QA.tech records 30,550 monthly visits with -4.4% month-over-month growth and Paid, Contact for Pricing pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.
Autonomous AI QA agents that verify your web and mobile app on every pull request
The data, evaluations and systems behind AI that has to be right.
| Dimension / Metric | | |
|---|---|---|
| Official Domain | qa.tech | scale.com |
| Pricing Model | Paid, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 30.55K (30,550) | 616.92K (616,915) |
| MoM Traffic Delta | -1.42K (-4.4%) | +68.69K (+12.5%) |
| Primary Market & Share | 🇸🇪 Sweden (24.4%) | 🇺🇸 United States (44.2%) |
| Direct Visits / mo | 21.23K | 191.41K |
| User Rating | 4.3 | 4.7 |
| Supported Platforms | Website | Website |
Autonomous AI QA agents that verify your web and mobile app on every pull request
Describe a journey or rule in chat and the agent turns it into durable test cases that survive refactors and redesigns.
Every pull request gets a dynamic exploratory pass with preview environments, failure breakdowns, screenshots, console and network logs.
Agents target real browsers and native iOS and Android apps, so coverage reaches beyond the web front end.
Findings flow into Jira and Linear, and agents can be queried over MCP by other coding agents.
The data, evaluations and systems behind AI that has to be right.
Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.
SpecialistStreamlines computer vision dataset annotation and model training, but is less suited for general LLM text tasks.
SpecialistStreamlines computer vision dataset annotation and model training, but is less suited for general LLM text tasks.
GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language
Focuses heavily on enterprise data labeling and training data curation, similar to Scale's core annotation business.
Focuses heavily on enterprise data labeling and training data curation, similar to Scale's core annotation business.
Provides enterprise multimodal annotation and data management tools, but with less emphasis on managed labeling workforces.
Provides enterprise multimodal annotation and data management tools, but with less emphasis on managed labeling workforces.
Ship with confidence: one system of record for manual, automated, and CI tests
SpecialistTrack, evaluate, and ship AI models and agents in one connected environment.
SpecialistTrack, evaluate, and ship AI models and agents in one connected environment.
SpecialistFocuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.
SpecialistFocuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.
Specializes in data infrastructure and annotation specifically tailored for computer vision and physical AI workloads.
Specializes in data infrastructure and annotation specifically tailored for computer vision and physical AI workloads.
AI-augmented quality platform for web, mobile, API and desktop testing
Free / Open-sourceOffers a flexible open-source alternative for custom data labeling and human-in-the-loop annotation pipelines.
Free / Open-sourceOffers a flexible open-source alternative for custom data labeling and human-in-the-loop annotation pipelines.
SpecialistBuild, simulate, evaluate and monitor self-improving AI agents
SpecialistBuild, simulate, evaluate and monitor self-improving AI agents
SpecialistProvides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services.
SpecialistProvides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services.
