Concord Horizon is an AI native contract platform built from a complete rewrite of Concord’s technology, applying ten years of experience to a modern architecture for faster and more accurate contract work.
The redesigned interface offers light and dark mode, collapsible navigation, full screen focus, custom columns, advanced filtering, and consistent tables across modules.
AI Copilot supports natural language questions, contract summaries, key point extraction, and fast portfolio insights, while AI Search adds lexical and semantic search with improved performance and multi actions on results.
MCP brings contract intelligence into AI tools like ChatGPT and Claude for summaries, tables, or automated monitoring. Concord applies a strict zero data retention policy with AI partners and never uses customer data to train AI models .
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PackageX OCR API turns any smartphone into an incredibly powerful universal label scanner. It can read every bit of text, including barcodes, QR codes and other information on the label.
Our OCR technology is the best in the industry. It uses proprietary algorithms and deep learning models to extract information from labels.
Our OCR API has been trained using information from more than 10 million labels. This allows for the highest scanning accuracy in the market, at over 95%.
Our technology can scan in low-light conditions and read labels from any angle.
Create your own OCR scanner app to eliminate pen-and-paper inefficiencies.
Our OCR scanner allows you to extract information from printed text or handwritten labels.
Our OCR software is trained using multilingual label data extracted in over 40 countries.
Detect and extract information from barcodes or QR codes.
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Light-in-Night
This application is designed for the planning of street lighting and illumination in public spaces, serving as a mobile solution for designers and lighting professionals. It assists purchasers of lighting equipment in selecting appropriate fixtures by allowing users to input the specifications of the area or roadway to be illuminated. Users can choose different fixtures and installation methods tailored to their needs. After completing the calculations, a detailed visual 3D representation of the scene will be generated, showcasing the distribution of light. Additionally, users have the option to save the lighting calculation results and scene parameters in a comprehensive report. Furthermore, the inclusion of sample projects crafted by experienced lighting technicians offers users the opportunity to not only explore the software's capabilities but also to create their own unique lighting designs inspired by these examples. This blend of functionality and inspiration makes the tool invaluable for both novice and seasoned lighting designers alike.
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Kray
Kray stands out as a cutting-edge global illumination renderer that facilitates swift and precise scene rendering, especially in environments where indirect lighting is crucial. It incorporates the latest algorithms and enhancements, enabling it to efficiently generate comprehensive global illumination effects, including reflections, refractions, and caustics, on standard computing systems. The renderer boasts rapid global illumination techniques such as light/photon mapping, which, while biased, provides impressive speed with minimal dependency on ray recursion counts; path tracing, which is unbiased and employs various sampling optimizations; and irradiance caching, designed for fast, view-independent storage of reusable GI solutions, along with caustics management. It features diverse light models, including point, directional, line, area, background lights, HDR image-based lighting, and the ability to pre-sample lights. Additionally, it supports instancing, permitting the efficient reuse of the same geometry across multiple locations in the rendered scene with minimal memory usage. Remarkably, instanced geometry can even be instantiated further, allowing for self-cloning capabilities with a user-defined number of recursions, making Kray a versatile tool for advanced rendering tasks.
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