ABOUT Envixion
OUR MISSION
Currently, Envision serves numerous top-tier hospitals, financial institutions, law firms, and universities, driving the core competitive edge of “low false alarm risk, high security protection, low cost deployment, and high-efficiency service.” It has become a major knowledge-intensive industry model, moving from “technology exploration” toward “practical application.”
OUR TEAM
Founded jointly by Harvard, MIT, Tsinghua top researchers, and renowned tech giants, focusing on innovations in large model AI native technologies, striving to shatter the barriers of large model application silos through cutting-edge tech.
Chinese website :https://www.envisionagents.com
Breaking the Bottleneck of Large Model Native Localization
Medical multi-agent workstation
The team leverages profound academic accumulation and AI frontier expertise to innovate multi-layer fusion architectures for computing and storage, breaking through the computing power and cost bottlenecks of large model AI native localization.
Explore the Future of Technology
The Four Major Pain Points of Knowledge-Intensive Industries
• Uncontrollable output quality
Untrustworthy "professional scene" with low efficiency of traditional
knowledge bases
•The dilemma of security and cost
Data and context gaps digging into the "double difficulty" dilemma
• High maintenance threshold for deployment
Difficulty in crossing the "localization tiger's path" for site-specific
implementation
• Lack of long-term memory
Intelligent systems can't sustain continuous learning and evolution
in work scenarios
Envision AI Medical Professional Multi-Intelligent Solution
Providing doctors with ready-to-use specialized AI intelligent body services, pre-installed with trillion-level large models and professional medical models, along with integrated professional medical literature and specialized knowledge resources, offering a full-suite of bedside diagnosis, medical research, and data management capabilities.
Core Technical Advantages
1.Model Hallucination Elimination
2.Trillion-Level Large-Scale Local Deployment
3.Medical Scene Pre-Installed Integration
4.Long-Term Memory Engine