Choosing between Voiceflow and Botpress sounds simple if you only look at the surface level.
You can use both to build AI agents, chatbots and knowledge bases and create a full-scale conversational AI experience. Both will allow you to build web chat interfaces and custom workflows, and integrate with the rest of your tech stack.
However, Voiceflow is easier to use and work with, especially for non-technical teams. Botpress allows much more customization that goes beyond the average chatbot, but you pay the cost with a complex setup.
If you’re looking for your next agentic AI platform and you’re considering Voiceflow and Botpress, we give you an honest, detailed comparison.
| Voiceflow | Botpress | |
| Best for | Non-technical teams, CX teams, support teams, agencies, and conversation designers | Developer-heavy teams, technical founders, automation teams, and companies with complex projects |
| Main strength | Clean conversation design and easier collaboration | More customization and stronger technical control |
| Ease of use | More user-friendly for non-technical users | Easier for technical users, but less friendly for business teams |
| Visual builder | Polished visual flow builder built around conversation design | Drag and drop interface with more technical options behind it |
| AI agents | Good for building customer facing AI agents across chat and voice | Good for building highly customized AI agents with complex logic |
| Chatbot platform use cases | Best for support automation, lead generation, customer experience, and voice based use cases | Best for support automation, custom workflows, integrations, and technical chatbot builds |
| Technical knowledge required | Lower. Business users can build and review flows more easily | Higher. Teams get more value when developers are involved |
| Customization | Strong enough for many customer experience use cases, but less flexible for very technical builds | Better for custom code, APIs, custom event logic, and complex workflows |
| Integrations | Good fit for common business tools like CRMs, help desks, and support systems | Better for flexible integrations, APIs, external services, and custom systems |
| Knowledge base features | Strong fit for customer-facing AI agents that answer from company content, but no data transformation | Strong fit for structured data, file based answers, and more technical knowledge setups, but no data transformation |
| Voice capabilities | Stronger native voice positioning | More focused on chat, web chat, messaging channels, and custom builds, possible voice chat in the future |
| Analytics | Useful for improving conversations and customer experience | Better for detailed analytics, logs, dashboards, and technical monitoring |
| Collaboration features | Better for support, CX, product, and agency teams working together | Better for technical teams building and managing agents together |
| Multiple channels | Suitable for chat, voice, web, and mobile use cases | Suitable for web chat, messaging apps, and multiple deployment channels |
| Security and enterprise features | Strong enterprise-grade security positioning, but no test capabilities | Stronger security and admin features on higher-tier plans, , but no test capabilities |
| Pricing model | Less public for business use, often requires pricing discussions | More public pricing, but real cost depends on AI Spend, messages, add ons, seats, and usage |
| Main downside | May feel limiting for developer heavy teams that want deep customization | Can feel too technical for non technical teams |
| Choose it if | You want a cleaner, more collaborative way to build AI agents | You want more control, custom integrations, and advanced technical flexibility |
What is Voiceflow?
Voiceflow is an AI agent platform for building chat and voice agents. It is mainly aimed at teams that want to create customer-facing conversational AI without asking developers to own every single change.
Voiceflow positions itself around AI customer experience, with use cases like support automation, lead generation, call center automation, virtual receptionists, answering services, and omnichannel AI agents. Its website describes support for web, phone, and mobile deployment, including customizable chat and voice widgets, phone-based conversational AI, and API based deployment across different interfaces.
The big thing Voiceflow gets right is the workflow.
A product manager, CX lead, support manager, or conversation designer can do things such as:
- map user intent
- define paths
- test responses
- connect data sources
- and collaborate with others
They can do all of this without feeling like they accidentally opened a developer console.
That does not mean Voiceflow is only for basic bots. It can support advanced AI agents, knowledge base answering, integrations, observability, and enterprise features. But the platform serves teams that want the building process to feel visual and manageable.
For non-technical users, this can be the tipping point in favor of Voiceflow.
What is Botpress?
Botpress is a chatbot platform and AI agent platform built for teams that want more technical control.
It also has a visual flow builder, so you are not forced to write everything from scratch. But compared with Voiceflow, Botpress leans more toward builders who are comfortable with logic, APIs, custom integrations, structured data, and technical configuration.
