Products
Expertise is not absorbed from a textbook. It is earned through demonstration, correction, and hours of practice — and the same holds for the models we train.
Our products cover that whole range: the voices people actually use, the scenes they move through, and the judgment of the professionals who do the work. As the frontier of what models can do expands, so does what they need to learn from.
Speech-to-Text (STT) Audio Data
Speech the way people actually produce it: monologue reads, spontaneous talk, and real-world captures across accents and acoustic conditions. Every recording ships with a human-verified transcript, speaker metadata, and an annotation layer covering event tags, paralinguistics, and disfluencies — the hesitations stay in, because that is what a model meets in production.
Text-to-Speech (TTS) Audio Data
Studio-grade voice data recorded for synthesis — 48 kHz / 24-bit from studio microphones with a calibrated noise floor, phonetically balanced scripts, and consistent timbre across hours of material from the same speaker. Transcripts are human-verified and annotated for prosody, emphasis, and breath, so the ceiling on your model is the model rather than the corpus.
Full-Duplex Audio Data
Two-speaker conversations captured on separate channels, so overlap, interruption, and backchannels survive into training. The turn-taking is real rather than stitched together from single-speaker recordings after the fact, and every session is transcribed and annotated by humans: speaker-attributed turns with timestamps, overlap and backchannel tags, paralinguistics, and disfluencies.
Full-Duplex Audiovisual Data
The same two-speaker conversations with synced 4K video on each participant, so gaze, gesture, and mouth movement line up frame-accurately with both sides of the audio. Lens, lighting, and sensor are documented per session, captures ship as a color-graded master plus a delivery proxy, and the human-verified transcription and annotation layer carries over from the audio.
Transcription-as-a-Service
The same annotation pipeline, run on your audio instead of ours: emotion trajectory across a turn, emotional tags, end-of-utterance (EOU) boundaries, overlap and backchannel events, and speaker attribution, every pass human-verified. Domain-heavy audio is staffed from our expert network — physicians on clinical recordings, attorneys on depositions.
Professional Voice Actor Voices and Audio Data
Default voices you can license today, already recorded — or the same actors booked for a session against your script. A deep network that includes performers with film and Hollywood credits, studio-captured with consistent timbre across domains from call-center to clinical intake, profiles spanning age, accent, and register, personas held steady between sessions, and the alphanumerics, addresses, and spelled-out strings that break models in production. Usage rights, releases, and the legal work for commercial synthesis and cloning are settled before delivery.
Expert Professional Domains
Doctors, lawyers, engineers, financial analysts, and linguists drawn from a vetted network of 10,000+ practitioners across 40+ languages. They write the prompts, grade the outputs, and settle the edge cases a textbook never reaches.
Internationalization
We work in 40+ languages, and the job is never translation. A Korean legal summary, a Brazilian news headline, an Arabic dialogue — each carries grammar, idiom, and assumptions that a translated corpus quietly flattens. Native linguists design the data so a model picks up the culture along with the words.
Multimodal Data
Text, image, audio, and video reasoning inside a single dataset — reading a chart aloud, describing what changed between two frames, answering a question that spans a document and a recording at once.
Off-the-Shelf Data
A catalogue that is already collected, cleared, and documented. Hours of speech across languages, accents, and recording tiers that your team can evaluate this week instead of waiting out a collection cycle.
Custom Evals and Training Datasets
Evaluation suites and training sets built against your capability targets rather than a public benchmark. Every prompt, rubric, and environment is designed from scratch, starting from the gaps your own error analysis turned up.