The startup develops a behavioral simulator that automates the collection and curation of training data for AI computer vision applications, significantly reducing the time required for model preparation. Its platform enables the deployment of production-ready AI systems across various sectors, including retail, healthcare, and smart cities, by enhancing the understanding of human interactions.
Funding
$12.9M 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
AI computer vision models require large, diverse, and accurately labeled training datasets, which are often time-consuming and expensive to collect and curate using traditional methods. Real-world data collection can also raise privacy concerns and may not adequately represent rare or edge-case scenarios critical for robust model performance.
Solution
Mindtech Global offers a platform and data packs for generating synthetic data to train AI vision systems, addressing the limitations of real-world data collection. The Chameleon platform allows data scientists to create and customize synthetic datasets, blending them with real-world data to improve model accuracy and reduce bias. The platform includes tools for asset management, scenario editing, automated sequence production, and data curation, enabling users to specify, create, and refine training data efficiently. Mindtech also provides pre-built, GDPR-compliant data packs tailored for specific industries and use cases, offering a faster and more cost-effective alternative to manual data collection and annotation.
Target Audience
The primary target audience includes data scientists, AI engineers, and computer vision specialists in industries such as automotive, retail, smart cities, manufacturing, safety and security who require high-quality, privacy-compliant training data for AI vision systems.
Features
- Chameleon Platform: A behavioral simulator for creating relevant synthetic data, featuring an asset manager, scenario editor, simulator, and curation manager.
- Real-World Alignment: Tools to build virtual environments that mirror real-world conditions, including dynamic environments with adjustable lighting, weather, and time of day.
- Scalable and Customizable: The platform can be adapted to fit specific AI training needs, with features like per-character annotation, segmentation, and customizable text.
- Data Packs: Pre-built, customizable data packs offering thousands of annotated, GDPR-compliant images for various industries.
- End-to-End Platform: Seamless integration of 3D simulations, allowing users to import standard 3D files and transform them into "Smart" objects.
- Anomaly Detection: Generation of diverse synthetic data representing various fault conditions to train algorithms for identifying and diagnosing anomalies.