# Luxand.cloud vs Scale

Luxand.cloud records 6,211 monthly visits with -40.3% month-over-month growth and Freemium, Free Trial, Paid pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.

| Metric | [Luxand.cloud](https://openaitools.app/tool/luxand-cloud) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://luxand.cloud | https://scale.com |
| Categories | AI Face Recognition, AI API, AI Developer Tools, AI Image Recognition | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Freemium, Free Trial, Paid | Contact for Pricing |
| Monthly Visits | 6,211 | 616,915 |
| MoM Growth Rate | -40.3% | +12.5% |
| Primary Market | Uzbekistan | United States |
| Direct Visits | 2,408 | 191,408 |
| Review Score | 4.1 | 4.7 |
| Saved Count | 2 | 3 |
| Supported Platforms | Website | Website |

## Luxand.cloud

Luxand.cloud is a cloud-first face recognition platform aimed at developers and businesses that want to add biometric and facial analysis to their products without building computer-vision pipelines themselves. The service groups its capabilities into three product lines: a Face API for recognition, verification, similarity, cropping, landmark detection, age/gender and emotion detection plus liveness checks; a Baby Maker API that generates a predicted image of a future baby from two parent photos using AI image generation; and an Aging API that applies realistic age-progression effects to a uploaded portrait. Every endpoint shares a consistent request/response pattern, so once a team learns one call the rest follow the same logic.

Integration is intentionally lightweight: HTTP requests work from essentially any language, and the vendor publishes copy-pasteable examples for Java, JavaScript, Node.js, Ruby, Go, Python, C# and more. Face templates — not raw photos — are stored in the cloud, which the vendor says makes it practical to share a face database across devices and services while avoiding the risk of reconstructing images from stored data. Performance is a selling point as well: face recognition is quoted at roughly 60 ms on their cloud infrastructure, and the platform scales horizontally for high-volume image processing. An on-premises FaceSDK is offered as a separate path for teams that cannot use the cloud.

Commercially, Luxand.cloud runs on a freemium model: a free tier with a limited monthly request quota and no credit card, then tiered paid plans that increase request volume, per-minute transaction rate and stored-face capacity, up to enterprise terms with 24/7 support. The company markets the API to finance, KYC/AML, payments, fintech, trading, crypto, iGaming, retail, logistics, marketing, education, transport and hospitality use cases, and positions it as one of the more cost-effective face recognition APIs on the market.

**Pricing & Plans:** Freemium with a no-credit-card free tier (limited monthly requests) plus paid subscription plans billed monthly. Published tiers start at $9/month and rise through $19, $39, $99, $249 and $1,949/month, with request quotas, per-minute transaction limits and stored-face capacity increasing at each level. All major credit/debit cards are accepted via Stripe, and there are no setup or installation fees.

- **Face recognition & verification:** Match one face against a stored gallery or confirm that two photos show the same person using consistent REST endpoints.
- **Liveness and anti-spoofing checks:** Detect whether a live person is actually in front of the camera rather than a photo or screen replay, useful for KYC and access control.
- **Age, gender and emotion detection:** Extract demographic and emotional attributes from a portrait to power personalization, analytics and audience insights.
- **Fun AI image APIs:** Separate Baby Maker and Aging APIs generate predicted baby images or realistic age-progression effects from uploaded photos for entertainment apps.
- **Multi-language integration:** Copy-paste code samples for Java, JavaScript, Node.js, Ruby, Go, Python and C#, plus a cloud template store that avoids keeping raw photos.

**Strengths:** Broad endpoint coverage — recognition, liveness, demographics and entertainment APIs in one platform; Straightforward HTTP API with code samples for most mainstream languages; Free tier with no credit card required makes evaluation easy; Transparent published pricing with no setup fees and template-based storage for better privacy

**Limitations:** Free-tier request quota is small, so real testing quickly requires a paid plan; Paid tiers jump steeply in price at the higher end; High-volume or offline scenarios may push teams toward the separate on-premises SDK

[Profile (Markdown)](https://openaitools.app/tool/luxand-cloud.md)

## Scale

Scale positions itself as the infrastructure layer for reliable AI - the data, evaluations and deployment support that sit underneath working systems rather than a single consumer-facing model. Founded in 2016, it built its reputation supplying training data and labelling capacity to the autonomous vehicle and then the generative AI wave, and now describes itself as powering a large share of the world's leading generative AI model builders.

