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Applause: Crowdtesting and Software Testing Services

Applause helps software companies and enterprise organizations validate digital experiences using a global community of testers. It is designed for teams needing feedback across diverse device configurations and geographic markets.

At a glance

Best for
Software companies, Enterprise companies, QA teams, Product teams, Engineering teams
Pricing
Pricing was not clearly available from the provided evidence. Contracts are tailored based on complexity and scale. Buyers should confirm current pricing on the vendor website.
Key use cases
Global Market Expansion, Payment Verification, Inclusive Design Validation, Gen AI Model Evaluation, Omnichannel Journey Testing
Integrations
TestRail, Applause API, Jira, GitHub, Azure
Official website
applause.com
Screenshot of Applause website

Applause is a crowdtesting platform that connects businesses with a global community of over 1.7 million testers to identify bugs and usability issues in real-world environments. It provides an alternative to internal lab-based testing by leveraging a diverse group of experts to validate digital products across various platforms.

The service supports engineering, product, and QA teams who need to scale their testing capacity. It covers a range of technologies, including standard web and mobile apps, as well as IoT, AR/VR, and automotive tech.

Beyond functional testing, the platform offers services for accessibility, global payments, and generative AI training and evaluation. These programs are designed to help teams identify defects before products reach the end customer.

Buyers should confirm pricing via the vendor website, as services are managed and tailored to specific project requirements.

Key Features

Manual Functional Testing

Uses a global community of vetted testers to identify bugs and usability challenges.

Automated Functional Testing

Provides test automation frameworks and engineers to support increased testing coverage.

Accessibility Testing

Testing performed by experts and people with disabilities to help ensure compliance with standards such as WCAG.

Global Payment Testing

Verification of transactions using real payment instruments across different countries.

AI Training and Testing

Programs designed to train algorithms and test the outputs of Gen AI apps, models, and agentic AI systems.

User Experience (UX) Testing

UX studies led by researchers to gather insights from specific target audience demographics.

Use Cases

Global Market Expansion

Testing digital properties in different countries with local users and devices to support proper localization.

Payment Verification

Validating that domestic and international fund transfers and e-commerce checkouts process correctly.

Inclusive Design Validation

Using a diverse group of testers to help ensure apps are accessible to users with visual, hearing, or cognitive impairments.

Gen AI Model Evaluation

Using human perspectives to identify inaccuracies, bias, or toxicity in AI models before launch.

Omnichannel Journey Testing

Testing customer flows that move from digital apps to physical in-store experiences.

Best For

Software companiesEnterprise companiesQA teamsProduct teamsEngineering teams

Integrations

TestRailApplause APIJiraGitHubAzureRedminePivotalTrackerRallyYouTrackSlackWebhooksOktaJumpCloudOneLoginPing Identity

Pricing

Pricing was not clearly available from the provided evidence. Contracts are tailored based on complexity and scale. Buyers should confirm current pricing on the vendor website.

FAQ

What is crowdtesting in Applause?

Crowdtesting is an approach where Applause connects businesses with a global community of over 1.7 million independent testers to provide feedback on digital products.

How does Applause handle pricing?

Applause does not provide fixed public pricing. They offer tailored contracts based on project complexity and scale, often beginning with a focused Pilot Program.

Can Applause test AI applications?

Yes, they provide services for training and testing Generative AI apps and models, as well as agentic AI systems, to help reduce bias and inaccuracy.

Source category: Software Development

Source subcategory: Test Automation

Software Type:

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