Prexable is an explainable, privacy-preserving video processing platform that enables businesses and individuals without AI expertise to train, understand, and debug their own computer vision models. The platform offers a drag-and-drop interface for detection, tracking, and recognition tasks, with cloud-based public and semi-private modes for scalability and cost-effectiveness. Prexable is currently in use for object detection, tracking, authentication, and recognition, with video annotation tools ready and explainable AI features under development.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional video processing systems operate as black boxes, making it difficult for non-experts to understand how AI models make decisions or debug their performance. Additionally, confidential videos often require upload to external servers, creating privacy risks and limiting adoption in sensitive industries such as healthcare, manufacturing, and security.
Solution
Prexable provides an online drag-and-drop video processing solution that allows businesses and individuals without AI expertise to train, comprehend, and debug their own personalized models in a privacy-preserving way. The platform supports detection, tracking, and recognition tasks through a single unified interface, eliminating the need for multiple specialized tools. Prexable offers three operational modes—private, semi-private, and public—enabling users to process videos locally for maximum confidentiality or leverage cloud resources for scalability and cost efficiency. The platform incorporates explainable AI modules that clarify how decisions are made, along with review tools for validating outcomes, boosting trust and transparency. Prexable is currently in use for object detection, tracking, authentication, and recognition, with video annotation tools ready and explainable AI features under active development.
Target Audience
Primary customers are businesses and individuals without specialized AI expertise who need to process video for detection, tracking, or recognition tasks, including organizations in security, manufacturing, healthcare, and agriculture seeking privacy-preserving and explainable computer vision solutions.
Features
- Drag-and-drop interface enabling non-experts to train, deploy, and debug custom video processing models without coding skills
- Explainable AI (XAI) modules that provide transparency into model decision-making processes, helping users understand and trust outcomes
- Privacy-preserving architecture with on-device processing options, eliminating the need to upload confidential videos to external servers
- Unified platform supporting detection, tracking, and recognition tasks within a single interface, reducing tool fragmentation
- Cloud-based public and semi-private modes for scalable, cost-effective processing of large video datasets
- Video annotation tools supporting human-in-the-loop workflows for labeling, tagging, and managing visual data for training or auditing
- Visual prompting capabilities that allow users to interact with models using points, bounding boxes, or natural language descriptions for flexible task adaptation
- Temporal video AI features that analyze sequences to understand actions, events, and interactions beyond simple object tracking