Besimple AI

Besimple AI is a Y Combinator-backed company (Spring 2025 / X25 batch) building what it describes as the data layer for AI, starting with audio. It curates a proprietary set of conversational audio spanning a wide range of languages, dialects and accents, then uses human expert audio annotators together with its own annotation platform to process that audio for automatic speech recognition, including transcription and speaker diarization. The company states it holds over millions of hours of conversational data, sourced through a global network of independent contributors covering 15+ languages and diverse accents, and can run custom collections to a customer's specification, including role-plays and domain-specific conversations.

Alongside the dataset business, the company has offered a self-serve annotation product that generates a tailored annotation platform from raw data pasted or streamed in by the customer. That product supports text, chat, audio, video and LLM traces, drafts or imports annotation guidelines, provides an automated human-in-the-loop workflow, and uses LLM-based "AI judges" that learn from incoming annotations to evaluate live traffic and flag borderline cases for human review. Deployment options include on-premise installation and user management for internal subject-matter experts, external vendors or Besimple's own vetted annotators.

Delivery follows a defined onboarding sequence: a scoping conversation about hours, languages and scenarios; sample delivery within 48 hours for quality and metadata review; validation of samples in the customer's own training pipeline; production access to full datasets via API or S3; and scaling of annotation capacity from roughly 10 to 100+ annotators with monthly dataset expansions. The company also publishes audio-model benchmarks, including Vocal Affect Bench and Voice Code Bench.

Founding story

Founded in 2025 by Yi Zhong and Bill Wang, who met the problem while at Meta, where they spent years building data infrastructure and the annotation platform for the Llama team. Zhong is described as an AI product leader with prior roles at Meta, Microsoft and Dropbox; Wang previously led Meta's GenAI Annotation team, developing an in-house annotation platform for Llama training, and earlier managed an engineering organization working on connectivity for over 300 million users and Meta's SMS spend optimization.

Business model

B2B. Besimple AI sells access to conversational audio datasets and annotation services to AI teams, offering flexible licensing arrangements it describes as suited to both startups and enterprises, with delivery via API or S3 and optional custom collection and annotation work. It has also offered a self-serve annotation platform product with an enterprise and on-premise deployment option.

Data licensing and paid annotation/data-collection services, with licensing deals structured for startups and enterprises; an annotation platform product is also offered, including a waitlist-based self-serve path.

Traction

The company reports over millions of hours of conversational audio data and a global contributor network covering 15+ languages. Edexia, an AI grading company, is cited as a user of the annotation product. Team size is reported at six.

Latest developments

Announced a $3M seed round on 2025-11-26 funded by Y Combinator and several venture firms and angels, stated it was hiring, and published audio-model benchmarks including Voice Code Bench (2026-05-01) and Vocal Affect Bench (2026-07-07). Open roles include an audio QA lead contractor, a strategic projects lead for audio data, and a mobile engineer.