The Developer Platform for Enterprise AI Agents

The control of building in-house. The speed of buying off-the-shelf. The governance to operate at enterprise scale.

Open source foundation
On-prem / private cloud / air-gapped
LLM-agnostic — bring your own model
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Top enterprises trust Rasa

Build agents that don't just respond — they resolve

WHY DEVELOPERS CHOOSE RASA

Build agents that don't just

respond — they resolve

Rasa gives you the framework to build enterprise AI agents with full architectural control — not a black box you configure.

Strong Architecture
Patented dialogue manager orchestrates autonomous reasoning and guided workflows in one system. LLM fluency meets deterministic logic — no hallucinations in your business rules.
Open Framework
Full access to prompts, policies, and codebase. Swap your LLM, your infra, your integration layer. The framework adapts to your requirements — not the other way around.
Multi-Agent Orchestration
Coordinate agents across systems with shared state, clean handoffs, and unified memory. Scale from a single agent to a decentralized enterprise network without architectural rework.
Full Observability
Inspectable dialogue state. Event-based tracker. Every orchestrator decision is traceable — not buried in logs. Debug, test, and improve with confidence.
Enterprise Dev Tooling
Work with Cursor, Copilot, VS Code, GitHub, Jenkins, and OpenTelemetry alongside Rasa. Git versioning, CI/CD pipelines, and rollback support built-in.
Deployment Control
Your infrastructure, your LLM provider, air-gapped if required. On-prem is the default — not an add-on. Built for regulated environments from the start.

Three layers. One coherent system.

how it works

Three layers.

One coherent system.

Orchestrator

The coordination layer that decides what happens next. Manages context, routes to the right skill, and keeps journeys consistent across steps, systems, and channels. If an AI agent is the performer, orchestration is the stage manager.

Skills

Reusable capability units the agent invokes on demand. A skill has a purpose, inputs it needs, tools it can use, and boundaries it respects. Build once, reuse across agents — no copy-paste prompt sprawl.

Memory

The continuity layer that carries context over time. Decides what should be remembered, when it should be used, and when it must be ignored. Session memory for coherence. Long-term memory for relationships.

50M+
conversations/month in production
80+
enterprise deployments
18k+
GitHub stars
3x
faster than DIY frameworks

Three layers. One coherent system.

HOW WE COMPARE

Stop rebuilding the

platform layer

DIY frameworks give you flexibility but consume engineering capacity building the foundation. Low-code tools are fast to configure but closed to customize. Rasa gives you both.

Capability
Rasa
DIY
Low-Code
Vendor Agents
On-prem / air-gapped deployment
—
—
LLM-agnostic (swap providers)
—
—
Multi-agent orchestration built-in
Build yourself
—
Vendor-controlled
Guided + autonomous skill mixing
Build yourself
Config only
Black box
Inspectable dialogue state
Build yourself
—
—
Open source foundation
—
—
Time to production
4-8 weeks
6–18 months
2–6 weeks*
3–6 weeks
* Low-code tools are fast for simple use cases but hit walls at enterprise complexity.

What engineering teams say

"We evaluated six platforms. Rasa was the only one that let us deploy on-prem, swap LLM providers, and maintain full observability. Our security and compliance teams signed off in weeks, not months."
Marcus K.
Lead Architect · Allianz
"With LangChain we were spending 60% of our time building orchestration and memory systems from scratch. Rasa gave us that layer out of the box — we shipped to production in 8 weeks."
Sophie L.
Platform Engineering Lead · Deutsche Telekom
"The inspectable dialogue state changed how we debug. Every decision is traceable — we can reproduce issues, understand why the agent behaved a certain way, and fix it with confidence."
Thomas R.
CTO · European Insurance Group

AI that adapts to your business, not the other way around

Ready to build enterprise

AI agents you actually own?

Get started with docs, explore the open source framework, or talk to our solutions engineering team about your deployment requirements.

start building