Appen platform: Use-Cases, Insights and Reviews | 2026 Cuspera

Appen's text-to-speech engine helped GuildLink deliver audio Consumer Medicines Information to patients. GuildLink needed to make medicine information accessible for people with vision impairment, la...nguage barriers, or learning disabilities. Appen built a custom lexicon and processed text files to create accurate audio output. GuildLink became the first to offer audio CMIs, leading to partnerships with Australian government websites. This improved access to medical information for many consumers.
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Appen Data Annotation Platform helped Trust Lab analyze user sentiment on millions of pieces of user generated content. Trust Lab used this data to identify high risk and unsafe content, accounts, an...d transactions at scale. The platform enabled Trust Lab to provide detailed trust and safety recommendations to internet platforms. This improved user safety and helped platforms enforce better content moderation. Trust Lab praised Appen for its expertise and scalability in delivering sentiment metrics.
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Appen's platform helped a large US-based gaming company scale its AI-powered customer support. The company needed more training data for chatbots to better understand player requests. Appen replaced ...manual Excel processes with a central data repository and enabled fast onboarding of internal labelers. The team grew, reviewing labeled data faster and improving chatbot response times. Data rows increased nearly 12-fold, leading to more personalized support and better customer interactions.
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Appen helped Shotzr speed up image labeling for location metadata using machine learning. Shotzr faced a challenge with scaling manual annotation for nearly 100 million images. With Appen's platform,... Shotzr identified over 17,000 images that did not need extra labeling after the first job. They expect to remove over 61 million assets from location data review. This lets Shotzr focus on images that need location tags and build new models faster.
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Appen helped a leading social media platform improve content relevance with a personalized news feed. The company needed a diverse rater pool and fast global scaling to train its machine learning alg...orithm. Appen delivered a scalable onboarding module and 24/7 data collection, expanding the pilot into an ongoing program. The platform now delivers more personalized content and refines its algorithm faster, meeting strict quality standards and adapting quickly to changing needs.
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Appen used its AI data platform (ADAP) to help a leading model builder evaluate 3-6 large language models (LLMs) in complex domains like healthcare, legal, and finance. The team delivered over 500,00...0 annotations in 5-day sprints of 50,000+ each. Expert evaluators ran structured A/B tests to check model accuracy, relevance, and Responsible AI standards. The project gave the client actionable insights for model improvement and domain-specific accuracy. Appen's process enabled rapid iteration and better LLM performance across industries.
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