The Best Open-Source Customer Support Chatbots in 2026 (An Honest Look)

Updated 28 July 2026 · GitHub data verified 28 July 2026.

You want a support chatbot you can actually own. Not a black box you rent by the seat, where the price jumps the month you get busy and your customer data lives on someone else's server. Fair enough. That's why people look at open-source.

But "open-source chatbot" covers a lot of very different tools. Some are full support desks with a bot bolted on. Some are raw developer frameworks that need an engineer for weeks. A few are true AI-first agents. Pick the wrong type and you'll waste a month before you notice.

So here's a plain, honest guide to the main options in 2026. What each one is good at. Who it fits. Where it falls short. We build one of these tools, so we'll be upfront about that when we get to it.

We're the smallest project on this list by a wide margin — 79 stars against Chatwoot's 34,824. We'll say that plainly. What we'd point to instead is maintenance: our last release shipped this week, while the Botpress open-source line hasn't shipped since June 2023 and Rasa's core hasn't since January 2025. Category fit and recent releases are the honest case for a small project, not star count.

First, what "open-source chatbot" really means

Two things get mixed up here, and it matters.

A support desk manages conversations. It takes messages from chat, email, and social, puts them in one place, and lets your team reply. Some of these add a bot on top.

A chatbot framework is the engine that reads what a customer types and writes an answer. Some are simple flowcharts ("if they click this, show that"). Some use AI to understand plain language.

Most teams want both: a place to handle chats and a bot smart enough to answer the easy questions on its own. Keep that in mind as you read. A tool can be great at one job and weak at the other.

One more thing worth saying out loud. "Open-source" means free to download, not free to run. You still pay for a server, updates, and someone to keep it alive. We'll come back to that, because it's the part most guides skip.

Chatwoot — the popular all-rounder

Chatwoot (34.8k GitHub stars) is the name most people hit first, and for good reason. It's an open-source support desk that pulls live chat, email, and social messages into one inbox. Its community edition is MIT-licensed (the repo also carries an enterprise directory, so GitHub reports the licence as unspecified), so you're free to self-host it or use their cloud. It has a chat widget, a help center, and an AI helper called Captain.

Who it fits: teams whose support is mostly people messaging them, who want one tidy inbox and full control of their data. It's the closest open-source match to Intercom or Zendesk.

Where it falls short: Chatwoot started as an inbox for humans, not as an AI agent. The bot side is newer and lighter. If your main goal is a bot that answers most questions on its own, you may find yourself wiring a lot of that together. We wrote a full, fair comparison in ChatterMate vs Chatwoot if you want the details.

Rasa — for teams with engineers

Rasa (21.3k GitHub stars) is a Python framework for building chatbots from scratch. The core is free under the Apache-2.0 license. It gives you deep control over how the bot understands language and manages a conversation.

Who it fits: companies with a real dev team who want to control every part of the bot and are fine training their own models. Banks and big enterprises like it for that reason.

Where it falls short: it's a framework, not a ready product. There's no inbox, no widget you drop on your site in an afternoon. You build most of it. For a small team without engineers to spare, Rasa is a heavy lift. Worth noting on the maintenance front: the open-source core's last tagged release was January 2025.

Botpress — visual bot building

Botpress (14.8k GitHub stars) sits in the middle. It gives you a drag-and-drop editor to design chat flows, plus room for code when you need it. It handles multiple languages and connects to modern AI models.

Who it fits: people who want to see and shape the bot's logic without writing everything by hand, but still want power under the hood.

Where it falls short: it's a bot builder first. You still need to connect it to your channels and your support process. And the more you lean on the AI parts, the more setup and tuning you take on. One caveat to check: the open-source v12 line hasn't had a tagged release since June 2023 — active development moved to their newer hosted platform.

Typebot — great for forms, not full support

Typebot (10.2k GitHub stars) is built for chat-style forms: lead capture, quick surveys, guided sign-ups. It's clean, it looks good, and it's quick to set up.

