A common scenario: a business needs an AI chatbot for lead qualification, but ready-made solutions are overloaded with features or expensive. Typebot is an open-source chatbot builder with a visual builder that lets you assemble an intelligent form with LLM integration in a couple of days and embed it on your site. This no-code chatbot platform supports self-hosted deployment via Docker Compose, giving you full control. The embedded chatbot can be styled to match your design. These bots handle over 1,000 dialogues per month, and average lead processing time drops from 5 minutes to 30 seconds — a 90% reduction.
Problems We Solve
Complexity of LLM integration. Connecting GPT-4 or Claude via Typebot's OpenAI block is a few clicks. But to get relevant answers, you need to properly configure the system prompt and limit context. Without that, the chatbot hallucinates or goes off-topic.
Need for custom frontend. Ready-made chatbots often require iframe embedding, which breaks UX. Typebot offers flexible embed options: popup, bubble, full-page. We style the appearance to match your design—custom CSS overrides inside a <style> tag.
Lack of analytics. Typebot provides data on completion rate (typically 95%+), drop-off points, and collected fields. If these metrics aren't enough, we integrate export to Google Analytics via custom events.
How We Do It
Let's break down a case: a fintech client wanted to collect loan applications with pre-qualification. We deployed Typebot in Docker Compose on their infrastructure (PostgreSQL + MinIO). In the flow, we added an OpenAI block with a prompt that analyzes responses in English and Russian and estimates a credit score. Results are written to Airtable via webhook. Deployment took 4 days: 2 for flow design, 1 for integration, 1 for testing and operator training. The bot handles over 2,000 dialogues per month with a 97% completion rate.
According to the official Typebot documentation, the platform supports up to 1,000 users on a single instance, which is sufficient for most mid-size projects.
Our Process
- Analysis — review communication scenarios, collect typical questions and answers.
- Flow design — draw branching logic, define LLM integration points.
- Implementation — assemble blocks, configure variables and API requests.
- Testing — run scenarios, fix found errors, optimize prompts.
- Deployment — set up a self-hosted instance, configure embed on the site.
- Training — provide documentation and conduct a workshop for your team.
What's Included
Scope of work (turnkey solution)
| Component | Description |
|---|---|
| Deployment | Docker Compose + PostgreSQL + MinIO + HTTPS setup |
| Flow design | Visual scenarios with LLM blocks, up to 10 scenarios |
| Integrations | Webhooks, API, CRM (AmoCRM, Bitrix24) |
| Embed | JavaScript code for popup/bubble/inline |
| Documentation | Architecture, operation manual, prompt changes |
| Support | Warranty support for 2 weeks after release |
Comparison of Typebot with Alternatives
| Criterion | Typebot | Botpress | Tidio |
|---|---|---|---|
| Type | No-code flow builder | Platform for AI agents | Ready-made service |
| LLM block | Yes (OpenAI) | Yes (any model) | Built-in AI answers |
| Self-hosted | Yes (open-source) | Yes (Community) | No |
| Tool use | No | Yes | No |
| Complexity threshold | Low | Medium | Low |
Typebot is deployed 2x faster than Tidio and gives full control over data. This is especially important if you process personal data and cannot transfer it to cloud providers. Self-hosting saves approximately $200/month in subscription fees for a typical mid-size deployment.
Timeline and Cost
We offer turnkey deployment within 3–5 days. If customization or multiple integrations are needed, up to 2 weeks. Typical project cost is $3,000–$5,000. Contact us for a free project assessment — we'll send a quote within a day.
The average project payback is 3 months due to savings on manual lead qualification. For example, you can reduce application processing costs by 35% and cut manual effort by 40%.
Why Go Self-Hosted?
Self-hosted Typebot gives you full data control: store everything on your servers, pay no extra licenses, extend functionality via API. Our team has 5+ years of experience in AI/ML and over 50 chatbot implementations. We guarantee stable operation and fast support.
How Typebot Integrates with LLMs
In the OpenAI block, you specify the model (gpt-4o, gpt-4, gpt-3.5-turbo), system prompt, and variables for substitution. The response comes as text, which can be stored in a variable or displayed to the user. This approach is ideal for open-ended questions, answer generation, and sentiment analysis in conversational AI applications. The average response time is under 1 second.