# Appen vs ShareID Appen records 665,840 monthly visits with +0.2% month-over-month growth and Contact for Pricing pricing. ShareID records 3,618 monthly visits with +200.5% growth and Contact for Pricing pricing. | Metric | [Appen](https://openaitools.app/tool/appen-com) | [ShareID](https://openaitools.app/tool/shareid) | | :--- | :--- | :--- | | Website URL | https://appen.com | https://shareid.ai | | Categories | AI Models, Large Language Models (LLMs), AI Developer Tools | AI Face Recognition, AI Detector, AI Image Recognition | | Pricing Model | Contact for Pricing | Contact for Pricing | | Monthly Visits | 665,840 | 3,618 | | MoM Growth Rate | +0.2% | +200.5% | | Primary Market | United States | United States | | Direct Visits | 238,314 | 1,440 | | Review Score | 4.4 | 4.1 | | Saved Count | 2 | 2 | | 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) ## ShareID ShareID positions itself as an identity hub rather than a single verification widget. Its modules cover document authenticity checks performed by photo, video or NFC, active and passive liveness detection aligned with the low, substantial and high eIDAS 2.0 assurance levels, and the issuance and verification of EUDI Wallet attestations such as PID, EAA and QEAA. A fourth module, described as MFA 3.0, lets users authenticate to services with their EUDI Wallet instead of a password, reusing an identity verification already performed. What makes the platform distinctive is the assembly model. You pick the journeys you need, stack optional behaviours such as reusable versus single-use identity, assisted or unattended flows and intelligent fallback, then deploy through customisable SDKs for web and native apps. Everything runs behind a management console where teams review each request, override automated rejections when the model got it wrong, and track volumes, success rates and fraud typologies. Results are retained only for the authorised retention window. Compliance is treated as a first-class feature: the platform states that all eIDAS 2.0 assurance levels are supported by design, and that it helps with GDPR and related requirements. It is available as SaaS, on-premise or on SecNumCloud. ShareID reports 92% first-attempt enrollment success and 99.9% document authentication accuracy, and states that 0% of personal or biometric data is stored. The company also works with the French Gendarmerie Nationale on document fraud detection. **Pricing & Plans:** Not published; ShareID uses contact-for-pricing sales with a free trial available. Deployment can be SaaS, on-premise or on SecNumCloud, which typically implies volume- and scope-based quoting. - **Document identity verification:** Verify ID document authenticity by photo, video or NFC at low, substantial or high eIDAS 2.0 assurance levels. - **Active and passive liveness detection:** Detect spoofing attempts with liveness checks that adapt to your required assurance level and follow ETSI TS 119 461 alignment. - **EUDI Wallet attestations:** Enroll users with their PID attestations and issue or verify EAA and QEAA attestations in line with EUDI Wallet specifications. - **Passwordless strong authentication:** Let users sign in with their real, already-verified identity through EUDI Wallet authentication rather than a password. - **Management console and analytics:** Review every verification request, override automated decisions, and monitor volumes, success rates and fraud typologies in one place. **Strengths:** covers all eIDAS 2.0 assurance levels by design; States that no personal or biometric data is stored; Modular: pick only the verification blocks you need; Flexible deployment, including on-premise and SecNumCloud **Limitations:** No public pricing; you must contact sales to get a quote; Feature depth aimed at regulated enterprises, which may be heavy for small teams; EU-centric design assumes users hold an EUDI Wallet or EU-recognised documents [Profile (Markdown)](https://openaitools.app/tool/shareid.md) ## Frequently Asked Questions ### How do Appen and ShareID compare in monthly traffic? Appen has 665,840 monthly visits, while ShareID has 3,618. 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%; ShareID has +200.5%. ### 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. ShareID: Contact for Pricing. Not published; ShareID uses contact-for-pricing sales with a free trial available. Deployment can be SaaS, on-premise or on SecNumCloud, which typically implies volume- and scope-based quoting. ## 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 | [Undetectable AI](https://openaitools.app/tool/undetectable-ai) | 3,113,403 | +17.5% | Freemium | Detect, humanize and verify AI content in one place | [.md](https://openaitools.app/tool/undetectable-ai.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 | [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) | | 9 | [Face Search AI](https://openaitools.app/tool/face-search-ai) | 211,136 | +10% | Freemium, Paid | Reverse face search across the public web, with strong privacy guardrails | [.md](https://openaitools.app/tool/face-search-ai.md) | | 10 | [Defined.ai](https://openaitools.app/tool/definedcrowd-com) | 146,251 | -21% | Contact for Pricing | Offers pre-packaged AI training datasets and custom data collection services, but with a smaller global crowd than Appen. | [.md](https://openaitools.app/tool/definedcrowd-com.md) | --- Source: https://openaitools.app/compare/appen-com-vs-shareid More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)