Monday afternoon, a client needed a proposal fast
Last Monday at 10 p.m., I was revising a quote in a Hangzhou café. A colleague in Chengdu was using another AI, while client materials were scattered across chat logs and cloud drives. I couldn’t find the right version. I got stuck too: the problem wasn’t a lack of tools, but that everyone was using different ones—and I still had to clean everything up by hand.
What MonkeyAI is, and who is using it
MonkeyAI (Baizhi Office) is a team AI workspace that can run on your own server. It centralizes commonly used models, team knowledge bases, and reusable skills, while employees handle documents, spreadsheets, and presentations in one interface. The open-source project currently has about 5,000 GitHub stars. Independent consultant Lin Xiao once used it in a Shenzhen coworking space to organize client case studies. She said its biggest value wasn’t generation speed, but that new colleagues no longer had to ask, “Where do we keep the quote template?”
What it takes to replicate this today
Money: The free version works for initial trials, but teams with more than 10 people need a paid license; current pricing depends on the official website. Time: Allow 1–2 days for evaluation and a trial deployment, then reserve 2–4 hours each month for maintenance. Technical barrier: You’ll need some familiarity with server installation; if nobody on your team handles operations, a service provider can help. First step: Open MonkeyAI’s official Demo, register a team account, and try the document tools without rushing to migrate every file.
Before putting materials into a shared team space, check client privacy, backups, and permission settings. It isn’t essential for everyone: if you work solo with clients, sticking with the services you know may be simpler. There’s no urgency to try it now, either.
How I’d choose based on my stage
If I’m just starting: I’d test it with one real task, such as turning quote notes into a spreadsheet, before building a complex system.
If I have 1–2 clients: I’d create two isolated spaces for their materials and keep the existing backups.
If I’m scaling: I’d then evaluate unified accounts, usage analytics, and licensing costs—and decide who owns maintenance.
My advice is plain: solve one real mess today, then decide whether it deserves a place in everyday work.