Who it fits: marketing and sales teams who want a friendly form that feels like a chat.

Where it falls short: it's not a support tool. It won't run your help desk or answer deep product questions from your docs. Right tool, different job. One licence note worth knowing: Typebot uses the FSL, which is not an OSI-approved open-source licence and restricts competing commercial use for a period before each release converts to open source.

Tiledesk — live chat plus bots

Tiledesk (314 GitHub stars — the smallest community here apart from ours) is an open-source live chat with built-in bots, shared under the MIT license. It supports human handoff, so a bot can pass a tricky chat to a real person. It bills itself as an open alternative to tools like Voiceflow.

Who it fits: teams who want live chat and a bot in one open package and don't mind running the stack themselves.

Where it falls short: like the others, you own the hosting and upkeep. And the AI quality depends heavily on how you set it up. The community is small, so expect to lean on the docs more than a big project's forum.

The big LLM projects — powerful, but not support agents

You'll also see four much larger projects recommended whenever "open-source AI chatbot" comes up: Open WebUI, AnythingLLM, Flowise, and LibreChat. They dwarf everything else on this list by GitHub stars, so they're worth understanding. But there's a catch that matters for support specifically: none of them is a customer-support agent. They're general-purpose or document-chat tools. No ticketing, no human handoff, nothing a customer on your website can reach out of the box. They're chat for your team, not agents for your customers.

Open WebUI — the self-hosted LLM chat front-end

Open WebUI (147k GitHub stars) is the most-starred project on this list by a distance. It's a polished, self-hosted interface for running large language models — think a private ChatGPT you point at Ollama or any OpenAI-compatible API. It ships under a custom licence, so check compatibility before you build a product on it rather than assuming MIT.

Who it fits: teams and individuals who want a private chat UI over their own models, fully self-hosted so no data leaves your servers. It's excellent at that.

Where it falls short: it isn't a support tool. There's no shared inbox, no ticket, no way for a customer on your website to reach a human. If the self-hosting-for-privacy angle is what draws you, we walk through the real tradeoffs in self-hosted customer support software.

AnythingLLM — document chat you can run anywhere

AnythingLLM (64k GitHub stars) is an all-in-one app for chatting with your documents. Upload PDFs and files and it builds a retrieval layer so the model answers from them. It's MIT-licensed and runs as a desktop app or self-hosted.

Who it fits: people who want private retrieval over their own document set without wiring the pipeline themselves.

Where it falls short: same gap as the others — it's built for you to query your documents, not for your customers to get support. The retrieval idea is exactly right for grounded answers, though; it's the same reason support bots need RAG for customer support.

Flowise — a visual builder for LLM apps

Flowise (55k GitHub stars) is a drag-and-drop canvas for building LLM apps and agents. You wire nodes together — models, retrievers, tools — into a flow. It ships under a custom licence, so read the terms before commercial use.

Who it fits: developers and technical teams who want to prototype a custom AI workflow visually rather than in code.

Where it falls short: it's a builder, not a finished support product. You get powerful primitives and an empty canvas; the inbox, the handoff, the widget, the whole customer-facing side is on you to assemble and maintain.

LibreChat — one interface, many models

LibreChat (41.4k GitHub stars) is an open, self-hostable chat interface that talks to many model providers from one UI, with plugins and conversation search. It's MIT-licensed. Worth noting it ships without tagged releases, so you're tracking the main branch rather than versioned builds.

Who it fits: teams that want a single private front-end across OpenAI, Anthropic, local models, and more.

Where it falls short: like Open WebUI, it's a chat client for your team, not a support agent for your customers. No ticketing, no handoff to a human.

ChatterMate — the AI-first, doc-grounded option

Now the part where we're the ones being built. We'll keep it honest.

