# Appen vs Defined.ai

Appen records 665,840 monthly visits with +0.2% month-over-month growth and Contact for Pricing pricing. Defined.ai records 146,251 monthly visits with -21% growth and Contact for Pricing pricing.

| Metric | [Appen](https://openaitools.app/tool/appen-com) | [Defined.ai](https://openaitools.app/tool/definedcrowd-com) |
| :--- | :--- | :--- |
| Website URL | https://appen.com | https://defined.ai |
| Categories | AI Models, Large Language Models (LLMs), AI Developer Tools | Other |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 665,840 | 146,251 |
| MoM Growth Rate | +0.2% | -21% |
| Primary Market | United States | United States |
| Direct Visits | 238,314 | 84,423 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 2 | 1 |
| Supported Platforms | Website | Website |

## Appen

Appen is one of the oldest pure-play AI data companies, tracing its roots to 1996 when it began building human-labeled datasets for speech recognition and NLP. Over three decades it supported successive generations of model development — search relevance in the 2000s, machine translation, deep-learning vision annotation, Transformer-era semantics, GPT-3 scale corpora, RLHF for conversational AI, and now agentic and multimodal foundation models.

Today Appen positions itself around six specialised capability areas: Frontier Alignment (chain-of-thought reasoning traces, SME RLHF, supervised fine-tuning demonstrations, adversarial red teaming), Agentic AI (golden trajectories, RL environment design, failure-mode taxonomies, SWE-driven evaluation), Multimodal and Speech AI (multilingual ASR and conversational corpora, expressive TTS annotation, VLM training data, video action labelling), Physical AI (LiDAR point-cloud annotation, multi-camera sensor fusion, robotics demonstration trajectories, world-model rollouts), Model Integrity (hallucination benchmarking, bias detection, regulatory audits and continuous monitoring), and Research Services (context engineering, calibrated LLM-as-a-judge, synthetic data and custom benchmarking).

Delivery runs through Appen's AI Data Platform (ADAP), which blends automation with human oversight, and the company cites SOC 2 and ISO 27001 certification, 500+ global locales, and a client roster that includes major cloud, search, retail and aerospace organisations. Appen does not publish self-serve pricing; engagements start with a scoping conversation and are quoted per project, so cost depends on data volume, language coverage, modality and annotation complexity.

**Pricing & Plans:** Enterprise/contact-for-pricing. Appen does not publish self-serve plans; projects are scoped and quoted individually. Appen also sells off-the-shelf (OTS) datasets and crowd/contractor workforce programs with separate terms.

- **Frontier alignment data:** Chain-of-thought reasoning traces, SME-level RLHF, supervised fine-tuning demonstrations and adversarial red teaming for the most capable models.
- **Agentic AI datasets:** Golden trajectories, RL environment design, failure-mode taxonomies and software-engineering-driven deep evaluation for autonomous agents.
- **Multimodal and speech corpora:** Multilingual ASR and conversational speech data, expressive TTS annotation, vision-language model training data, video action labelling and voice-agent evaluation.
- **Physical AI annotation:** LiDAR point-cloud labeling, multi-camera sensor fusion, robot demonstration trajectories, world-model rollouts and embodied interaction logs.
- **Model integrity and evaluation:** Hallucination benchmarking, bias detection, regulatory audits and continuous monitoring, plus independent model evaluation.
- **AI Data Platform (ADAP):** A production platform that combines automation with human oversight, with SOC 2 and ISO 27001 certification and 500+ locales covered.

**Strengths:** Three decades of annotation methodology, tooling and workforce management experience; Very broad coverage: frontier alignment, agentic, speech, multimodal, physical AI and evaluation in one vendor; 500+ locales and multilingual expertise that most in-house teams cannot match; Enterprise-grade security posture (SOC 2, ISO 27001) and publicly listed governance

**Limitations:** No transparent self-serve pricing; every engagement requires a sales/scoping cycle; Enterprise-oriented contracts can be heavy for small teams or indie developers; Quality depends on workforce management, so results vary by project and locale; Overlaps with many cheaper specialist annotation vendors, making vendor selection non-trivial

[Profile (Markdown)](https://openaitools.app/tool/appen-com.md)

## Defined.ai

Defined.ai supports the full AI data lifecycle, from sourcing and collection through annotation, machine translation, conversational data and model evaluation. Its AI Data Marketplace offers off-the-shelf datasets spanning audio, image, video, text and multimodal formats, with advanced filters so teams can find data matching specific technical requirements such as content type, file format, sample rate and bit depth, then request free samples and quotes.

Beyond off-the-shelf data, Defined.ai delivers custom services: model-in-the-loop data annotation for text, audio, image and video, global data collection, multilingual machine translation and conversational AI datasets designed to be natural and bias-free. Work is delivered via file transfer or API so teams can begin training quickly, and services are positioned as enterprise-grade with respect to privacy, security and compliance.

