Most live chat tools on the market ask you to make the same trade-off: convenience in exchange for control. You get a SaaS dashboard, a chat widget, maybe an AI bot — but your customer conversations, your support data, and your team’s workflow all live on someone else’s cloud.

We built GoLiveChat because we believe there is a better way.

Why We Built GoLiveChat — A Self-Hosted Live Chat Platform That Puts You in Control - GoLiveChat Live Chat System - Self-Hosted Customer Service Solution

The Problem with SaaS-Only Live Chat

The SaaS model works — until it doesn’t. Here is what we kept hearing from teams:

• “Our compliance team won’t let customer chat data leave our infrastructure.” For finance, healthcare, legal, and government — this is a dealbreaker.
• “Per-seat pricing kills us as we scale.” Adding ten more agents shouldn’t cost ten times more.
• “We hit rate limits during peak hours.” Shared infrastructure means shared bottlenecks.
• “The vendor changed their API and our integrations broke.” You are building operations on a foundation you do not own.

GoLiveChat is our answer to all of this.

What GoLiveChat Actually Does

At its core, GoLiveChat is a live chat and AI customer support platform that runs entirely on your own server. You deploy it. You own the database. You control every line of configuration.

Real-Time Website Chat — One Line of JavaScript

Add live chat to any website — desktop or mobile — with a single <script> tag. The widget is fully themeable: colors, position, trigger behavior, proactive greetings. When a visitor clicks the chat button, the conversation appears in your agent dashboard in real time, powered by WebSocket connections that stay fast even under high concurrency.

No iframes. No third-party dependencies. No external calls leaving your domain.

AI That Works Alongside Your Team — Not Instead of It

GoLiveChat ships with deep AI integration, but we designed it as a copilot, not a replacement. Here is how the hybrid model works:

• Bot-first triage: connect ChatGPT (GPT-3.5 / GPT-4 / GPT-4o), Coze, or Dify as your first line of response. The AI handles common questions instantly — order status, shipping policy, pricing FAQ.
• Context-aware handoff: when the AI cannot resolve a query, it transfers the full conversation history to a human agent. The customer never repeats themselves.
• Streaming responses: AI replies appear word-by-word via SSE, making the interaction feel natural — like a real person typing.

We also integrated Qdrant, an open-source vector database. Upload your documentation, knowledge base articles, product manuals — PDF, Word, Excel, plain text. The system chunks and embeds them. When a customer asks a question, GoLiveChat retrieves the most relevant passages first, then feeds them to the LLM for a precise, grounded answer. This is retrieval-augmented generation (RAG) running on your own infrastructure.

A Unified Agent Workspace

Every conversation — from your website, from API integrations, from email — lands in a single dashboard. Key features for your support team:

• Multi-agent allocation: assign, transfer, and collaborate on conversations without losing context
• Canned responses: shared reply library for your team, organized by category
• Visitor tracking: real-time IP geolocation, browser fingerprint, page history, language detection
• File sharing: image, document, and attachment support within chat — configurable size limits
• Message translation: built-in translation for cross-border support teams
• Dark mode & responsive: the dashboard works on desktop and tablet

Ticketing and Analytics

Not every conversation ends in chat. GoLiveChat includes:

• A full ticketing system with priority levels, SLA tracking, and status workflows (pending → processing → resolved → closed)
• Conversation history searchable by visitor, agent, or time range
• Analytics dashboard: agent workload, satisfaction scores, response times, visitor trends

Open API and Extensibility

The platform exposes REST APIs for custom integrations. Connect your own CRM, push visitor data to your analytics pipeline, build custom chat clients, or integrate with your existing SSO/OAuth authentication. You are not locked into our front-end — although it is open-source and fully customizable.

Built on Golang — Here Is Why It Matters

We chose Go for the backend, and it was not an arbitrary decision.

• Single binary, zero dependencies: compile to a statically-linked executable. Deploy by copying one file.
• Goroutines: thousands of lightweight concurrent threads. A single GoLiveChat instance handles hundreds of simultaneous chats without breaking a sweat.
• Channel-based communication: Go’s CSP model eliminates entire classes of concurrency bugs that plague thread-and-lock architectures.
• Low resource footprint: GoLiveChat runs comfortably on a $5/month VPS. Compare that to the memory hunger of Node.js or JVM-based alternatives.

Since 2019, the project has logged over 3,356 optimizations — from connection pooling to message serialization to query performance. Production-tested, not a weekend prototype.

That is it. The Docker Compose file spins up GoLiveChat + MySQL 8.0 in a single command. The binary approach needs only a MySQL instance running somewhere. Both take under five minutes from zero to live.

Supported platforms: Linux, macOS, Windows.

Who Is GoLiveChat For?

We built this for teams that:

• Need data sovereignty — customer conversations must stay on owned infrastructure
• Want predictable costs — no per-seat pricing, no usage-based surprises
• Value performance — high-concurrency, sub-second message delivery, no rate limits
• Run multi-site or multi-tenant operations — one deployment can serve multiple domains and teams
• Use AI thoughtfully — want LLM-powered automation but under their own API keys and configuration

Typical deployment scenarios include SaaS companies embedding chat in their products, e-commerce brands running high-volume pre-sales and support, fintech/healthtech organizations with strict compliance requirements, and agencies managing chat for multiple clients from a single server.

What Is Next

GoLiveChat is under active development with a clear roadmap:

• Predictive engagement: trigger proactive chats based on visitor behavior signals
• Voice-to-text: let customers speak naturally and receive text or AI-generated voice replies
• Deeper analytics: conversation sentiment, topic clustering, agent performance benchmarks
• Plugin marketplace: community-contributed integrations for popular CRMs and help desks

Try It Today

We believe you should be able to run your own customer support platform without handing over your data, your workflow, or your budget to a SaaS vendor.

GoLiveChat is the alternative — private, performant, AI-capable, and fully yours.

Deploy in Minutes

We put a lot of effort into making deployment simple:

# Option 1: Docker Compose (recommended)
git clone https://github.com/taoshihan1991/golivechat.git
cd golivechat
docker-compose up

Option 2: Single binary

./golivechat server