The startup develops a real-time data generation platform that utilizes generative algorithms to create custom datasets with pixel annotations and structured spatial data. This technology enables data scientists to rapidly iterate models while ensuring improved accuracy and effective bias controls in their datasets.
Funding
$3.8M 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
Training computer vision models requires large, accurately labeled datasets, which are often expensive and time-consuming to acquire, especially for specialized applications or rare scenarios. Existing datasets may also contain biases that negatively impact model performance and generalization.
Solution
Lexset provides a platform for generating synthetic data to train computer vision models, offering a cost-effective and scalable alternative to traditional data collection methods. The platform allows users to create custom datasets with pixel-perfect annotations and structured spatial data, enabling rapid iteration and improved model accuracy. By controlling scene parameters and event probabilities, users can generate diverse datasets that address specific training needs and mitigate potential biases. The generated data covers various sensor modalities, including EO, IR, SAR, and thermal.
Target Audience
Lexset targets data scientists, machine learning engineers, and computer vision researchers who need custom, high-quality training data for AI model development in industries such as security, defense, manufacturing, and tech.
Features
- Unlimited synthetic data generation with customizable scene parameters and event probabilities
- Robust APIs and integrations for seamless data access and model training workflows
- Simple, no-code interface for intuitive dataset creation and management
- Support for importing custom 3D content and advanced camera controls
- Library of tens of thousands of annotated 3D assets for diverse scene creation
- Advanced lighting controls for photorealistic rendering
- Ability to store and iterate on scene configurations for reproducible experiments
- Tools for compositing objects into existing images with precise lighting matching
- Features for creating blemishes, dents, and other imperfections to enhance data realism