# Scale vs Scalebrowser Scale records 616,915 monthly visits with +12.5% month-over-month growth and Contact for Pricing pricing. Scalebrowser records 161,955 monthly visits with +212.7% growth and Free Trial, Paid pricing. | Metric | [Scale](https://openaitools.app/tool/scale) | [Scalebrowser](https://openaitools.app/tool/scalebrowser) | | :--- | :--- | :--- | | Website URL | https://scale.com | https://scalebrowser.net | | Categories | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent | AI Browsers, AI Agent, AI Developer Tools, AI API | | Pricing Model | Contact for Pricing | Free Trial, Paid | | Monthly Visits | 616,915 | 161,955 | | MoM Growth Rate | +12.5% | +212.7% | | Primary Market | United States | Global | | Direct Visits | 191,408 | 65,234 | | Review Score | 4.7 | 4.7 | | Saved Count | 3 | 0 | | Supported Platforms | Website | Website | ## 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) ## Scalebrowser >Scalebrowser targets the part of agent work that usually breaks first: staying authenticated. Instead of scraping a signed-out page or re-logging in on every run, it hands each agent a browser machine that keeps a stable identity, complete with stored passwords, per-profile inboxes, two-factor codes and passkeys. The product installs as a desktop app so the GPU, screen and fingerprint values match the real machine, which reduces the chance that a profile contradicts itself. On top of the browser layer, Scalebrowser adds an agent layer. Agents read a page once and then only what changed, which keeps token spend predictable on long runs. Captchas are handled through human-like input, keys on a page are surfaced to the agent as placeholders, and each tool call is logged as a step with a result and a screenshot. It works with MCP clients such as Claude and Cursor, Python and Node SDKs, a REST API and direct CDP for existing browser-use code. Plans are measured by how much runs at once. The free tier covers a single browser and three profiles, while paid tiers grow concurrent browsers, machines, profiles and workflows. Workflows can be started by hand or by an agent, and higher tiers add schedules, webhooks, sync and phone approvals. **Pricing & Plans:** Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial. - **Persistent profile identity:** Each profile is generated from a seed so its identity, cookies and logins persist across restarts, and sites see the same returning visitor rather than a new device. - **Isolated browser profiles:** One browser per profile means separate logins, cookies and devices that share nothing, making multi-account automation safe to run in parallel. - **Built-in sign-in and 2FA handling:** Agents get through username and password forms, email confirmation codes, TOTP and SMS two-factor codes, passkeys and permission prompts without stalling. - **Human-like input and captchas:** Press-and-hold, image grid, slider and rotation captchas are solved through human-like input rather than third-party solving keys. - **Flexible agent integrations and trails:** Connect over MCP, Python or Node SDKs, REST or direct CDP, and review every action as a step with its result and screenshot. **Strengths:** Strong focus on persistent, isolated identities so agents stay logged in across runs; Broad integration surface covering MCP, Python/Node SDKs, REST and direct CDP; Built-in handling of logins, email codes, TOTP, SMS, passkeys and captchas; Token-efficient page reading that only reports what changed between steps **Limitations:** Requires installing a desktop app and running it on your own machine, so it is not a purely cloud-hosted service; Free tier excludes schedules, webhooks, sync and phone approvals; Paid tiers meter concurrent browsers, machines and profile counts, which can raise costs for large fleets; Advanced anti-detection features may raise compliance responsibility with target platforms [Profile (Markdown)](https://openaitools.app/tool/scalebrowser.md) ## Frequently Asked Questions ### How do Scale and Scalebrowser compare in monthly traffic? Scale has 616,915 monthly visits, while Scalebrowser has 161,955. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Scale has a month-over-month growth rate of +12.5%; Scalebrowser has +212.7%. ### How does pricing compare? 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. Scalebrowser: Free Trial, Paid. Free plan with 1 concurrent browser, 1 machine and 3 profiles, no card required. Paid plans: Start at $19/month (1 browser, 25 profiles), Solo at $49/month (5 browsers, 100 profiles), Studio at $99/month (20 browsers, 3 machines, 500 profiles), and custom Enterprise pricing. Most paid plans include a 7-day free trial. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Apify](https://openaitools.app/tool/apify) | 4,147,762 | +3.9% | Freemium, Contact for Pricing | A massive cloud web scraping and automation marketplace, though it lacks Scalebrowser's focus on persistent isolated profiles. | [.md](https://openaitools.app/tool/apify.md) | | 2 | [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) | | 3 | [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) | | 4 | [Eigent AI](https://openaitools.app/tool/eigent-ai) | 575,703 | +1.4% | Freemium, Free Trial, Contact for Pricing | Open-source desktop AI workforce that runs browser, file, and app tasks for you | [.md](https://openaitools.app/tool/eigent-ai.md) | | 5 | [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) | | 6 | [ego (lite)](https://openaitools.app/tool/ego-lite) | 384,099 | +97.6% | Free | A free Chromium-based browser optimized for running parallel AI web automation and scraping tasks locally. | [.md](https://openaitools.app/tool/ego-lite.md) | | 7 | [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) | | 8 | [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) | | 9 | [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) | | 10 | [Happycapy](https://openaitools.app/tool/happycapy) | 191,406 | +7.2% | Freemium | An agent-native computer that works while you sleep | [.md](https://openaitools.app/tool/happycapy.md) | --- Source: https://openaitools.app/compare/scale-vs-scalebrowser More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)