Key points at a glance
- Look at four things when choosing an open-source alternative: the license, whether it's truly self-hostable, whether memory is long-term and controllable, and whether models can be swapped.
- Enclave is MIT open-source, self-hostable with one docker compose command, and your data stays only on your machine.
- Enclave is more than character chat: multiple experts, proactive follow-ups, and the ability to produce real documents.
Why people look for an open-source Character.AI alternative
Character.AI offers a polished experience, but it's closed-source and cloud-only: your conversations live on the platform's servers, you can't self-host, and you can't personally verify how the data is used. People who want data sovereignty, who want to avoid platform lock-in, or who want to modify the product to fit their needs naturally seek an open-source, self-hostable alternative — code laid out on GitHub, a promise that can be audited line by line.
What a good open-source alternative should have
Four key dimensions: first, the license must be permissive enough (such as MIT, free to modify and use commercially); second, it must be truly self-hostable, not merely "source-available"; third, memory must be long-term and controllable — viewable / editable / deletable, not forgotten the moment a session ends; fourth, models must be swappable, able to connect to both cloud APIs and local models. Use these four as a checklist and it's easy to weed out "pseudo-open-source" or feature-incomplete projects.
Where Enclave stands on these dimensions
Enclave's entire monorepo is open-source under the MIT license, self-hostable with one docker compose command — API, frontend, database, and vector index all run locally; it uses structured long-term memory rather than a simple context, with memory manageable item by item; and its model layer can mix OpenAI, Anthropic, Google, DeepSeek with local Ollama / vLLM. The difference is that Enclave goes beyond "chatting with characters" — it's an assistant world of multiple experts that follows up proactively and can produce PPT / Word / Excel, making it better suited to those who want both open-source control and an AI that actually gets things done for them.
Key facts
- License
- MIT (free to modify and use commercially)
- Self-hosting
- One docker compose command
- Supported models
- OpenAI / Anthropic / Google / DeepSeek / Ollama / vLLM
- Language
- 中文 / English / 日本語 / 한국어
FAQ
Is Enclave open source? What license does it use?
Yes. The entire Enclave monorepo is open source on GitHub under the MIT license — free to audit, modify, and use commercially. Any promise that we won't misuse your data is something you can verify by reading the code yourself, instead of just having to take it on faith.Can I self-host Enclave? Is it hard?
Yes, and it's about as hard as running an ordinary web service. If you've used docker compose, three steps get you your own instance: clone the repo, copy .env, and docker compose up. The API, frontend, database, and vector index all run on your own machine.Can I use Enclave commercially? What does the MIT license restrict?
Yes, commercial use is allowed. Enclave is open source under the MIT license, which permits free use, modification, and distribution — including commercial use — with the only requirement being to retain the copyright and license notice. You can build on it, deploy it internally, or offer it as a service, with no extra licensing fees.Which large language models does Enclave support?
Enclave's model layer is fully swappable: OpenAI, Anthropic, Google, DeepSeek, and local Ollama / vLLM can all be configured. Different characters can even use different models, freely allocated by scenario and cost.
Ready to try it?
Open it in your browser — no credit card, no install.