Building Team. One 26MB Primitive. Air-Gapped. Deterministic. Runs Anywhere (www.getarbiter.dev)

ARBITER has introduced a revolutionary 26MB AI model that streamlines the typical vector database stack by combining the functionality of embedding, indexing, and ranking into a single primitive. This model achieves a remarkable 10.7× compression while delivering 11% greater similarity preservation compared to traditional PCA methods. By enabling real-time disambiguation of queries, ARBITER minimizes noise and enhances the accuracy of results significantly, suggesting users can replace their existing stacks of multiple vendors, such as OpenAI and Cohere, with this one solution. The significance of ARBITER lies in its potential to drastically reduce costs and improve efficiency for businesses, particularly enterprises spending $500K–$2M annually on vector stacks. By consolidating various components into a single model, organizations can save up to 90% in storage costs and eliminate vendor fees, all while obtaining superior results. The model supports air-gapped deployments to ensure data security, making it suitable for sensitive sectors like defense, life sciences, and finance. With its capabilities, ARBITER is poised to redefine how organizations manage and extract insights from their data.