Botpress supports AI agents for customer support, lead generation, product recommendations, and workflow automation. Its pricing page mentions features like human handoff, conversation insights, visual knowledge base indexing, real-time collaboration, custom analytics, custom dashboards, multiple channels, external service integrations, and building agents as code through an API and SDK.
This is where Botpress makes the most sense.
If your team wants to build a simple web chat agent, Botpress can do that. But if you are planning complex flows, custom event handling, CRM integrations, custom data logic, and heavy testing, Botpress starts to look more appealing.
The tradeoff is obvious, as more customization usually means more technical knowledge.
Botpress and Voiceflow are not built for the exact same user
Botpress and Voiceflow overlap, but they were built for the same primary buyer.
Voiceflow is easier to hand to a CX team, support team, or agency. The visual builder makes it easier to understand how conversations move from one step to another. That makes it better for conversation design, stakeholder review, fast prototyping, and collaboration features.
Botpress is better when the builder is technical or has access to technical help. The platform gives you more room to create complex workflows, connect with APIs, work with structured data, and create custom AI workflows. That is great when you need deep customization, but it can slow down teams that just want to launch a useful assistant quickly.
This is the biggest difference in the Voiceflow vs Botpress debate.
Voiceflow asks, “How can we make AI agent creation easier for teams?”
Botpress asks, “How much control can we give builders?”
Both questions are valid. They just lead to different products.
Core features compared
Whether you need a basic chatbot or advanced features and AI workflows, there are some noticeable differences between the two platforms.
Visual builder
Both tools have a visual builder.
Voiceflow’s visual flow builder feels more polished for conversation designers and non-technical teams. It is easier to map the user journey, review decision points, and collaborate around conversation design.
Botpress also offers a visual drag-and-drop interface, but it pairs that with more developer-focused options. Its pricing page specifically mentions the ability to design agents visually and build agents as code using an API and SDK.
Voiceflow is easier for beginners, and Botpress gives you more flexibility, provided you have the right knowledge and team members to pull it off.
Knowledge base and data sources
Both platforms support knowledge base use cases.
This is now one of the essential features for any AI agent platform. A support agent that cannot answer from company content, help docs, product pages, or internal data sources is not very useful.
It’s also worth mentioning that neither platform offers transformation capabilities. In other words, you bring your data as is. The cleaner your data, the better the knowledge base and the better the CX. Unfortunately, this can mean a lot of additional work for your team.
Botpress includes knowledge base answering, structured data through Tables, file uploads for AI answering, and vectorized knowledge base files, including visual media like images and diagrams.
Voiceflow also supports connected knowledge and integration tools, with its website mentioning production-grade integration tools, major model providers, and control over agent behavior.
For simple knowledge base bots, either tool can work well and help you provide dedicated support without hiring extra agents.
For more structured data work, Botpress may give technical teams more control. For a conversation-led customer experience, Voiceflow may be easier to manage.
Integrations
Integration capabilities are important because AI agents rarely live alone.
They need to talk to CRMs, help desks, analytics tools, messaging channels, calendars, ecommerce systems, internal databases, and ticketing tools.
Voiceflow shows integrations with tools like Google Sheets, Zendesk, Salesforce, Airtable, Shopify, HubSpot, Make, and Gmail on its pricing page.
Botpress supports external services and APIs, multiple channels, website embedding, custom web chat, third party analytics tools, and CRM or support tool integrations on managed plans.
In plain English:
Voiceflow is better if you want integrations that are easier for business teams to work with. The selection is more limited but the integrations are easier to set up.
Botpress is better if you want flexible integrations and have the technical knowledge to wire things together properly. If you want to build multi step workflows that go beyond standard support channels (and future-proof your agentic AI tech stack), it’s the safer bet.
Analytics and reporting
Botpress has a weak analytics story for technical teams. Built-in analytics are fairly limited and only support basic chat logs and query counts, with no quality scoring, intent analysis, or CX-grade reporting.
It does support conversation history, conversation insights, custom analytics, custom dashboards, detailed logs, error notifications, event data, token spend logs, and third-party analytics integrations.
Voiceflow also talks about real-time observability, performance analytics, conversation-level visibility, and big picture observability.
