VecML’s mission is to build the next-generation AI infrastructure to facilitate AI Agents and many different Large Language Model (LLM) applications, including personal assistants, smart RPA, AI-enabled phones, recommendation/advertising systems, AI-assisted medical diagnosis, humanoid robots, etc. We have released the initial trial version of our SaaS products for neural search engine, privacy-protection engine, statistical modeling, machine learning (ML) platform, and Retrieval Augmented Generation (RAG) platform.

The founders, core engineering team, and advisory committee of VecML consist of renowned scientists and highly experienced engineers in AI, machine learning, search, databases, knowledge graphs, privacy, and edge computing. Dr. Ping Li, the CEO, has been ranked highly by (score 44.6 listed by Rutgers University).

VecML Softwares

Take the recommendation/advertising system as an example, which is the major cash cow for many IT companies. One million (or one billion) products are represented as (feature) vectors through LLMs or special purpose embedding algorithms. These one million (or one billion) vectors are stored in the “neural search engine”. If privacy protection is needed (e.g., when they are stored in the public cloud), these vectors are first processed via our novel privacy-protection engine before they are stored in the neural search engine. When a customer query arrives, a query embedding is generated and compared with the one million (or one billion) vectors in the neural search engine. The best 1000 products (vectors) are selected as the candidates which are re-ranked by the ML platform (typically a neural network) to produce the top-3 or top-10 recommendations.

In summary, VecML offers a variety of products for AI infrastructures including: