# Lunit vs Scale

Lunit records 29,181 monthly visits with -12.8% 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 | [Lunit](https://openaitools.app/tool/lunit) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://www.lunit.io/en | https://scale.com |
| Categories | AI Healthcare, AI Medical Diagnosis, AI Image Recognition | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Contact for Pricing | Contact for Pricing |
| Monthly Visits | 29,181 | 616,915 |
| MoM Growth Rate | -12.8% | +12.5% |
| Primary Market | South Korea | United States |
| Direct Visits | 8,314 | 191,408 |
| Review Score | 4.6 | 4.7 |
| Saved Count | 1 | 3 |
| Supported Platforms | Website | Website |

## Lunit

Lunit is a medical AI company headquartered in Seoul, South Korea, spun out of deep-learning research and focused squarely on oncology. Rather than chasing general-purpose healthcare AI, it has built two connected product families: one that helps clinicians find cancer earlier in imaging, and one that extracts quantitative biology from tissue to guide treatment and drug development. Its technology is used across a large international footprint spanning more than 10,000 customer sites in over 70 countries, with hundreds of peer-reviewed publications and industry partnerships behind the deployments.

On the screening side, the Lunit INSIGHT family analyzes mammograms and chest radiographs. Lunit INSIGHT MMG handles 2D mammography while Lunit INSIGHT DBT covers 3D breast tomosynthesis, both designed to flag suspicious regions so radiologists can prioritize the studies that need attention most. Lunit INSIGHT CXR does the same for chest X-rays. Around these detection engines Lunit has assembled program-level tooling: density assessment, risk assessment and risk pathways, live mammography reporting, quality management, analytics, and a patient hub, so a screening service can run AI as part of its routine rather than as an isolated experiment.

On the precision oncology side, the Lunit SCOPE portfolio analyzes pathology images. Lunit SCOPE IO quantifies the tumor microenvironment and immune cell infiltration, which matters for immunotherapy strategy, while the Lunit SCOPE IHC Suite supports immunohistochemistry quantification across markers such as HER2 and PD-L1, alongside a genotype prediction tool. These products are aimed at biopharma partners, clinical trial teams, and companion diagnostic development, where reproducible quantitative readouts are the bottleneck. Because Lunit sells to hospitals, screening programs, and pharmaceutical companies, pricing is quoted directly rather than published, and regulatory status differs by market.

**Pricing & Plans:** Contact for pricing. Lunit sells enterprise software and platform licenses to hospitals, screening programs, and biopharma partners, so commercial terms and deployment costs are quoted directly through its sales team. No public price list is offered.

- **Lunit INSIGHT MMG and DBT:** Deep-learning analysis of 2D and 3D mammography that marks suspicious lesions to help radiologists detect breast cancer earlier and reduce missed findings.
- **Lunit INSIGHT CXR:** Chest X-ray analysis that highlights potential abnormalities such as nodules and other findings, supporting faster triage in high-volume radiology workflows.
- **Lunit SCOPE IO:** Tumor microenvironment analysis that quantifies tumor-infiltrating lymphocytes and immune phenotypes from pathology slides, informing immunotherapy research.
- **Lunit SCOPE IHC Suite:** AI-assisted immunohistochemistry quantification covering HER2, PD-L1, and other markers, including uIHC and a gene-expression prediction tool for standardized scoring.
- **Screening analytics and workflow tools:** Live mammography reporting, risk assessment, risk pathways, quality management, and patient-facing tools that embed AI into the wider screening program.

**Strengths:** Clinically validated radiology AI with documented regulatory clearances and published evidence; Covers two ends of the cancer pathway — screening detection and precision oncology biomarkers — in one vendor relationship; Wide real-world adoption across many countries, which means integrations and workflow lessons already exist; Strong research output and biopharma partnerships support credibility for trial and CDx work

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

Lunit has 29,181 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Lunit has a month-over-month growth rate of -12.8%; Scale has +12.5%.

### How does pricing compare?

Lunit: Contact for Pricing. Contact for pricing. Lunit sells enterprise software and platform licenses to hospitals, screening programs, and biopharma partners, so commercial terms and deployment costs are quoted directly through its sales team. No public price list is offered. 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 | [ScanSkinAI](https://openaitools.app/tool/scanskinai) | 265,770 | -10.9% | Freemium, Paid | Free AI skin and mole scanning with optional dermatologist review | [.md](https://openaitools.app/tool/scanskinai.md) |
| 6 | [Overjet](https://openaitools.app/tool/overjet-ai) | 256,150 | +12.6% | Contact for Pricing | FDA-cleared dental AI for diagnostics, imaging, and insurance workflow | [.md](https://openaitools.app/tool/overjet-ai.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Pearl](https://openaitools.app/tool/hellopearl-com) | 221,155 | -7.6% | Contact for Pricing | FDA-cleared dental AI for sharper diagnosis and a smoother front office | [.md](https://openaitools.app/tool/hellopearl-com.md) |
| 10 | [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) |

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

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