FirstHandAPI

FirstHandAPI is an AI data collection tool that lets AI teams gather real-world multimodal training data — photos, audio, video, and screen recordings — through verified human workers dispatched via a single API call. After posting a job, human contributors capture files from their phones; an AI ensemble built on Claude Vision and Whisper then scores every submission on a 1-to-5-star scale, automatically approving files rated 3 stars or above and sending structured rejection feedback for lower-quality submissions. This human-in-the-loop crowdsourced data collection pipeline eliminates the need for a separate labeling stage because every delivered file arrives pre-annotated as structured JSON with pre-signed URLs — including labels, OCR results, transcripts, speaker diarization, and scene or action tags. Geo-targeting lets teams scope jobs to specific cities or neighborhoods, which is useful for location-specific ground-truth benchmarks or regional UGC collection. The API is MCP-compatible and integrates directly with Claude Code, Cursor, OpenAI, Stripe, and AWS S3. Output is delivered as annotated JSONL files ready for vision, OCR, and speech model training. FirstHandAPI supports three primary use cases: collecting authentic user-generated content, building ground-truth evaluation benchmarks for AI models, and producing multimodal training datasets at scale. Pricing starts with $2.50 in free credits on a pay-per-file model, with example rates cited at $0.50 per file in the documentation.

AI teams and developers who need real-world multimodal training data — photos, audio, video — collected by verified humans, quality-scored by AI, and delivered as pre-annotated JSONL files ready for model training and evaluation.