So you're looking into conversational AI options? You're definitely not alone – the number of platforms out there keeps growing, and it can feel overwhelming trying to figure out which one is right for you.
Whether you want to set up a basic AI chatbot to handle customer questions or you're thinking bigger – like building an AI agent that can have back-and-forth conversations – there's a lot to think about.
Botpress and Rasa emerge as top chatbot building platforms, each taking distinctly different approaches to chatbot development. One prioritizes ease of use and visual design, while the other focuses on open-source flexibility and machine learning customization.
Ready to explore which platform aligns with your project needs? Let's examine Botpress vs. Rasa in detail.
Quick Overview: Rasa vs. Botpress
TL;DR: Rasa is an open-source, developer-first framework for building ML-based chatbots from scratch, while Botpress is a visual AI agent platform designed for creating LLM-powered agents.
Rasa is an open-source conversational AI platform built for technical teams. It offers flexibility for building intent-based bots with custom NLU pipelines and dialogue management using stories and rules.
Rasa is fully self-hostable, making it attractive to enterprises with strict data control requirements. However, Rasa’s price point positions them as out of reach for most SMBs or startups and is geared toward large teams with larger budgets.
Additionally, almost everything in Rasa — from knowledge ingestion to security layers — must be built and maintained in-house.
Botpress is an AI agent building platform. With features like in-house retrieval-augmented generation (RAG) and multi-turn memory, Botpress enables the creation of AI agents that can drive product recommendations, onboarding, internal workflows, and more – all while being fully customizable and deployable on private infrastructure. Teams still have full-stack flexibility to code and customize, but they start from a platform that already solves much of the heavy lifting.
Feature-By-Feature Comparison
Rasa vs. Botpress Pricing Comparison
TL;DR: Rasa is priced for enterprise buyers, while Botpress offers cost-effective options for SMBs and enterprises.
Rasa Pricing
While Rasa’s core platform is free for developers to use, their advanced support, scalability features, and enterprise security are locked behind paid tiers.
These pricing plans are primarily targeted at large teams or businesses looking for long-term commercial support, compliance, and dedicated infrastructure.
Rasa's provides three pricing tiers:
Botpress Pricing
Botpress offers a free plan that includes $5 in monthly AI credits. These credits are what allow your bots to “think” by making calls to large language models (LLMs). In simple terms, the credits are like fuel that lets bots pull information from knowledge sources and generate natural responses.
The Pay-As-You-Go Plan allows teams to only pay for the AI they bots use, instead of a set monthly fee. This makes it flexible and cost-friendly, since costs vary based on how much bots are used.
Botpress offers straightforward pricing tiers:
Integration Capabilities
TL;DR: Both Rasa and Botpress let teams integrate with any backend system, but Botpress includes built-in knowledge tools and RAG while Rasa requires developers to build these from scratch.
Rasa and Botpress both provide APIs and SDKs that allow connection to virtually any backend or third-party system. In practice, though, they diverge when it comes to knowledge sources.
Rasa doesn’t include built-in knowledge base capabilities. If teams want the chatbot to answer questions from help docs or external data, they must build that themselves – typically by setting up a custom search system (like ElasticSearch or RAG) and writing Python actions to fetch answers. Features like uploading PDFs or accessing live data aren't supported out of the box either, so everything must be manually built and maintained.
Botpress comes with built-in tools for working with knowledge sources. Teams can upload PDFs, connect APIs, scrape websites, or pull from CSVs and JSON files. Its built-in retrieval-augmented generation (RAG) engine finds the most relevant info at runtime and creates helpful responses based on it.
Security Features
TL;DR: Rasa’s self-hosted model gives teams full control and responsibility for security and compliance, while Botpress provides advanced built-in security features and compliance tools.
Rasa provides strong security by design, primarily through self-hosted deployments. This ensures that sensitive data never leaves team infrastructure, giving organizations full control over encryption, access control, and compliance standards.
However, that flexibility comes with responsibility. Teams must configure and maintain all security layers themselves — including SOC2 readiness, audit logging, server hardening, and more. Security features like role-based access control (RBAC), SSO, and 2FA are not built-in and typically require custom development or third-party tools.
As an open-source framework, Rasa’s security posture depends heavily on how it’s deployed (e.g. self-hosted vs. Rasa X/Enterprise).
In practice, Rasa is best suited for organizations with dedicated security engineering resources that need to meet specific regulatory requirements on their own terms.
Botpress comes with enterprise-grade security features baked in – including role-based access control (RBAC), data encryption, and SOC2 compliance certifications. Because these controls are ready to use, teams can focus on building agents without heavy security overhead.
Botpress is a better fit for companies that want to move quickly while still meeting compliance standards (e.g. in healthcare or finance), without staffing a large in-house security team.
Memory
TL;DR: Rasa requires external setup to store memory across sessions. Botpress includes built-in memory for tracking user context automatically over time.
