Seesa builds local enterprise AI with Jev-like label classifiers
Seesa aims to save each employee 20% of their time per week, built on custom Jev-like label classifiers, 150 agent routines, and self-healing context graphs, all running locally.
So proud of the team for the work done over the last year to get this done. The goal of Seesa is to save every employee 20% of their time each week. In many cases, we are seeing way more than that. A huge announce of technical achievements under the hood to make this work including our work and collaboration with @ashxhart on the incredible Tensorfold engine, custom built jev-like label classifiers systems, connections to over 100 integrations, 150 agent routines, auto healing context graphs with our gardener, fusion, and healing agents that keep everything accurate and up to date. Truly multiplayer, enterprise and local AI that runs entirely in your own building. No more token counting or handing over your valuable data to someone else’s cloud. And we are just getting started. Built in 🇬🇧
This post quotes another post: “Seesa.ai launches packaged on-premises AI suite for enterprises”