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

Appen's computer vision automation helped a leading global security and aerospace company fight wildfires. The company used machine learning to predict wildfire paths and improve resource deployment.... Appen's platform enabled accurate data labeling with multi-sensor integration and advanced annotation tools. The solution saved time by allowing data annotation at the storage point, keeping data secure. The platform supported many data types, helping data scientists use new sources and improve model accuracy.
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FlamingoAI used Appen's training data to launch its virtual assistant fully automated from day one. The challenge was to solve the cold-start problem for financial and insurance clients who wanted in...stant automation. Appen provided high-quality, real-world data to train the assistant before deployment. After seven weeks, the assistant answered over 80% of customer questions and achieved a 30% conversion rate for life insurance quotes. FlamingoAI improved customer experience and sales conversion with Appen's data solutions.
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Appen's platform helped the London School of Economics speed up data labeling for political text analysis. The team replaced slow, expert-only annotation with Appen's global crowd, cutting weeks of w...ork down to four to five hours. They labeled 20,000 sentences from six political parties, each up to 20 times, and replicated studies in several languages. Appen's reporting features and validation metrics improved data quality and reduced bias. The solution enabled LSE to build machine learning models for political text sophistication and publish results in top journals.
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Appen used its AI data platform to help a global technology company improve its large language model (LLM) across 70+ dialects in 30+ languages. The project delivered over 250,000 rows of dialogue da...ta for supervised fine-tuning. Native speakers ranked model responses for relevance, coherence, and accuracy. The LLM now gives more accurate and culturally aligned answers. User satisfaction and model accuracy improved with better linguistic diversity.
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Appen helped Dialpad boost labeler accuracy from 70% to 88% in just weeks. Dialpad uses Appen to create transcription and NLP training data for their speech recognition models. The platform enables a...ccurate audio transcription, data classification, and geolocation labeling. Dialpad now maintains high accuracy across diverse models. This partnership supports scalable, high-quality machine learning for human conversation analysis.
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Appen helped a top-10 multinational software provider optimize its global SaaS eCommerce platform. The provider faced challenges with transaction funnels across multiple markets and product types. Ap...pen designed a multilingual usability study to find bottlenecks and improve user experience. The study delivered clean, accurate data for both quantitative and qualitative analysis. The provider improved its eCommerce sales and returned for further optimization studies.
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