Daniela Braga
Founder & CEO
The company provides an on‑demand data annotation platform that lets machine‑learning engineers upload audio, text, or image assets via a web UI or API and receive labeled data in standard formats ready for training pipelines. A global pool of vetted contributors performs task‑specific labeling, augmented by AI‑driven pre‑labeling and multi‑pass quality assurance, while role‑based access controls and encryption ensure compliance.
Raised to date
$15MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.



Founder & CEO
Machine learning projects require large, accurately labeled datasets, but manual annotation is often slow, costly, and inconsistent. Organizations lacking in‑house labeling capacity struggle to scale data preparation, leading to delayed model development and suboptimal performance.
The platform delivers on‑demand data annotation and validation through a vetted, global network of contributors. Users upload raw speech, text, or image assets via a web portal or API, and the workforce applies task‑specific labeling workflows. AI‑assisted pre‑labeling accelerates the process, while multi‑pass quality checks—including consensus voting and expert review—ensure high‑precision outputs. All results are returned in standardized formats ready for immediate ingestion into training pipelines. The service scales elastically to handle projects of any size, and data is protected with role‑based access controls and compliance‑grade encryption.
Primary customers are machine‑learning engineers, data‑science teams, and AI product organizations that need scalable, high‑quality labeled datasets for speech, text, and image modalities.