The company emphasizes ethical sourcing and governance. It states ISO 27001, 27701 and 42001 accreditation, GDPR and HIPAA compliance, and fair working conditions, and works with a crowd of over 1.6 million experts across 150+ countries and 500+ languages, dialects and locales. It also offers Accelerat.ai for multilingual AI agent support.

**Pricing & Plans:** Defined.ai does not publish standard list prices; datasets and services are quoted per project. Teams can browse the marketplace, access free dataset samples and request quotes, with pricing depending on dataset type, customization, volume and delivery method.

- **AI Data Marketplace:** A large selection of ready-to-use, ethically sourced datasets across audio, image, video, text and multimodal formats, with advanced filtering and free samples.
- **Data annotation & model-in-the-loop:** Expert-verified labeling for text, audio, image and video using model-first, human-in-the-loop workflows for accuracy and fairness.
- **Machine translation & multilingual data:** High-quality multilingual content for global AI systems, drawing on 500+ languages, dialects and locales.
- **Custom data collection:** Global, diverse data collection at scale for training, with privacy and security vetting on every dataset.
- **Data & model evaluation:** Rigorous testing of datasets and models to ensure accuracy, fairness and quality before deployment.

**Strengths:** One of the largest marketplaces of ready-to-use AI training datasets; Full lifecycle services from collection to annotation and evaluation; Strong compliance posture (ISO 27001/27701/42001, GDPR, HIPAA); Global crowd of 1.6M+ experts across 150+ countries and 500+ languages

**Limitations:** No public list pricing; quotes required for datasets and services; Enterprise-oriented, which may be heavy for small hobby projects; The legacy definedcrowd.com domain now routes to a restricted access gateway rather than a public product page

[Profile (Markdown)](https://openaitools.app/tool/definedcrowd-com.md)

## Frequently Asked Questions

### How do Appen and Defined.ai compare in monthly traffic?

Appen has 665,840 monthly visits, while Defined.ai has 146,251. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Appen has a month-over-month growth rate of +0.2%; Defined.ai has -21%.

### How does pricing compare?

Appen: Contact for Pricing. Enterprise/contact-for-pricing. Appen does not publish self-serve plans; projects are scoped and quoted individually. Appen also sells off-the-shelf (OTS) datasets and crowd/contractor workforce programs with separate terms. Defined.ai: Contact for Pricing. Defined.ai does not publish standard list prices; datasets and services are quoted per project. Teams can browse the marketplace, access free dataset samples and request quotes, with pricing depending on dataset type, customization, volume and delivery method.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Prolific](https://openaitools.app/tool/prolific-com) | 18,697,671 | -1.8% | Paid | Connects teams directly with verified human participants for preference tuning and studies, but lacks managed end-to-end labeling pipelines. | [.md](https://openaitools.app/tool/prolific-com.md) |
| 2 | [ModelScope](https://openaitools.app/tool/modelscope-community) | 3,085,423 | +5.1% | Free | Open-source model and dataset hub with one-click online demos | [.md](https://openaitools.app/tool/modelscope-community.md) |
| 3 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines computer vision dataset annotation and model deployment, but lacks the broad human crowd-sourcing services of Defined.ai. | [.md](https://openaitools.app/tool/roboflow.md) |
| 4 | [Invisible Technologies](https://openaitools.app/tool/invisible-technologies-inc) | 1,364,520 | +64.4% | Contact for Pricing | Blends custom software with dedicated human expert teams to handle complex operations, but operates as a bespoke service. | [.md](https://openaitools.app/tool/invisible-technologies-inc.md) |
| 5 | [Bright Data](https://openaitools.app/tool/bright-data) | 802,752 | -5.9% | Free Trial, Paid | Web data infrastructure for scraping, proxies, and AI-ready datasets | [.md](https://openaitools.app/tool/bright-data.md) |
| 6 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | Comprehensive enterprise data labeling platform with powerful automation agents, but carries significant pricing overhead for smaller teams. | [.md](https://openaitools.app/tool/labelbox.md) |
| 7 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | Provides enterprise-grade AI training data and model evaluation at massive scale, but often with higher enterprise pricing. | [.md](https://openaitools.app/tool/scale.md) |
| 8 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Delivers advanced multimodal data curation and annotation infrastructure, but requires your own annotation workforce for labeling tasks. | [.md](https://openaitools.app/tool/super-annotate.md) |
| 9 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) |
| 10 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Advanced multimodal data infrastructure for computer vision teams, though specialized primarily in video and image annotation. | [.md](https://openaitools.app/tool/encord-com.md) |

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Source: https://openaitools.app/compare/appen-com-vs-definedcrowd-com

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