Botpress

Chatbot and agent platform with visual flows and built-in channels

AI Agents & AutomationFree planOverseas★★★★☆ 4.0

Visit Botpress official site ↗ View similar tools Compare alternatives →

What is Botpress?

Botpress is a platform for building conversational agents that combines a visual flow editor with an LLM-driven runtime. You can define deterministic paths where the conversation must follow rules, then hand off to a model for open-ended questions, all inside the same bot. It ships with channel connectors for web chat, messaging platforms and voice, plus knowledge base retrieval, analytics and a developer API for custom actions. Teams pick it when a support or sales bot has to be reliable on the fixed paths and flexible everywhere else.

Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.

Key features

Visual flow editor with LLM and knowledge-base nodes
Channel connectors for web, messaging platforms and voice
Knowledge base retrieval over your own documents
Custom code actions plus a complete developer API
Conversation analytics with drop-off and resolution metrics
Agent handoff to a human when the bot gets stuck

Pros & cons

Strengths

Deterministic flows and open-ended AI in one bot
Channel integrations reduce weeks of plumbing
Analytics make it possible to see where bots fail

Watch out for

Complex flows become hard to maintain as they grow
Advanced features sit on higher paid tiers
Costs scale with message volume as usage grows

Best for & use cases

customer support bots, lead qualification, internal help desks and voice assistants

If you're comparing similar products, check the alternatives below, or browse all tools in the AI Agents & Automation category.

FAQ

Do I need developers?

No for standard flows, which are assembled visually. Developers are useful for custom actions, API integrations and any logic that the visual editor cannot express directly.

How does it avoid wrong answers?

The usual pattern is to keep critical paths deterministic and let the model handle open questions with retrieved context. Fallback and human handoff cover the cases where neither is confident.

What does pricing depend on?

Mainly message volume and access to advanced features. A prototype is cheap, but a bot handling a busy support queue scales into higher tiers quickly.