# Antom vs Scale

Antom records 2,337,988 monthly visits with +28.6% month-over-month growth and Contact for Pricing pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.

| Metric | [Antom](https://openaitools.app/tool/antom) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://www.antom.com | https://scale.com |
| Categories | AI For Finance | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 2,337,988 | 616,915 |
| MoM Growth Rate | +28.6% | +12.5% |
| Primary Market | China | United States |
| Direct Visits | 212,942 | 191,408 |
| Review Score | 4.2 | 4.7 |
| Saved Count | 0 | 3 |
| Supported Platforms | Website | Website |

## Antom

Antom is a unified payment platform built for merchants that sell across borders. Through one integration, businesses can accept more than 300 payment methods — cards, digital wallets, online banking and buy-now-pay-later options — in over 200 markets and 140+ currencies, with strong coverage of high-growth Asian markets.

Beyond raw acceptance, Antom layers AI across the payment lifecycle. Antom Payment Orchestration uses smart routing to lift authorisation success rates, while Antom Shield performs real-time fraud decisioning trained on billions of data points. Subscription and usage-based billing modules handle recurring revenue, metered charging, invoicing and global tax compliance.

The platform also includes growth tooling such as A+ Rewards for wallet cashback and loyalty campaigns, plus ready-made Shopify and WooCommerce plugins for merchants that want to go live without development work. It is positioned for e-commerce stores, platforms, travel, gaming, digital entertainment and retail brands.

**Pricing & Plans:** Antom uses a contact-for-pricing model. Merchant fees depend on markets, payment method mix and volume, with a transparent fee structure and no hidden charges advertised; Shopify and WooCommerce plugins are self-serve to install.

- **300+ payment methods, one integration:** Accept cards, wallets, online banking and BNPL across 200+ markets and 140+ currencies through a single gateway.
- **Antom Payment Orchestration:** Route transactions across multiple gateways, acquirers and wallets with smart routing to raise success rates and cut development cost.
- **Antom Shield fraud management:** AI-driven risk decisions delivered in real time, trained on billions of data points to widen fraud coverage without blocking good buyers.
- **Subscription and usage-based billing:** End-to-end subscription management, metered usage billing, invoicing and collections, plus automation for global tax compliance.
- **A+ Rewards and commerce plugins:** Run cashback, coupon and loyalty campaigns to wallet users, and switch on Shopify or WooCommerce payments without code.

**Strengths:** Very broad coverage of local Asian and global payment methods; AI orchestration and fraud tools tuned for conversion, not just approval; Built-in subscription, metered billing and tax automation for recurring revenue; Ready-made Shopify and WooCommerce plugins reduce integration effort

**Limitations:** Pricing is quote-based, so costs are not transparent up front; Full value depends on committing to the Antom stack rather than picking modules à la carte; Advanced orchestration and shield features assume a reasonably high transaction volume

[Profile (Markdown)](https://openaitools.app/tool/antom.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 Antom and Scale compare in monthly traffic?

Antom has 2,337,988 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Antom has a month-over-month growth rate of +28.6%; Scale has +12.5%.

### How does pricing compare?

Antom: Contact for Pricing. Antom uses a contact-for-pricing model. Merchant fees depend on markets, payment method mix and volume, with a transparent fee structure and no hidden charges advertised; Shopify and WooCommerce plugins are self-serve to install. 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 | [xPay](https://openaitools.app/tool/xpay) | 223,057 | +152.8% | Paid, Contact for Pricing | Provides similar cross-border payment processing and checkout integration, but focuses more on standard international gateway services than full merchant digitalization. | [.md](https://openaitools.app/tool/xpay.md) |
| 8 | [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) |
| 9 | [Waffo.ai (Waffo Pancake)](https://openaitools.app/tool/waffo-ai) | 132,327 | +71.2% | Paid (per transaction, volume discounts) | Acts as a merchant of record handling global billing and tax compliance, similar to Antom's checkout infrastructure. | [.md](https://openaitools.app/tool/waffo-ai.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/antom-vs-scale

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