Popular AI Services Use Cases

Scalable collection of diverse speech samples across languages, accents, age groups, and environments—vital for training speech recognition and voice AI models.

From object detection to semantic segmentation, Truelancer's annotators label millions of images and video frames for applications like autonomous driving, visual search, and facial recognition.

Support for tasks such as sentiment tagging, topic classification, intent detection, and named entity recognition (NER) across 50+ languages and domains.

High-quality human transcription of audio clips with support for diarization, timestamping, and multi-language tagging, used to fine-tune ASR and voicebot models.

Create training data for LLMs using prompt engineering, creative text generation, and classification. Includes instruction-following, paraphrasing, and chain-of-thought annotation.

Manual dataset reviews to identify and flag bias, NSFW content, spam, and irrelevance—ensuring your training datasets remain clean, ethical, and compliant.

Evaluate search results or recommendations by relevance, quality, and context—helping improve ML models for ranking, personalization, and recommendation.

Truelancer teams annotate opinions and emotional tone in user-generated content to train sentiment detection and opinion mining models.

Human translators provide culturally accurate translations and regional localization for multi-language AI models and global product rollouts.

Crowdsourced fairness testing across geographies, ethnicities, and gender identities helps identify and reduce unintended bias in AI systems.