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.
Funding
$15M raised to dateRaised 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.
Founders
Product
Problem
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.
Solution
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.
Target Audience
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.
Features
- Web‑based annotation interface supporting audio transcription, text entity tagging, image bounding‑box, segmentation, and classification tasks
- Global pool of vetted contributors with skill‑based routing to match annotators to specific data domains
- AI‑driven pre‑labeling that suggests initial tags, reducing manual effort and cost
- Multi‑layer quality assurance: consensus aggregation, automated validation metrics, and optional expert reviewer audit
- RESTful API and SDKs for seamless data ingestion, job submission, and result retrieval
- Real‑time project dashboard displaying progress, turnaround time, and quality statistics
- Role‑based access control, end‑to‑end encryption, and GDPR/HIPAA‑compatible data handling
- Pay‑per‑task or subscription pricing options to fit varying volume requirements