The offering spans three broad areas. Data covers sourcing and expert annotation for training and fine-tuning, including RLHF-style preference data. Evaluation covers public leaderboards and private benchmarks used to measure model capability and safety. Applications covers the build-and-deploy side: identifying a viable use case, constructing the system and owning the outcome, with agentic AI for enterprise operations.

Scale's customer list leans heavily enterprise and public sector, including large technology companies, healthcare providers, media organisations, energy companies and government defence programmes. Because engagements are scoped rather than self-serve, pricing is arranged through a sales process, and the platform is aimed at organisations with serious data volume, strict compliance needs and a mandate to put AI into production.

**Pricing & Plans:** Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

- **Data Engine:** Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
- **Model evaluation & benchmarks:** Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
- **Enterprise AI applications:** Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
- **Agentic deployment:** Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.
- **Domain expertise:** Programmes spanning healthcare, robotics, defence, public sector and enterprise with human oversight built in.

**Strengths:** Backed by a long track record in training data and model evaluation.; End-to-end coverage from data sourcing through to deployed systems.; Experienced with regulated, classified and safety-critical environments.; Benchmarks and leaderboards give an independent view of model capability.

**Limitations:** No public pricing or self-serve signup - you need a sales conversation to get started.; Enterprise-scale contracting and data operations require real internal commitment.; Overkill for small teams with modest data or evaluation needs.; Some projects involve sensitive government and defence work with strict compliance overhead.

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

## Frequently Asked Questions

### How do Luxand.cloud and Scale compare in monthly traffic?

Luxand.cloud has 6,211 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Luxand.cloud has a month-over-month growth rate of -40.3%; Scale has +12.5%.

### How does pricing compare?

Luxand.cloud: Freemium, Free Trial, Paid. Freemium with a no-credit-card free tier (limited monthly requests) plus paid subscription plans billed monthly. Published tiers start at $9/month and rise through $19, $39, $99, $249 and $1,949/month, with request quotas, per-minute transaction limits and stored-face capacity increasing at each level. All major credit/debit cards are accepted via Stripe, and there are no setup or installation fees. Scale: Contact for Pricing. Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines computer vision dataset annotation and model training, but is less suited for general LLM text tasks. | [.md](https://openaitools.app/tool/roboflow.md) |
| 2 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | Focuses heavily on enterprise data labeling and training data curation, similar to Scale's core annotation business. | [.md](https://openaitools.app/tool/labelbox.md) |
| 3 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Provides enterprise multimodal annotation and data management tools, but with less emphasis on managed labeling workforces. | [.md](https://openaitools.app/tool/super-annotate.md) |
| 4 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 5 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation. | [.md](https://openaitools.app/tool/arize-com.md) |
| 6 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Specializes in data infrastructure and annotation specifically tailored for computer vision and physical AI workloads. | [.md](https://openaitools.app/tool/encord-com.md) |
| 7 | [Label Studio](https://openaitools.app/tool/label-studio) | 137,199 | -16.1% | Contact for Pricing, Free | Offers a flexible open-source alternative for custom data labeling and human-in-the-loop annotation pipelines. | [.md](https://openaitools.app/tool/label-studio.md) |
| 8 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Build, simulate, evaluate and monitor self-improving AI agents | [.md](https://openaitools.app/tool/future-agi.md) |
| 9 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Provides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services. | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 10 | [ComplyCube](https://openaitools.app/tool/complycube) | 85,685 | +39.6% | Contact for Pricing | Identity verification, KYC, KYB and AML compliance in one platform | [.md](https://openaitools.app/tool/complycube.md) |

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Source: https://openaitools.app/compare/luxand-cloud-vs-scale

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