The practical difference is how teams will use that data.
Voiceflow analytics are likely to appeal more to CX teams that want to improve flows, spot weak points, and make the agent better over time.
Botpress analytics are more useful when you want detailed analytics, logs, technical monitoring, custom dashboards, and deeper operational visibility. Like the features themselves, reports also have extensive customization options.
Collaboration features
Voiceflow has the edge for collaboration between non-technical teams.
That is one of the main reasons to choose it. Conversation designers, support managers, product teams, and stakeholders can work together in a visual environment that does not feel too technical.
Botpress also has collaboration features. Its Team plan includes real-time collaboration, role-based access control, and multiple people building in Botpress Studio at the same time. It also supports member permissions and separate staging and production environments.
So Botpress is not weak here, it is just more technical in flavor.
Voiceflow is better for collaborative design, while Botpress is better for collaborative building.
Botpress vs Voiceflow: Key differences
By now, it should be obvious that Voiceflow and Botpress go in different directions. However, here are some more differences you should know about.
Voiceflow is better for conversation design
If conversation design is a major part of your process, Voiceflow is probably the more natural fit.
The platform is built around planning, mapping, testing, and improving conversations. You can see how a user moves through a flow, where the AI agent should answer from a knowledge base, when it should ask a clarifying question, and when it should pass the conversation to human agents.
That is useful for teams that care about customer experience, not just automation.
A lot of AI chatbots fail because the builder thinks only in terms of responses. Good conversation designers think about intent, context, fallback paths, tone, user frustration, and what happens when the customer asks something unexpected.
Voiceflow gives those people a better working space.
Botpress offers more customization
Botpress is the better choice when the project needs more technical control.
You can use the visual drag and drop interface, but you can also go deeper with custom code, APIs, custom dashboards, external services, structured data, and more advanced analytics. Botpress also supports multiple LLM providers, backup LLMs, and bringing your own LLM or API key.
That makes Botpress a stronger fit for complex projects where the AI agent needs to do more than answer FAQs.
For example, Botpress makes sense if your agent needs to:
- Pull account data from internal systems
- Route users based on custom event logic
- Connect with several messaging apps
- Trigger workflows in business tools
- Work across multiple languages
- Support different customer journeys across multiple channels
- Hand conversations to human agents when needed
Voiceflow can also handle serious use cases, but Botpress gives technical teams more room to shape the system around the project.
Voiceflow is friendlier for non-technical users
Voiceflow is easier to explain to people who do not write code, which matters more than vendors like to admit.
In many companies, AI agents are not built by one developer in isolation. They involve support leaders, product managers, compliance reviewers, marketing teams, sales teams, and sometimes executives who want to understand what the agent will actually say to customers.
Voiceflow’s visual builder makes that process less painful.
A non-technical user can look at a flow and understand the logic. They can comment, suggest changes, test a path, or review how the agent handles user intent. That makes Voiceflow a stronger option for non-technical teams that still need serious control over the customer experience.
Botpress is better for developer-heavy teams
Botpress is not impossible for non-technical users, but it clearly rewards technical expertise.
If your team has developers, automation specialists, or technical operators, Botpress can be very flexible. You can connect more systems, build more custom logic, and use the platform in a more engineering-led way.
This is especially useful when the AI agent needs to sit inside a bigger software setup.
For example, a developer-heavy team might want a support agent that connects to a CRM, checks subscription status, reads product usage data, creates tickets, tags conversations, and triggers alerts in Slack.
That kind of build is possible in many tools, but Botpress is better suited to the messier version of it.
Voiceflow has stronger native voice positioning
Voiceflow has a clearer focus on voice capabilities.
Its website talks about chat and voice agents, web-based widgets, phone automation, and mobile deployment through APIs. Voiceflow also positions itself around customer-facing AI agents across channels, including voice and chat.
That makes Voiceflow more interesting if voice channels are part of your plan.
For teams looking at call center automation, appointment booking, answering services, or phone based conversational AI, Voiceflow may feel like the more natural fit from day one.
Botpress is still strong for web chat and messaging channels, but Voiceflow’s native voice story is easier to understand.
