Datagrid offers a generative AI platform that creates realistic image, video, and audio data without human involvement. By synthesizing high‑quality synthetic data for use cases such as digital humans, anomaly generation, and domain‑specific training sets, it enables enterprises in manufacturing, retail, advertising, entertainment, and life sciences to train AI models and produce content at scale while avoiding costly data collection and privacy issues.
Funding
$4.7M 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
Many industries lack sufficient high-quality training data for AI models, especially for visual inspection, human detection, and content creation, leading to costly data collection, privacy concerns, and limited scalability of AI solutions.
Solution
Datagrid provides a suite of generative AI technologies that synthesize realistic image, video, and audio data without human intervention. Their platform includes modules for digital human generation, appearance and motion control, anomaly data creation, and domain‑specific synthetic data for manufacturing, retail, entertainment, and drug discovery. By leveraging GANs, diffusion models, and large language models, Datagrid can produce large volumes of high‑fidelity synthetic data from a few source examples, reducing the need for costly data acquisition and eliminating privacy issues. The generated data can be accessed via APIs or integrated into custom workflows, enabling rapid AI model training, content production, and virtual‑human applications across multiple sectors.
Target Audience
Primary customers are enterprises in manufacturing, retail/apparel, advertising, entertainment, and life‑science sectors that require large volumes of high‑quality synthetic data to train or enhance AI models and create digital content.
Features
- Digital human generation with controllable attributes (age, gender, ethnicity) for photorealistic avatars usable in advertising, metaverse, and virtual assistants
- Appearance control that modifies facial features, clothing, and hairstyles, supporting virtual try‑on and anonymization use cases
- Motion control that animates synthesized characters based on text prompts, enabling low‑cost video creation for education, PR, and media
- Anomaly generator that creates diverse defect images from minimal samples to augment inspection AI training datasets
- Synthetic training data pipelines for human detection, defect detection, and image enhancement (super‑resolution, denoising)
- API and modular AI components built on GAN, diffusion, and large‑scale language models for easy integration into customer systems
- Domain‑specific solutions such as a virtual fitting service (kitemiru) and a drug‑discovery platform that combines generative and predictive AI