Rasa
Conversational AI FrameworksOpen-source framework for building contextual voice and text AI agents with full control over dialogue management.
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👍 Pros
- ✓Full control over NLU pipeline
- ✓On-premise for data sovereignty
- ✓Mature and battle-tested at scale
- ✓Strong enterprise support option
👎 Cons
- ✗Steeper learning curve than no-code tools
- ✗Requires ML expertise to tune well
- ✗Voice integration requires additional plumbing
Features
- ✓ Open-source NLU & dialogue
- ✓ Custom entity extraction
- ✓ Multi-turn conversation management
- ✓ On-premise deployment
- ✓ REST & gRPC APIs
- ✓ Active ML training loop
- ✓ Enterprise support available
From the blog
View all →15 May 2026 · 19 reads
ElevenLabs, OpenAI TTS, and Azure: Which Voice Is Right for Your Agent?
The TTS provider you choose shapes how users perceive your voice agent. Here's a practical comparison of the three leading options for production deployments.
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How to Evaluate a Voice AI Agent: 5 Metrics That Actually Matter
Not all voice agents are created equal. These five metrics will tell you whether an agent is ready for production — or still needs work.
Read more →9 May 2026 · 6 reads
The Voice Stack Explained: STT, LLM, and TTS
Every voice AI agent is built on a three-layer stack. Understanding each layer — and the tradeoffs between providers — is essential for building reliable, natural-sounding agents.
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