Rasa is an open-code platform for enterprise conversational AI agents. This listing delivers a fully licensed dialogue engine, container images, and a Helm chart to deploy in your own infrastructure, on the LLM you choose.
The world's largest banks, telecoms, and healthcare companies run Rasa in production. Rasa is an open-code platform for building and running conversational AI agents in the enterprise. The orchestration architecture you would otherwise assemble yourself ships prebuilt, refined over more than a decade of conversational AI in production. You build agent skills in code, locally and version-controlled; this listing delivers the engine that runs them.
With Rasa, you can orchestrate the full spectrum of dialogue: guided workflows for steps that must follow a defined path, autonomous prompt-based reasoning where they can't be predefined, knowledge retrieval for document-grounded answers, and tool calls into your systems. You decide per agent skill.
Rasa is also architected for observability. At build time, Rasa Inspector, a debug panel, shows you the decision-making behind every test conversation. And in production, every message, action, and memory update lands in the Tracker Store as an event history you own (DynamoDB, PostgreSQL, or Redis), with observability through OpenTelemetry into the monitoring stack you already run.
What you get with this listing:
Production container images and Helm chart, pulled directly from AWS Marketplace ECR
The fully licensed Rasa engine; a license reflecting your agreed terms is issued on purchase
A deployment you own and operate: your Amazon EKS cluster, your existing CI/CD, the LLM you choose
Usage instructions covering prerequisites and installation
Deployment requires supporting infrastructure in your account, such as a PostgreSQL database (for example, Amazon RDS) and Kafka; full prerequisites are in the usage instructions.
Highlights
Rasa is the open-code conversational AI Agent solution for enterprises. It allows you to automate internal and external customer conversations. Established in 2016, Rasa is known for building, deploying, and managing conversational customer experiences.
Rasa comes with a deployable dialogue engine that orchestrates agent skills anywhere on the spectrum from fully guided workflows to fully autonomous, prompt-based reasoning, with built-in patterns for interruptions, corrections, and topic shifts.
Rasa includes more than simply a framework and runtime; it includes collaboration workflows to support teams, including testing, simulation, and evaluation workflows to improve your AI Agents.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This listing uses a single pricing dimension: Conversations. You buy under a contract, and your cost scales with the number of conversations your AI agents handle. There are no separate instance sizes or feature tiers to choose from. Instead, you commit to a conversation volume, and the platform supports building, testing, deploying, and governing agents across that usage. As your conversation volume grows, your committed quantity grows with it. This keeps the pricing structure tied directly to how much your deployed agents are actually used.
Top-of-mind questions for buyers
What counts as one conversation for billing purposes?
A conversation is an exchange between an end user and your AI agent. The listing separates external conversations, which involve outside users, from internal conversations handled by your own employees. These are counted differently. Each conversation your deployed agent handles counts toward your committed volume.
What happens if my conversation volume grows beyond my committed amount?
Because this is a contract tied to conversation volume, your committed quantity sets your usage level. If your deployed agents handle more conversations than committed, contact the vendor to adjust your contract. The platform supports scaling to higher volume on infrastructure you operate.
What capabilities are included once I commit to a conversation volume?
Your contract covers building, testing, deploying, and governing AI agents. You get a visual flow builder, natural language understanding, end-to-end testing, and deployment on container orchestration. It also includes access controls, single sign-on, and personal data management. A voice connector is available as a separate purchase.
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Helm charts are Kubernetes YAML manifests combined into a single package that can be installed on Kubernetes clusters. The containerized application is deployed on a cluster by running a single Helm install command to install the seller-provided Helm chart.
Version release notes
Rasa Pro Helm chart 2.6.1.
Additional details
Usage instructions
Follow the steps in the 'Pull container images and Helm charts' section below in order to pull the Helm chart, you do not need to pull the container images. Next, follow the steps documented in the README file inside the chart to launch the product.
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