# Appen vs Grably

Appen records 665,840 monthly visits with +0.2% month-over-month growth and Contact for Pricing pricing. Grably records 1,923 monthly visits with -13% growth and Contact for Pricing pricing.

| Metric | [Appen](https://openaitools.app/tool/appen-com) | [Grably](https://openaitools.app/tool/grably) |
| :--- | :--- | :--- |
| Website URL | https://appen.com | https://grably.us |
| Categories | AI Models, Large Language Models (LLMs), AI Developer Tools | AI Developer Tools, AI Image Recognition, Large Language Models (LLMs) |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 665,840 | 1,923 |
| MoM Growth Rate | +0.2% | -13% |
| Primary Market | United States | Global |
| Direct Visits | 238,314 | 683 |
| Review Score | 4.4 | 3.8 |
| 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)

## Grably

Grably is a multi-modal human interaction data research company. Rather than selling generic web scrapes, it positions itself as a lab that captures and models how people act, sense, decide, and communicate, then packages that into structured datasets for AI developers. Its site highlights backing from Techstars and partnerships with leading AI labs and technology companies.

The company organizes its offering into suites for image, video, audio, code, and text, alongside a catalogue of multi-modal conversational data. Publicly described assets include billions of sequential messages in more than 100 languages, thousands of hours of labelled sports footage, and tens of millions of medical studies. Each dataset is aimed at a specific modelling need, from LLM pretraining and multilingual coverage to embodied AI, temporal video understanding, speech, and document intelligence.

Grably also builds custom datasets for clients with niche goals, aligning anonymization, filtering, and delivery formats to internal research, legal, and infrastructure requirements. Delivery timelines vary by modality, and pricing is scoped per engagement, so prospective buyers discuss requirements directly with the team. The overall pitch is data quality and human-centred signal, not volume alone.

**Pricing & Plans:** Pricing is contact-based. Each dataset or custom project is quoted according to scope, modalities, and delivery requirements.

- **Multi-modal data suites:** Datasets covering image, video, audio, code, text, and conversational interaction for varied model-training needs.
- **Custom dataset design:** Buyer-scoped datasets with configurable anonymization, filtering, modalities, and delivery formats.
- **Multilingual coverage:** Conversational and text data spanning 100+ languages, including low-resource and underrepresented regions.
- **Structured, annotated content:** Signals that are aligned, annotated, and validated for cross-modality and scientific consistency.
- **Domain-specific corpora:** Specialized datasets for sports, medical records, documents, scientific literature, and code.

**Strengths:** Broad multi-modal and multilingual dataset catalogue; Custom dataset design with configurable anonymization; Enterprise and research-lab oriented delivery; Backed by a recognised accelerator program

**Limitations:** No self-serve pricing or instant purchase flow; Dataset access requires a sales conversation; Delivery timelines for rich modalities can span weeks

[Profile (Markdown)](https://openaitools.app/tool/grably.md)

## Frequently Asked Questions

### How do Appen and Grably compare in monthly traffic?

Appen has 665,840 monthly visits, while Grably has 1,923. 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%; Grably has -13%.

### 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. Grably: Contact for Pricing. Pricing is contact-based. Each dataset or custom project is quoted according to scope, modalities, and delivery requirements.

## 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 | [clickworker](https://openaitools.app/tool/clickworker-com) | 1,861,149 | +0.5% | Contact for Pricing | Crowdsourcing data services for AI training and market data | [.md](https://openaitools.app/tool/clickworker-com.md) |
| 3 | [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) |
| 4 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | Combines robust data labeling tools with automated workflows, but focuses more on software tooling than managed human workforces. | [.md](https://openaitools.app/tool/labelbox.md) |
| 5 | [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) |
| 6 | [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) |
| 7 | [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) |
| 8 | [Surge AI](https://openaitools.app/tool/surgehq-ai) | 245,142 | +6.6% | Contact for Pricing | Expert human data and evaluation for training frontier AI | [.md](https://openaitools.app/tool/surgehq-ai.md) |
| 9 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | The multimodal data layer for computer vision and physical AI teams | [.md](https://openaitools.app/tool/encord-com.md) |
| 10 | [Wirestock](https://openaitools.app/tool/wirestock) | 167,156 | +12.9% | Freemium | Where creators get paid and AI teams get premium training data | [.md](https://openaitools.app/tool/wirestock.md) |

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

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