graveiensai

AI training data services turn raw, real-world signals — text, images, video, and audio — into structured, model-ready datasets through human collection, labeling, transcription, and review. In short: they convert mess into something your model can actually learn from.

The full pipeline usually spans four stages:

• Data collection — sourcing and capturing images, speech, text, and sensor data to a written spec
• Annotation & labeling — bounding boxes, segmentation, 3D point clouds, NER, sentiment, and more
• Transcription — verbatim and clean-read audio for ASR training and evaluation
• LLM fine-tuning & evaluation — RLHF preference data, supervised fine-tuning, and expert red-teaming