Appen has long been a leading player in the global data labeling market, recognized for its large-scale workforce and ability to deliver across geographies. For years, scale was the key differentiator in AI data services. But as AI evolves, volume alone is no longer enough.
With the rapid rise of LLMs and generative AI, development workflows have become far more complex. Engineering teams today require more than just data at scale. They need partners who can offer deep domain expertise, structured quality frameworks, agile operations, and flexible engagement models. This shift is driving more organizations to seek Appen alternatives that better match their domain-specific requirements.
In this guide, we take a closer look at leading Appen competitors, companies like Appen, and other companies similar to Appen, comparing them across actual AI and LLM use cases. Instead of a generic list, we focus on how each provider aligns with specific domains such as automotive, construction, and coding agent development. Key evaluation criteria include quality assurance processes, domain expertise, scalability, security standards, and the ability to support complex AI workloads.
If you are searching for an Appen alternative or evaluating alternatives to Appen for a high-stakes AI project, this guide will help you navigate the landscape and choose the right data partner.
Top Data Labeling Companies for AI and LLM Teams in Particular Domains
AI data providers vary significantly in their specialization. While some excel in computer vision for autonomous systems, others focus on large-scale NLP. This diversity is a key driver behind the global growth of the AI and LLM markets. Below, we examine companies like Appen across specific verticals.
Data Collection and Data Annotation Service Providers in Automotive
Autonomous vehicles and Advanced Driver-Assistance Systems (ADAS) demand high-precision data pipelines, especially as OEMs race to achieve SAE’s six levels of driving automation amidst ongoing safety incidents. As a result, automotive AI teams are seeking vendors capable of providing high-quality, large-scale data processing, such as data collection, data annotation, and data validation, to train models with absolute accuracy.
LTS GDS
Overview:
LTS Global Digital Services (LTS GDS) is a global data provider and a key member of the LTS Group technology ecosystem in Vietnam. LTS GDS specializes in digital BPO services, including data processing for Computer Vision and NLP, and E2E data solutions for Generative AI (LLMs, coding LLMs, diffusion, and multimodal models). Having successfully delivered over 500 projects, LTS GDS has processed 50+ million data points with an industry-leading 99% accuracy rate. In particular, LTS GDS possesses extensive experience in the automotive industry, managing multi-year partnerships and delivering millions of high-precision annotated data points for autonomous driving systems.
Website: https://www.gdsonline.tech/
Headquarters: Hanoi, Vietnam
Why LTS GDS?
High quality: With nearly a decade of experience in data annotation for autonomous driving and transportation, LTS GDS utilizes a strict 4-layer QA framework to achieve up to 100% accuracy across LiDAR, 2D/3D object detection, and semantic segmentation. In addition, LTS GDS is among the first providers to receive the Data Labeling Assessment from DEKRA Testing and Certification S.A.U, validating our standardized processes for AI and ADAS systems.
Security: LTS GDS ensures the utmost confidentiality of your automotive data through mandatory NDAs and strict adherence to ISO 27001 and GDPR standards, guaranteeing top-tier data protection and privacy.
Scalable teams: Leveraging rapid ramp-up capabilities, LTS GDS can recruit and train a specialized team within one week. They offer flexible engagement models to optimize operations, including project-based, time & materials (T&M), and build-operate-transfer (BOT).
Reasonable cost: LTS GDS leverages Vietnam’s competitive labor costs and favorable tax policies to provide cost-efficient IT outsourcing. Their flexible pricing models are designed to meet diverse client requirements without compromising quality.
Best for:
Automotive AI startups and Tier 1 suppliers are seeking large-scale, cost-efficient annotation teams with extensive industry experience.
Scale AI
Overview:
Scale AI is a global leader in AI data infrastructure, powering top-tier autonomous vehicle and defense programs. The company achieved ‘unicorn’ status rapidly, fueled by strategic investments from industry giants such as Nvidia and Meta. Beyond providing the data foundations for training AI, Scale AI builds and trains specialized AI agents for generative AI and national security platforms. It is one of the high-end alternatives to Appen; however, its services are priced above the industry average.