Pricing comparison
Voiceflow pricing
Voiceflow’s current pricing page is less public about fixed plan prices than older pricing pages and third-party breakdowns. The page separates its offer into paths for agencies and partners, plus businesses that need to deploy and manage AI agents across customer experience. It also mentions a free trial, usage-based billing, multi-client workspace management, white labeling, and request pricing for business use.
That means the real cost of Voiceflow depends on your use case, usage, workspace setup, and whether you need business or enterprise features.
This is important for buyers.
Voiceflow can look simple when you are testing it, but the real cost can change once you add production usage, more users, customer data, higher tier plans, premium support, and deployment across multiple channels.
Botpress pricing
Botpress is more public about its pricing model.
Botpress has a free Pay-as-you-go plan at $0 per month plus AI Spend. Plus is listed at $79 per month when paying annually, Team at $495 per month (when paid annually), while Managed and Enterprise plans have custom pricing. Botpress also charges AI Spend separately, and its page says LLM usage is billed at provider cost without markup.
Botpress also has usage limits and add-ons.
For example, the free plan includes 500 incoming messages and events per month, Plus includes 5,000, Team includes 50,000, and additional blocks of 5,000 messages cost $20 per month. Additional bots, seats, vector database storage, file storage, and Always Alive capacity can also add to the final price.
So Botpress pricing is transparent, but not always simple.
The sticker price is only part of the story. Your real cost depends on monthly users, message volume, LLM usage, add-ons, collaborators, data storage, and whether you need premium support or managed implementation.
Which one is cheaper?
Botpress is easier to estimate from the outside because more pricing details are public.
Voiceflow may be easier for teams that want guided deployment, especially if they are talking to sales for business use. But without a public fixed price for every business plan, you will need to request pricing to understand the actual cost.
Botpress can start cheaply, especially with the free plan. But usage, AI Spend, add-ons, and technical build time can change the economics quickly.
My take: do not compare only plan prices, but also make sure to compare the cost of getting a useful AI agent live.
That includes setup, content prep, testing, integrations, analytics, maintenance, support, and the person who has to fix the thing when it breaks.
Self-hosting options and open source reality
This is an area where people can easily get outdated information.
Botpress used to be strongly associated with open source and self-hosting. But Botpress v12 and all self-hosted or locally installed versions are now officially sunset and are no longer available for purchase, download, or new deployments. Botpress says new users should use Botpress Cloud.
That does not mean nobody online talks about Botpress open source anymore. You will still find old references, old GitHub pages, old discussions, and older self-hosted guides.
But if you are choosing a platform today, do not assume Botpress gives new customers a clean self-host path.
For most new teams, Botpress vs Voiceflow is now much more of a cloud platform comparison.
Security and enterprise features
Voiceflow has a strong enterprise-grade security story.
Its security page mentions SOC 2 Type II, ISO/IEC 27001:2022, GDPR compliance, HIPAA compliance, SSO, automated and code reviews, vulnerability scanning, external penetration testing, and enterprise access controls.
Botpress also includes security and compliance features in higher plans, including logs of workspace changes, trusted domain restrictions, DPA, BAA, custom data retention, and data residency policies.
For enterprise buyers, both tools deserve a proper security review.
The better choice depends on your internal requirements. If your legal team cares about data residency, customer data handling, access controls, healthcare use cases, audit logs, and support SLAs, you should not rely on the pricing page alone.
Ask both vendors for their security docs, subprocessors, data retention policy, compliance reports, and support terms.
Voiceflow vs Botpress for customer experience
Voiceflow feels better suited for teams that think in terms of customer experience.
That includes support journeys, voice channels, lead qualification, web chat, human handoff points, fallback paths, tone, and customer data use.
If your team is building an AI agent that customers will actually interact with every day, the design process matters. You need to know what the agent says, why it says it, when it should stop guessing, and when it should send the user to human agents.
Voiceflow gives non-technical teams more control over that process.
Botpress can absolutely support customer experience use cases too, especially for support automation and lead generation. But it is better when you have the technical expertise to build and maintain the logic behind the scenes.
Botpress vs Voiceflow for complex workflows
For complex workflows, Botpress has the edge.
If your agent needs to do simple support answering, either platform can work.
