# Lab Laps vs Scale

Lab Laps records 36,077 monthly visits with +203.3% month-over-month growth and Freemium, Contact for Pricing pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.

| Metric | [Lab Laps](https://openaitools.app/tool/lab-laps) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://www.lablaps.com | https://scale.com |
| Categories | AI Image Recognition, AI Image Scanning | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Freemium, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 36,077 | 616,915 |
| MoM Growth Rate | +203.3% | +12.5% |
| Primary Market | United States | United States |
| Direct Visits | 14,179 | 191,408 |
| Review Score | 4.4 | 4.7 |
| Saved Count | 0 | 3 |
| Supported Platforms | Website | Website |

## Lab Laps

Lab Laps is built around the reality of bench work, where a researcher juggles a protocol on paper, a phone timer, a spreadsheet for dilutions and separate imaging software for colony counts. The app consolidates those tasks into one environment: you write or import step-by-step protocols with timers and to-dos built in, run them at the bench, and share them with your lab. Cloud sync means the same projects open in the browser and in the iOS or Android app, and sharing links let colleagues view or import projects into their own workspace.

The AI features target the most repetitive parts of the day. Drop in a photo of a plate and the colony counter automatically boxes every colony, letting you correct the few it misses before exporting the count. A blood cell counter handles RBC, WBC and platelet counting, while gel and blot tools turn ladder and band images into publication-ready figures. Plate labelling supports colour-coded maps from 6 to 384 wells, so a layout can travel from screen to bench without transcription errors.

The calculation layer covers the arithmetic that quietly consumes lab time. Serial and reverse dilution, buffer and medium recipes, molarity, master mix and PCR setup are all handled with exact pipetting and weighing volumes, and a unit converter, custom equation calculator and periodic table round out the toolkit. Lab Laps reports being trusted by more than 70,000 researchers and offers a free tier with limited AI counts and up to five projects, with Pro removing those limits.

**Pricing & Plans:** Lab Laps is freemium. The free plan includes web lab tools with up to five projects, limited AI colony counts and access to the mobile app with up to two protocol projects. Pro unlocks unlimited projects, unlimited AI colony counting, premium tools and the full Pro experience in the iOS and Android apps. Enterprise and lab-wide arrangements are handled via contact.

- **Protocol tracking with built-in timers:** Write step-by-step protocols with timers and to-dos embedded, run multiple timers simultaneously at the bench, and share protocols with your whole lab.
- **AI colony and cell counting:** Upload a plate photo and the AI boxes every colony for quick correction; separate counters handle blood cell counting for RBC, WBC and platelets.
- **Lab calculators and conversions:** Serial and reverse dilution, buffer and medium recipes, molarity, master mix and PCR setup deliver exact volumes, alongside a unit converter, custom equation calculator and periodic table.
- **Gel, blot and plate tools:** Turn ladder and band images into labelled, publishable figures and build colour-coded plate maps from 6 up to 384 wells.
- **Cloud sync and project sharing:** Data syncs across browser and mobile so nothing is lost between devices, and share links let collaborators view or import projects within 30 days.

**Strengths:** Consolidates protocols, timers, calculators and counting that normally need several apps; AI colony counting meaningfully reduces a repetitive daily task; Free tier is genuinely usable, with paid Pro removing limits; Cross-device sync plus sharing links work well for team labs

**Limitations:** Free tier limits the number of projects and AI counts; AI counting accuracy still needs a human correction pass; Best value depends on adopting it lab-wide rather than by one person

[Profile (Markdown)](https://openaitools.app/tool/lab-laps.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 Lab Laps and Scale compare in monthly traffic?

Lab Laps has 36,077 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Lab Laps has a month-over-month growth rate of +203.3%; Scale has +12.5%.

### How does pricing compare?

Lab Laps: Freemium, Contact for Pricing. Lab Laps is freemium. The free plan includes web lab tools with up to five projects, limited AI colony counts and access to the mobile app with up to two protocol projects. Pro unlocks unlimited projects, unlimited AI colony counting, premium tools and the full Pro experience in the iOS and Android apps. Enterprise and lab-wide arrangements are handled via contact. 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 | [Pl@ntNet](https://openaitools.app/tool/plantnet-org) | 439,904 | +34.9% | Free | Identify plants from photos and contribute to biodiversity science | [.md](https://openaitools.app/tool/plantnet-org.md) |
| 4 | [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) |
| 5 | [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) |
| 6 | [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) |
| 7 | [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) |
| 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 | [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) |
| 10 | [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) |

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Source: https://openaitools.app/compare/lab-laps-vs-scale

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