Website: https://scale.com/
Headquarters: California, USA
Why Scale AI?
Scale AI is regarded as one of the strongest competitors to Appen in automotive AI. The company provides advanced tooling, integrated data pipelines, and infrastructure tailored for perception stacks involving LiDAR, radar, and multi-sensor fusion.
Its value proposition centers on end-to-end automation and platform integration. Rather than acting solely as a labor provider, Scale AI offers software and workflow orchestration that fits seamlessly into enterprise ML pipelines.
However, pricing structures tend to reflect enterprise-grade positioning, which may not align with early-stage startups.
Best for:
Major automotive players and top-tier AI firms demand sophisticated tools and integrated systems capable of handling annotation at scale.
TELUS Digital
Overview:
TELUS Digital (formerly TELUS International) is a global leader in digital customer experience (CX) and AI-driven solutions. Headquartered in Vancouver, Canada, it operates as a specialized subsidiary of the telecommunications giant TELUS Corporation. TELUS Digital offers end-to-end data annotation support for various domains.
Website: https://www.telusdigital.com/
Headquarters: Vancouver, Canada
Why TELUS Digital?
TELUS Digital stands out for its global workforce and long-standing enterprise partnerships. For automotive companies operating across multiple regions, this international footprint makes it easier to scale data annotation while maintaining consistent processes across markets. The company supports a wide range of data labeling tasks, including image, video, and multi-sensor datasets used in autonomous driving systems.
TELUS Digital also brings structured operations and mature security practices that appeal to organizations with strict compliance and governance requirements. Because of its scale and diverse global talent pool, TELUS Digital is considered one of the leading Appen alternatives when enterprises evaluate data labeling partners for automotive AI training data projects.
Best for:
Global enterprises seeking multilingual automotive annotation services with enterprise compliance support.
Mindy Support
Overview:
Mindy Support is a large-scale BPO and AI data infrastructure company headquartered in Cyprus, with major operational hubs in Eastern Europe, particularly Ukraine. The company is a global provider of data collection and data labeling services for LLMs, as well as customer support solutions, and is a trusted partner of Fortune 500 and GAFAM companies.
With more than ten years of experience, and offices and representatives in Cyprus, Poland, Romania, the Netherlands, India, the UAE, and Ukraine, Mindy Support has built a team of over 2,000 professionals helping companies tackle complex data annotation challenges for advanced AI systems.
Website: https://mindysupport.com/
Headquarters: Cyprus
Why Mindy Support?
Mindy Support is known for its flexible project setup and the ability to scale annotation teams based on project needs. For automotive AI projects that rely heavily on image and video datasets, the company provides structured labeling workflows supported by dedicated QA processes to ensure data quality.
With more than 11 years of experience in data annotation and customer operations across 25+ countries, Mindy Support has built a globally distributed workforce capable of supporting multilingual datasets in over 30 languages. The company also maintains strong security and compliance standards, including ISO 27001, ISO 9001, SOC2 Type 1, HIPAA, CCPA, and GDPR. This combination makes Mindy Support a viable Appen alternative for automotive data labeling projects.
Best for:
Ideal for companies seeking a provider that offers multilingual data labeling alongside customer support services.
Cogito Tech
Overview:
Established in 2011, Cogito Tech is a US-headquartered firm with primary delivery operations in India, specializing in high-quality data solutions for AI training. The company provides a comprehensive suite of data annotation services, spanning image, video, audio, and text, tailored for computer vision, natural language processing, and Generative AI. They are recognized for their expertise in complex, domain-specific projects within the automotive and medical sectors.
Website: https://www.cogitotech.com/
Headquarters: New York, USA
Why Cogito Tech?
