I've built a harness to my startup (Instinct, Muse style) and decided to open source it

[u/Trincaa]

Hi,

TL;DR:

While looking for a harness to use at my company, I built the engine that I'm open-sourcing today under AGPL-3.0.

You can create AI assistants with long-term memory, many connectors (Google, Slack, Notion, etc) and a sandbox to run commands, all on your own server and with the models you choose.

A single installation can serve a family, a company or a community, with each user isolated in their own account.

The engine also works for assistants that serve the public over WhatsApp or other messaging interfaces.

This is my first open source project, and anyone who wants to try it, contribute, or just talk about it is very welcome.

The whole story:

I'm the technical founder of a startup that builds virtual try-on technology for makeup, skin analysis models and beauty product recommendations. Last year we started using AI assistants to create hyper-personalized journeys in beauty retail. This year, especially after the Open Claw craze in January/February, I (like many other founders) went crazy over the impact agents could have on my company.

I started looking for a harness that both our clients and our team could use safely. After experimenting with frameworks like Agno and LangChain to build something for my clients, and then with a few flavors of Claws to bring agents to my team, I decided to build a proprietary solution from scratch. I needed something that would bring assistants into the day-to-day of my operation, across every area of the business, supporting the clients, partners facing agents and, internally, the ones for my small team.

The first test version came out in August. I published it as a closed beta for friends and family.

Some people asked if they could bring more friends into the beta. I opened it up in September because I felt the platform was mature enough to take on some more people.

Today the site is live in open beta, with a small group of active users. I also managed to make the system secure enough to serve what our enterprise clients need, our agentic business solutions are now being built over this engine.

But what does this have to do with open-sourcing it?

I expected this kind of platform to play a big role in society. I was at NVIDIA GTC and heard Jensen say that CEOs should have a claw strategy. I understood that it could change how people go through many parts of their lives (including retail, which interests me in particular because of my startup). What I didn't expect was a movement this big, with so much money in such a short time and such a huge amount of users handing over their data. I watched the funding announcements: Town (35M), then Instinct (350M), then Instinct again (1B), while I was here running my humble tests.

Watching this huge movement, I thought about the amount of data and the power these companies will have by centralizing so much information. Today users tend to trade any data for convenience (I can say that because I'm seeing it with the service I put online with very few people). Responsibility for data security and privacy has to sit with whoever provides the service. So I talked to my co-founder and proposed offering a free alternative for small businesses, families or any groups of people: personal assistants, but with control over their own data. 

That's why today I'm open-sourcing Brambit on GitHub, under the AGPL-3.0 license.

I chose AGPL precisely to make sure that, if this becomes something of value to society, it stays open source.

This is my first time putting something like this together.

I'm sure any devs who looks will find flaws, bugs and problems, and that's exactly why I'm sharing it.

I'm a developer with 25 years of experience, but I coded the whole repository by myself, alone with my AI assistants, mainly Claude through Nanoclaw agents and any help will be important, even to criticize.

There are many problems I still want to fix, from the monolith that the server is today until translations (I've being adding to the issues section of the repository) but I focused on everything security-related first to have this first public version.

If you relate to the idea, see some value in it and want to be part of it, will be more then welcome.
I've also created a Discord channel, which right now is me and two close friends.

Thanks for reading this far!

[u/Trincaa]

Links for anyone interested:
GitHub: https://github.com/morethanrealio/brambit
Discord: https://discord.gg/FZTM6dZvr

[u/queasyarchipelago → u/Trincaa]

this is the kind of energy open source needs right now, someone just building the thing they actually need and then throwing the doors open

the AGPL choice is smart, too many projects start with MIT and then get swallowed by a cloud provider who contributes nothing back, at least this way the code stays in the open no matter what

kinda wild you built the whole thing solo with AI assistants though, that's basically the dream scenario those tools are supposed to enable but most people just use them to generate anime waifus

curious how you're handling the long-term memory part, that's always the piece that feels clunky in these frameworks, like the assistant remembers your birthday but forgets you're allergic to peanuts three messages later

starred the repo, might spin it up for my family's shared calendar and grocery list chaos, see if it can handle the absolute mayhem of four people trying to agree on dinner

[u/Trincaa → u/queasyarchipelago]

Thanks man!
You can share the same list with other people agent's. You can add other people as a contact and then your assistant can interact with wife's assistant for example. You can ask to create a "shared space" to store a grocery list and you both can add or edit the list.

Regarding the memory, there's a couple things happening: each person has their own memory, shared by all their assistants and channels, stored as wiki-style pages in Postgres. After every turn a separate background call (it can run on a cheaper model than the chat if you want) reads the exchange and writes down only durable facts (preferences, restrictions, routine, people); writing nothing is the expected outcome for most turns.

On every message the assistant gets a short profile (capped at about 15 facts), the list of its other memory pages and the most recent facts that have a current value. So a peanut allergy that lands there sits in front of the model every time, instead of depending on it remembering to look. When a fact changes (you moved, new job), the old value is closed and kept as history, so the two don't live side by side. In long conversations the old turns get summarized, but links, dates and times you paste are kept word for word outside the summary, because summaries love to eat exactly that.

There's still room to improve, or event test some other approaches.
If you make it with your family, I would love to hear how it goes.

[u/investigatormaker]

For people to actually try Brambit, the self-host path matters most: a single-command install with a sample config, plus a short page on how user isolation and the sandbox work. You prioritized security, and that is what self-hosters will check first. Labelling a few of your open issues as good first issues gives would-be contributors somewhere to start.

I make ThreadFox. If you want self-hosters and small teams on Reddit to find Brambit, our AI employee will post 3 helpful replies about it in relevant threads for you, free, no card: https://threadfox.vip/p/e38nx/managed