Visual Layer provides an AI-powered platform for managing unstructured visual data, enabling teams to organize, explore, and enrich images and videos at scale. The platform uses a graph engine to automate data curation, improve dataset quality, and extract insights via semantic and visual search. This results in streamlined machine learning pipelines, reduced manual effort, and enhanced model performance for data and AI operations.
Funding
$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.
MFounders
Product
Problem
Managing and extracting insights from large datasets of visual data, such as images and videos, is challenging due to the unstructured nature of the data and the time-consuming manual processes required for curation and labeling. Traditional methods often result in duplicated images, incorrect labels, and inefficient data analysis workflows.
Solution
Visual Layer provides an AI-powered visual data management platform that indexes and analyzes large datasets of images and videos using a CPU-only graph engine. The platform automates data curation, enabling users to quickly view, organize, and manage data trapped in various storage locations. By leveraging clustering, similarity search, and slicing, Visual Layer identifies and resolves data quality issues, extracts insights using natural language and visual search, and enriches data with metadata using proprietary or third-party AI models. This allows users to create high-quality visual datasets for AI training, improve model accuracy, and streamline data analysis workflows.
Target Audience
Visual Layer targets data scientists, analysts, and tech leaders across industries such as technology, software, defense, security, manufacturing, logistics, retail, eCommerce, media, and entertainment, who need to manage and extract insights from large visual datasets.
Features
- CPU-only graph engine to uncover hidden connections within visual data
- Multimodal vector space to embed data, constructing a comprehensive graph (VL Index)
- Connects to various data sources: cloud storage, local file systems, and databases
- Automated tools to speed up manual data curation
- Natural language queries, similarity search, advanced filters, and interactive visualizations for data exploration
- Ability to enrich unstructured visual data with metadata using proprietary models or any foundation model
- API and web-based UI to scale from gigabytes to petabytes
- Tools for team collaboration, allowing users to share high-quality datasets