With over a decade of experience across a wide range of projects, Cogito Tech offers a competitive cost structure by leveraging its India-based workforce. The company is able to support autonomous driving projects, specializing in tasks such as object detection, classification, and class segmentation. Furthermore, Cogito Tech maintains a robust compliance profile, holding a comprehensive suite of certifications including ISO 27001, ISO 9001, GDPR, HIPAA, CCPA, and SOC 2 Type II.
Best for:
A strong fit for organizations that are looking to optimize their budget for data annotation services.
Label Your Data
Overview:
Founded in 2020, Label Your Data is a leading provider of data annotation and labeling services dedicated to accelerating the development of advanced AI models. By offering a comprehensive ecosystem that includes both professional labeling services and a proprietary platform, the company enables Data Scientists and ML Engineers to streamline dataset preparation. With its global headquarters strategically positioned across North America, the EU, and Asia, they leverage a modern infrastructure to support complex projects.
Website: https://labelyourdata.com/
Headquarters: Delaware, United States
Why Label Your Data?
Label Your Data offers both data processing services and a specialized data annotation platform, supported by a workforce of over 1,000 professionals across Europe and the Americas. The company operates with modern infrastructure and holds multiple certifications in security and domain expertise. In addition, Label Your Data provides flexible and transparent pricing models, including on-demand, short-term, and long-term options, making it easier for clients to estimate and manage project costs. However, its experience in data collection and annotation for emerging generative AI models remains limited.
Best for:
Companies seeking a vendor for data collection and annotation, particularly in Computer Vision use cases.
Read more: Top 9 Leading Data Labeling Companies | 2026 Updated
Data Collection and Data Annotation Service Providers in Construction
Construction AI is rapidly expanding into areas such as safety monitoring, defect detection, predictive maintenance, and site automation. Therefore, the demand for data collection and data annotation services in this sector is increasing to support the development of AI models tailored for the construction domain.
LTS GDS
Overview:
Founded in 2016, LTS Global Digital Services is a global data provider and a core member of the LTS Group technology ecosystem in Vietnam. The company specializes in digital BPO services, delivering data collection, data annotation, data processing, and end-to-end data solutions for a wide range of AI models.
With more than 500 successfully delivered projects, LTS GDS has processed over 50 million data points with an industry-leading 99 percent accuracy rate. In addition to its large-scale workforce, the company offers domain-specific experts across multiple industries, with strong capabilities in construction, ensuring high-quality data solutions for smart AI applications.
Website: https://www.gdsonline.tech/
Headquarters: Hanoi, Vietnam
Why LTS GDS?
Specialized teams: LTS GDS provides trained annotators with hands-on experience in the construction domain. They can handle complex tasks such as 3D point cloud labeling from LiDAR data, identifying detailed architectural components for BIM integration, and tracking heavy machinery movements to support site automation.
End-to-end data capabilities: Beyond data collection and annotation, LTS GDS delivers a full spectrum of data services, including data validation and data transformation, along with end-to-end data solutions tailored for various AI models.
Best for:
Construction companies and AI solution providers are looking for an Appen alternative with strong domain expertise, especially for complex projects such as site monitoring, BIM-based analysis, and automation.
Keymakr
Overview:
Founded in 2015 and headquartered in the United States, Keymakr provides training datasets for AI models, serving over 100 clients worldwide. The company operates with a team of around 500 specialists experienced in delivering datasets for both Computer Vision and LLMs across industries such as automotive, retail, agriculture, and construction.
Website: https://keymakr.com/
Headquarters: United States
Why Keymakr?
Keymakr brings over a decade of experience in data collection and data annotation, particularly for Computer Vision models. The company also offers its proprietary Keylabs platform, which supports both internal workflows and commercial data annotation projects, promoting efficient project management and smart operations.
Best for:
AI developers and construction firms are looking for a US-based partner with much experience in Computer Vision and access to a customized annotation platform (Keylabs) to handle complex, large-scale visual datasets.
Data Solutions Providers for Coding Agents
When generative AI continues to grow, the demand for high-quality datasets to power AI agents is rapidly increasing. In particular, coding agents require specialized data solutions to support tasks such as code generation, evaluation, and reasoning. This drives the need for vendors capable of delivering high-quality, various datasets tailored to trustworthy AI products.
