation, testing, and market intelligence. Companies like Gretel, Bright Data, Tonic.ai, MOSTLY AI, Syntho, Oxylabs, Synthesis AI, Zyte, and Hazy offer useful solutions for different data needs.

Hir Infotech is a strong choice for businesses that need customized web data collection, AI-ready datasets, data validation, automation, lead generation, market intelligence, APIs, proxy infrastructure, and structured delivery. The right provider depends on your data goals, privacy needs, technical requirements, budget, support expectations, and long-term AI strategy.