We built ChatterMate (79 GitHub stars, Apache-2.0) because we wanted a support agent that was AI-first from day one, not a human inbox with a bot stapled on later. It answers from your documents and cites where each answer came from. That last part matters more than it sounds. A bot that makes things up gives a great-looking answer and a furious customer. Grounding the answer in your knowledge base, with a citation, is how you avoid that. We dug into why in AI chatbot vs AI agent.

It's open-source and you can self-host the whole thing, so your data stays yours. It's free to start (your first 300 chats are on us), and there's a CLI and an MCP server for the technical folks. When the bot can't help, it hands off to a person cleanly. If you're weighing us against the big closed platforms, we put that side by side in ChatterMate vs Intercom.

Where we're still growing: we're younger than Chatwoot, so our community is smaller and we're adding integrations all the time. If you need a huge library of third-party plug-ins today, check that your must-haves are covered first. We'd rather you know that up front.

Frequently asked questions

What is the best open-source customer support chatbot in 2026?

There isn't one winner for everyone. Chatwoot is the strongest open-source shared inbox if your support is mostly humans replying. Rasa suits teams with engineers who want to build a custom bot from scratch. For AI-first, doc-grounded answers with human handoff and self-hosting, that's the gap we built ChatterMate to fill. Match the tool to whether you need an inbox, a framework, or a ready agent.

Is open-source chatbot software really free?

Free to download, not free to run. You avoid per-seat licence fees, but you still pay for a server, updates, monitoring, and someone's time to keep it healthy. Self-hosting is often worth it for data control and cost at scale, but price it out honestly first — a hosted free tier is sometimes cheaper than the hours self-hosting takes.

Can I run an AI support chatbot without sending data to OpenAI?

Yes. Several tools here, ChatterMate included, let you bring your own model — including local models via Ollama — so conversations never leave infrastructure you control. This is the main reason teams choose self-hosted, open-source support software over closed SaaS.

What's the difference between a support desk and a chatbot framework?

A support desk like Chatwoot manages conversations — it collects messages from chat, email, and social into one inbox for your team to answer. A chatbot framework like Rasa is the engine that reads a message and writes a reply. Most teams want both: a place to handle chats and a bot that answers the easy ones. Some tools do one job well and the other poorly.

Which open-source chatbots have built-in human handoff?

Chatwoot, Tiledesk, and ChatterMate can pass a conversation from the bot to a human agent with full context. General-purpose LLM interfaces like Open WebUI, AnythingLLM, and LibreChat do not — they have no agent-facing inbox to hand off to. If clean escalation matters, that distinction is worth checking first; we walk through it in human handover.

What licence is ChatterMate released under?

ChatterMate is released under the Apache-2.0 licence. That's a permissive, OSI-approved open-source licence that lets you self-host, modify, and use it commercially. You can read the full source on GitHub.

So which one should you pick?

Short version, no hedging.

If you want a conversation inbox for a human team and a light bot, Chatwoot is the safe pick. If you have engineers and want to build a custom bot brain, Rasa or Botpress give you the most control. If you want a private chat UI over your own models for your team, Open WebUI or LibreChat are the big names. If you just need a chat-style form, Typebot is lovely. If you want AI-first answers grounded in your own docs, aimed at your customers, with self-hosting and a free start, that's the gap we built ChatterMate to fill.

And remember the hidden cost. Free to download is not free to run. Before you commit to any of these, price out the server, the updates, and the hours someone on your team will spend keeping it healthy. Sometimes self-hosting is clearly worth it. Sometimes a hosted free tier saves you a headache. Be honest with yourself about which one you are.

If cutting ticket volume is the real goal, it helps to measure it properly too — we covered that in how to measure chatbot deflection rate.

Written by the ChatterMate team — we build an open-source, AI-first support agent that answers from your docs with citations. Yes, we're on this list. We tried to be fair to everyone else on it.

Want to try the AI-first option? ChatterMate is open source and free to start — your first 300 chats are free, and you can self-host it whenever you're ready.