Toloka
Overview:
Toloka provides curated data for AI agents and model development, helping enhance both performance and safety across a wide range of capabilities. These include agentic skills, AI safety, coding skills, text generation and reasoning, as well as image, video, and audio generation.
Trusted by leading AI innovators such as Anthropic, Amazon, Microsoft, Shopify, and Poolside, Toloka is backed by Bezos Expeditions and plays a key role in advancing next-generation AI systems.
Website: https://toloka.ai/
Headquarters: Amsterdam, Netherlands
Why Toloka?
Toloka brings over a decade of experience in delivering high-quality data, supported by a global network of more than 200,000 contributors across 50+ domains and 40+ languages. The company provides end-to-end data solutions, covering everything from dataset creation and annotation to evaluation.
Toloka also has a strong pool of expert programmers with experience across dozens of programming languages and frameworks. In addition, it offers tools such as Toloka Loop and internal benchmarking systems to continuously evaluate and improve dataset quality.
Best for:
AI companies are building coding agents that require high-quality data for prompt evaluation, ranking, and model performance optimization.
LTS GDS
Overview:
LTS Global Digital Services (LTS GDS) delivers end-to-end data solutions for a wide range of AI models such as Computer Vision, NLP, and Generative AI. Because one of the early providers in Vietnam to focus on data for coding agents, coding LLMs, and AI coding assistants, LTS GDS has been supporting leading clients across Europe and the Americas in building and fine-tuning high-performance coding models.
Website: https://www.gdsonline.tech/
Headquarters: Hanoi, Vietnam
Why LTS GDS?
LTS GDS stands out for its strong commitment to quality, thanks to QA processes that deliver up to 99 percent accuracy. The company supports the full data lifecycle, creating datasets for pre-training, fine-tuning, as well as evaluation and benchmarking of coding models.
With 100+ seasoned developers mastering SQL, Python, C#, JavaScript, TypeScript, Bash, .NET, and Scala, LTS GDS ensures that every line of generated code is fast, logically sound, and genuinely bug-free. Additionally, through a combination of its internal team and an established partner network, LTS GDS can ramp up to 200 contributors within just two weeks.
In addition, the company offers competitive pricing aligned with dataset quality, while bringing around three years of experience supporting leading European clients in building and optimizing coding agents.
Best for:
AI startups and enterprises are building coding agents that require technically skilled LLM evaluators and high-quality datasets for coding-focused model development.
Why Companies Are Searching for Appen Alternatives
The AI development has prompted many organizations to explore Appen alternatives because the requirements for data services have become significantly more complex. Today, modern workflows go far beyond traditional data labeling, encompassing stages such as supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), safety alignment, red teaming, and model evaluation. These growing demands push companies to look for Appen alternatives that offer more specialized expertise and flexible engagement models across different stages of AI development.
Another key reason companies turn to Appen alternatives is the need for a stable and scalable talent pool. AI projects can expand rapidly, and relying on a single vendor may create operational risks. In some cases, large providers may prioritize enterprise clients, which leads other businesses to diversify their vendor strategy. By working with multiple Appen alternatives, companies can ensure continuous resource availability, avoid disruptions, and maintain greater control over project timelines.
Cost is also a major factor driving the search for Appen alternatives. With increasing competition in the AI data services market, many providers are able to deliver high-quality results at more competitive price points. Meanwhile, certain projects require specific operational standards, stricter security requirements, or deeper domain expertise. This encourages companies to explore Appen alternatives that can better align with their technical needs, budget constraints, and long-term AI strategy.
How to Choose the Right Appen Alternative for an AI & LLM Project
With the growing number of Appen alternatives in the market, choosing the right partner requires a more strategic approach than ever. Not all vendors are built to support the full complexity of modern AI and LLM development, so companies need to evaluate options based on their specific project requirements.