Rasa can track information during a conversation using slots, which are stored temporarily within the session.
However, Rasa doesn’t offer built-in persistent memory across sessions. To retain context between user interactions (like remembering user preferences or past issues), teams must set up an external database and write custom actions – usually in Python – to read from and write to that database manually.
Botpress comes with built-in long-term session memory. It can automatically store and retrieve user data – like previous orders or support history – across multiple interactions. Developers can define what to remember, how long to retain it, and how it’s used – without needing to wire up external storage or write custom backend logic. This makes it easy to build personalized, context-aware AI agents.
Community & Support
TL;DR: Both Rasa and Botpress offer strong developer resources, but Botpress delivers more support across pricing tiers, plus a highly active community and real-time assistance.
Rasa provides detailed documentation and developer-focused learning materials through its official docs, blog posts, and GitHub repos. It has an active community forum and a public Discord server, where developers share solutions and discuss best practices. Rasa Pro and Enterprise users can access additional support through Slack channels, email, or custom onboarding services. However, support for the open-source edition is limited to community channels, and there's no direct live support unless on a paid plan.
Botpress, by contrast, offers a more hands-on support experience designed for teams at all stages. Live chat support connects users directly with the Botpress team for quick troubleshooting and setup help. Max, the AI Support Bot, gives instant answers and product guidance inside the platform.
Botpress also offers dedicated Customer Success Teams that work with businesses to optimize their AI agents and ensure long-term success. For those who are looking for a community, Botpress has a 30,000+ member Discord community that offers peer-to-peer support and daily live AMAs where the Botpress team answers questions in real time.
Ultimately, Botpress delivers both self-service education and collaboration through community and expert support.
Both platforms provide ample documentation and community support, but Botpress combines self-directed education with live support, making it a stronger choice for teams of all sizes to get answers fast.
Customization & Flexibility
TL;DR: Rasa offers flexibility through code and modular design, but requires manual setup. Botpress provides full-stack customization including built-in coding and UI control.
Rasa is highly flexible and developer-first. It uses open-source SDKs and modular architecture, giving teams full control over how the chatbot behaves, connects to systems, and processes language.
Developers can write custom Python code using Rasa’s Action Server to handle backend logic, call APIs, or manage conversations. Conversation flows are designed using stories and rules, which offer control but can become complex as bots grow.
Botpress takes a different approach to customization by combining a visual interface with direct coding options. Developers can write JavaScript or TypeScript directly in Botpress, use pre-built nodes or build their own, and call external APIs with minimal setup.
Flows are modular, reusable, and easy to manage visually, making Botpress accessible to both technical and semi-technical teams. Teams can also customize both backend logic and frontend behavior — including how the chatbot looks and behaves in the widget or across channels.
Which Platform is Better for My Business?
1. 24/7 Multilingual Support for a Global Travel Company
Key Problem: Providing 24/7 multilingual support across channels for a global customer base.
TL;DR: Rasa offers multilingual support and full control over deployments but requires significant engineering effort. Botpress delivers multilingual NLU, channel flexibility, and persistent memory out of the box.
Amir leads customer support at a global travel booking platform. His team handles urgent, multilingual inquiries — like flight changes, cancellations, and travel alerts — across WhatsApp, mobile apps, and their website. Amir needs:
- A chatbot that can understand and respond in multiple languages
- A consistent experience across platforms
- Access to real-time backend data for bookings and changes
Rasa supports multilingual bots through custom training pipelines, allowing teams to build separate language models and flows.
However, there’s no built-in translation or language routing in Rasa, so teams must develop and maintain this infrastructure themselves. Persistent memory also isn’t included — developers must connect to external databases and design their own logic for storing and retrieving context.
While Rasa offers complete deployment flexibility and open-source control, it comes with higher development overhead.
Botpress supports 100+ languages with customizable NLU per locale, and lets teams define dynamic flows based on language, location, or user behavior. It includes out-of-the-box integrations with WhatsApp, web chat, and custom channels. Built-in long-term memory helps bots recall past interactions and user preferences, reducing friction for frequent travelers.
Teams can deploy fast and scale affordably thanks to Botpress’s free tier, pay-as-you-go pricing, and predictable paid plans.
For multilingual travel support that’s scalable and easier to maintain, Botpress is the stronger choice.
2. Subscription SaaS Customer Support Scaling
Key Problem: A fast-growing SaaS company wants to deflect basic technical support and billing inquiries without hiring more agents.
TL;DR: Rasa offers full backend control for complex SaaS support, but requires significant developer effort. Botpress includes persistent memory and native API support, making it faster to deploy and easier to maintain.
