Multimodal data backbone for an avatar runtime
Image, video, audio, and text streams generated and curated jointly for a real-time conversational avatar — with explicit licensing posture for commercial deployment.
SVC // 09
Synthetic Dataset Generation
Purpose-built synthetic data across every format your model needs — text, audio, video, documents, chat logs, structured records, anything. Curated, license-clean, statistically defensible, and shaped to the workload. The boring details — dedupe, balance, provenance, quality flags — handled.
▌▌▌ WHAT WE DELIVER ▐▐▐
DELIVERABLES
Every format. Every edge case. Defensible.
- // TEXT CORPORA Domain prose, dialogue, instructions, Q&A pairs, structured-output exemplars. Style-matched, deduped, balanced across the dimensions that matter.
- // AUDIO & SPEECH TTS-generated speech with controllable identity, accent, prosody, and emotion; multi-speaker dialogue; environmental noise overlays; SNR ladders for robustness training.
- // VIDEO & IMAGERY Photo-realistic frames and motion sequences with controllable occlusion, weather, lighting, optical and thermal/IR variants — every sample paired with synced ground-truth annotations.
- // DOCUMENTS & FORMS Synthetic invoices, contracts, identity documents, medical forms, legal filings, magazine layouts, scans with realistic skew/noise — with ground-truth field labels.
- // CHAT & MESSAGING LOGS Multi-turn conversations, multi-party threads, instructional exchanges, refusal cases, and the safety-edge cases your eval suite needs.
- // STRUCTURED RECORDS Tabular data, sensor telemetry, transaction streams, time-series, and graphs — with realistic distributions, named edge cases, and controlled rare events.
- // LICENSING & PROVENANCE Every sample tagged with generation method, license posture, quality score, and lineage. Defensible at audit.
▌▌▌ REPRESENTATIVE ENGAGEMENTS ▐▐▐
DOSSIER
Selected work — redacted.
Eval & adaptation corpora for an agentic framework
Synthetic chat, instruction, and edge-case corpora purpose-built for evaluating and adapting a personal AI infrastructure layer.
▌▌▌ HOW WE WORK ▐▐▐
PROCESS
Specify. Generate. Certify.
- // 01 SPECIFY Define the schema, distribution targets, edge cases, and acceptance criteria — in writing — before any sample is generated.
- // 02 GENERATE Pipelines produce, validate, dedupe, balance, and provenance-tag samples at scale. Every step is reproducible from a seed.
- // 03 CERTIFY Independent quality checks, statistical sanity, model-based sample review, and a written quality report you can hand to a regulator.