But if your agent needs to connect to many tools, handle custom events, use structured data, call APIs, support complex flows, and move between different messaging apps, Botpress gives you more room.
This is where Botpress offers a stronger fit for technical teams.
The danger is overbuilding.
A lot of teams choose the more customizable platform because it feels safer. Then they spend weeks building a system that a simpler platform could have launched in a few days.
So be honest about your needs.
If you need deep customization, Botpress makes sense. If you need quick deployment and a clean design process, Voiceflow may be the better call.
Which one should you get?
You should have a pretty clear idea of which tool works better for your use case by now. Here’s a practical breakdown to help you decide.
Choose Voiceflow if…
Choose Voiceflow if your team cares most about conversation design, speed, collaboration, and customer experience.
It is the better option if your builders are support managers, CX leaders, product managers, conversation designers, or agency teams. It also makes sense if you need chat and voice capabilities, want a user-friendly interface, and prefer a platform that non-technical teams can actually use without asking engineering for every change.
Voiceflow is also the better choice if your AI agents need to be reviewed by people outside technical teams. The visual builder makes it easier to see what is happening and improve flows over time.
Choose Botpress if…
Choose Botpress if your team has technical expertise and wants more customization.
It is the better option if you need custom integrations, complex workflows, structured data, custom code, custom event logic, detailed analytics, and more control over how the agent behaves.
Botpress is also a better fit for complex projects where the AI agent is part of a larger technical system. If you have developers involved and want to build a highly customized chatbot platform, Botpress gives you more room to work.
Final verdict: Voiceflow vs Botpress
Voiceflow and Botpress are both strong AI agent platforms, but they are usually a better fit for teams that want to build and manage their own AI agents.
Voiceflow makes more sense if your team cares about conversation design, quick deployment, collaboration, and giving non-technical teams more control over the AI experience. Botpress is the stronger choice if you have technical expertise in-house and need more customization, custom integrations, detailed analytics, and complex workflows.
But there is a third option worth considering.
If you are not just looking for a chatbot platform, but an enterprise customer experience platform built around AI agents, Quiq may be a better fit than both.
Quiq is built for companies that want AI agents across the customer journey, including messaging, voice, email, human agent handoff, reporting, integrations, and AI assisted support for human agents. Quiq’s AI Studio also gives teams a place to build, test, deploy, and monitor AI agents, with enterprise guardrails and visibility built in.
That distinction matters.
Voiceflow and Botpress are strong when you want a builder platform. Quiq is stronger when the goal is to connect AI agents directly to real customer experience operations, across channels, systems, and support teams.
So the honest answer is:
Choose Voiceflow if you want a clean, collaborative tool for conversation design and customer-facing AI agents. Choose Botpress if you want a more technical platform for custom AI agents and complex workflows.
Choose Quiq if you want an enterprise agentic AI platform where AI agents, human agents, voice, messaging, analytics, and integrations are part of the same customer experience strategy.
Book a free demo with us today to find out how Quiq can fit into your agentic AI workflows.
FAQs
Is Voiceflow better than Botpress for non technical teams?
Yes, for most non-technical teams, Voiceflow is easier to learn and manage. Its visual builder is cleaner, collaboration feels more natural, and CX or support teams can review conversations without relying heavily on developers.
Is Botpress more powerful than Voiceflow?
Botpress gives technical teams more control over APIs, structured data, custom event logic, and advanced integrations. That makes it a stronger option for highly customized AI agents and complex automation projects.
Can both Voiceflow and Botpress connect to CRMs and support tools?
Yes. Both platforms support integrations with CRMs, help desks, analytics tools, and messaging channels. Voiceflow focuses more on business-friendly integrations, while Botpress gives developers more flexibility for custom setups.
Which platform is better for voice AI and phone automation?
Voiceflow has a stronger focus on voice AI, phone automation, and customer-facing conversational experiences across chat and voice channels. Botpress is stronger around web chat, messaging apps, and technical chatbot deployments.
Is Quiq a better option for enterprise customer experience teams?
Quiq may be a better choice for enterprises that want more than a standalone chatbot platform. It combines AI agents, voice, messaging, reporting, integrations, and human agent handoff inside one customer experience platform.
