Recruitment, recording, transcription, QA, and dataset delivery, run as one project. We start from your language, speaker, and recording requirements and finish with training-ready files.
Recruit, record, transcribe, structure, and audit. The same workflow on every project, configured to your data spec.
We collect monologues, dialogues, wake words, commands, scripted prompts, roleplays, and natural conversations with speakers matched to your language and profile requirements.
Remote or on-site sessions, audio-only or synchronized audio plus video.
We deliver machine-assisted or human-validated transcripts with timestamps, speaker labels, domain terminology, and annotation rules matched to your model training needs.
Word-level or segment-level timestamps, speaker labels, and human review on your QA criteria.
We package audio, transcripts, metadata, consent references, QA notes, and manifests in the format your engineering team needs.
WAV, JSON, JSONL, CSV, or custom formats. Bucket transfer, API handoff, or batch delivery.
Reviewers inspect recordings, transcripts, and metadata while the project is live. Each batch passes a quality gate before it joins the final delivery.
Cross-batch consistency, reviewer sampling, and human escalation on every project.
QA runs inside production, not at the end. These are the checks that run on every batch, every contributor, and every delivery.
Reviewers inspect recordings and transcripts while the project is live, so issues are caught during production.
Audio quality, transcript accuracy, metadata completeness, and format compliance are checked against the project spec.
Large projects run in batches. Each batch passes its own quality gate before it enters the final delivery.
Detected issues are escalated and resolved during production rather than discovered after delivery.
Cross-contributor and cross-batch consistency checks keep the full dataset to the same standard throughout.
Statistical sampling of recordings and transcripts validates quality without bottlenecking production throughput.
Three steps from your data spec to a delivered dataset your training pipeline can ingest.
Languages, accents, speaker profiles, recording setup, transcript format, metadata, and delivery requirements. We agree the spec before the first session.
Recording and transcription run alongside human QA. Issues surface during the project, not at handoff.
Audio, transcripts, metadata, and manifests packaged for direct ingestion. Mid-project adjustments and follow-on iterations are supported.
Tell us the languages, speech type, speakers, recording setup, transcript format, and metadata you need. We return within 48 hours with an initial workflow and data plan.