First, assess the vendor’s expertise across the AI data lifecycle. Strong Appen alternatives should be able to support not only data collection and annotation, but also offer end-to-end data solutions for full stages such as Pre-training, SFT, RLHF, model evaluation, and red teaming. This ensures the vendor can grow with your project rather than becoming a limitation later on.
Second, consider domain knowledge and technical depth. Many AI applications today require industry-specific understanding, whether in automotive, construction, healthcare, or coding. The best Appen alternatives combine skilled annotators with domain experts to deliver more accurate and context-aware datasets.
Scalability is another critical factor. AI projects often expand quickly, so it’s important to choose Appen alternatives that can ramp up teams efficiently without compromising quality. A large, well-managed talent pool and proven onboarding processes can help maintain consistency even as project scope increases.
Quality assurance should also be a top priority. Reliable Appen alternatives invest in strong QA frameworks, clear guidelines, and multi-layer validation processes to ensure high accuracy and consistency across datasets. This is especially important for LLM training, where data quality directly impacts model performance.
Finally, evaluate flexibility and cost efficiency. Different projects require different engagement models, timelines, and budgets. The most suitable Appen alternatives offer transparent pricing, adaptable workflows, and the ability to customize solutions based on specific needs, helping companies balance performance with cost.
By carefully considering these factors, businesses can identify the right Appen alternatives that not only meet current requirements but also support long-term AI development goals.
FAQs About Appen Alternatives
1. What are the best Appen alternatives in 2026?
The best Appen alternatives depend on your project needs, but top options include vendors with strong capabilities in data annotation, or data solutions for any AI models like Computer Vision, NLP, and LLM. Many companies now explore multiple Appen competitors to find the right balance between quality, scalability, and cost.
2. Why should companies consider an Appen alternative?
Businesses often look for an Appen alternative to access more specialized expertise, flexible engagement models, or competitive pricing. In many cases, working with companies similar to Appen helps reduce dependency on a single vendor and improves operational flexibility.
3. Are there companies like Appen that focus on LLM and Generative AI?
Yes, several companies (LTS GDS, Toloka, Scale AI) like Appen now specialize in LLM and Generative AI data services, offering data solutions for different AI development stages. These Appen competitors are often better equipped to handle modern AI workflows compared to traditional labeling providers.
4. How do Appen alternatives compare to Clickworker?
Both Clickworker alternatives and alternatives to Appen offer scalable crowd-based data services, but they may differ in terms of quality control, domain expertise, and other factors. Choosing between them depends on whether your priority is cost efficiency, technical depth, or project complexity.
5. How do I choose between different Appen competitors?
When evaluating Appen competitors, consider factors such as domain expertise (automotive, construction, coding, etc), QA processes, scalability, pricing, and experience with AI/LLM projects. The right choice among Appen alternatives will depend on how well a vendor aligns with your specific technical and business requirements.
Choosing the Ideal Data Solutions Partner for AI & LLM Projects
Selecting the right data labeling partner is essential for AI or LLM projects. Compare providers based on quality, domain expertise, security, workforce capacity, and scalability, since these factors directly impact model performance at every stage. As workflows become complex, evaluating Appen alternatives ensures companies have the necessary expertise, flexibility, and resources.
By defining clear requirements, aligning on quality standards, and choosing vendors with proven experience in specific areas, businesses can build a more effective and resilient data pipeline. Many organizations today are turning to Appen alternatives and companies like Appen to diversify their vendor strategy, optimize costs, and better support evolving AI projects.
LTS Global Digital Services is one of the emerging alternatives to Appen, delivering high-quality and cost-effective data solutions for AI and LLM projects. With over 100 experts possessing strong technical expertise, strict QA processes, and flexible engagement models, LTS GDS supports businesses in building trustworthy datasets tailored to their specific needs. Talk to our experts now!
Whether you are exploring alternatives to Appen for a pilot project or looking for a long-term data partner, choosing the right vendor can significantly accelerate your AI development journey.