Sam is the Head of Support at a rapidly growing B2B SaaS company. His team handles a flood of tickets related to login issues, billing confusion, and onboarding questions. To keep up without hiring more agents, Sam needs:
- A chatbot that can resolve common technical and billing questions
- Seamless deployment within Zendesk and Intercom workflows
- Real-time access to CRM and billing systems like Stripe or HubSpot
Rasa gives Sam’s team full backend control through Python SDKs and custom actions. They can connect to billing tools and CRM data using custom logic.
However, Rasa lacks built-in persistent memory — developers must implement their own storage and retrieval system to retain user history. Deployment within helpdesk platforms like Intercom also requires extra integration work.
Rasa’s flexibility makes it powerful, but time-consuming for lean teams without a dedicated engineering pipeline. Rasa’s pricing may also be steep for Sam’s organization.
Botpress, on the other hand, comes with out-of-the-box memory, allowing bots to recall users across sessions and personalize follow-ups. The platform supports direct API calls and visual logic builders, so Sam’s team can connect the bot to Stripe or HubSpot without writing a custom backend.
Botpress also supports native integrations with Zendesk and Intercom, making setup smoother. Teams can start free or use pay-as-you-go pricing, then scale into predictable paid tiers.
When it comes to SaaS companies looking to move quickly without compromising customization, Botpress offers faster time-to-value and greater long-term flexibility.
3. Automated Order Management for a D2C E-commerce Brand
Key Problem: Automating post-purchase support like tracking, returns, and product questions.
TL;DR: Rasa enables advanced automation with full backend control but requires heavy developer investment. Botpress offers real-time Shopify integration and memory, out of the box.
Priya leads CX at a D2C e-commerce brand that just expanded internationally. Her team handles thousands of queries about order tracking, returns, and product details every week. Priya needs:
- A chatbot that can guide customers through returns and track orders in real time
- Seamless integration into Shopify and web chat
- Support for automating repetitive tasks like refund requests or FAQs
Rasa lets Priya’s team build advanced logic using custom actions written in Python. Developers can integrate Shopify's APIs, manage return logic, and trigger refund processes by building their own backend workflows.
However, Rasa has no built-in persistent memory – teams must connect external databases and manage storage manually. Rasa doesn’t include native connectors for Shopify or order systems, so deployment takes longer and requires a skilled dev team.
Botpress offers built-in Shopify integration, allowing bots to fetch order data, check shipping status, or trigger returns with minimal setup. Built-in long-term memory enables the bot to remember user history and product preferences, which is especially helpful for upsells or follow-up interactions.
Botpress’ visual workflow builder makes it easy to automate multi-step flows like return approvals or refund tracking. Additionally, Botpress pricing is ideal for Priya as it has a pay-as-you-go option, and predictable monthly plans for scaling up.
For e-commerce brands looking to automate post-purchase support quickly and affordably, Botpress provides a better balance of power and ease.
4. Heavily Regulated Industry Support (e.g. Healthcare)
Key Problem: Automating inquiries while meeting strict compliance and audit needs.
TL;DR: Rasa supports secure, on-premise deployments with full control, but security and compliance must be built and maintained manually. Botpress provides enterprise-grade security features natively.
Marcus is responsible for customer experience at a healthcare provider. His team wants to automate scheduling, policy questions, and coverage info while staying compliant with HIPAA and regional data laws. Marcus needs:
- A secure chatbot that protects patient data
- Full audit logs and access control
- Option to deploy on-premise for compliance with internal security policies
Rasa gives Marcus’s team full control over security by enabling on-premise deployment. This means data never leaves company servers, and teams can meet HIPAA and GDPR requirements using their own infrastructure and tools.
However, Rasa doesn’t offer built-in features like role-based access control (RBAC), audit logging, or SSO – teams must develop these themselves or integrate with third-party tools. All compliance workflows, from encryption to identity management, require engineering effort.
Botpress, by contrast, includes enterprise-grade security features out of the box: built-in RBAC, audit trails, encrypted memory, and SOC 2 Type II compliance. Developers can build automated workflows like lab test scheduling or insurance checks while keeping sensitive data securely stored and auditable.
For healthcare and regulated industries where time-to-compliance matters, both Botpress and Rasa are good choices, but Botpress is the faster and secure option without added dev overhead.
The Bottom Line: Botpress vs Rasa
Rasa and Botpress are both powerful platforms for building conversational AI, but they serve different priorities and development approaches.
Rasa is best for enterprise teams that want control over their stack and are ready to engineer every layer themselves. It’s open-source and modular, which makes it powerful for regulated or self-hosted environments. The trade-off is that almost everything — from knowledge ingestion to security layers — must be built and maintained in-house.
Botpress delivers customization while also providing a large set of capabilities: enterprise security, human-in-the-loop tools, memory, RAG, and plenty of integration options. Teams still have full-stack flexibility to code and customize, but they start from a platform that already solves much of the heavy lifting. This balance makes Botpress especially compelling for teams that want endless customization with a faster path to production and scale.
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