Eleven Labs vs. Vapi. Which one is just a wrapper and which is more than that?

ElevenLabs is not just a wrapper around LLMs—its core product is AI-powered text-to-speech (TTS), specializing in realistic voice synthesis. While it may use some LLM technology under the hood for tasks like understanding context, emotion, or intent, its primary innovation lies in voice generation, not language modeling per se.

Here’s a breakdown:

• Core technology: ElevenLabs uses deep learning for speech synthesis, likely involving models similar to or evolved from Tacotron, VITS, or their own proprietary architectures. It focuses on generating natural, expressive, human-like speech.
• Not just a wrapper: It doesn’t just take GPT-style output and read it aloud. It creates custom voices, clones voices, and can simulate emotional tone, pacing, and multilingual delivery—which goes beyond what a typical LLM wrapper does.
• Where LLMs might be used: ElevenLabs could integrate LLMs for tasks like:
  • Summarizing or rephrasing text before narration
  • Understanding tone or sentiment to adjust vocal expression
  • Enabling conversational agents in combination with voice

So in short: No, it’s not essentially a wrapper around LLMs. It’s a voice AI company with a distinct technological stack focused on speech, not just language.

VAPI (Voice API) is much closer to being a wrapper around LLMs, especially in the context of building voice agents. It’s designed to let developers easily create voice-based AI applications by integrating:

1. LLMs (like GPT-4, Claude, or others) for natural language understanding and generation
2. Speech-to-Text (STT) for converting user speech into text (e.g., using Whisper or Deepgram)
3. Text-to-Speech (TTS) for replying with synthesized voice (e.g., using ElevenLabs or PlayHT)

So what exactly is VAPI doing?

VAPI acts as an orchestration layer or wrapper around:

• STT (understanding voice input)
• LLM (processing and generating responses)
• TTS (generating voice replies)

It abstracts the complexity of integrating all these components individually, allowing developers to:

• Set up phone or web-based voice agents quickly
• Plug in their choice of LLMs and voice services
• Handle interruptions, latency, call management, and more

So is it “just a wrapper”?

Yes and no:

• Yes, in the sense that it wraps powerful tools like GPT, Whisper, ElevenLabs into one easy-to-use interface.
• No, in that it adds value via orchestration, real-time interaction handling, interrupt logic, and call infrastructure.

In short, VAPI is a voice-agent wrapper built on top of LLMs and speech services, aiming to simplify and productize conversational voice AI.

🔈 ElevenLabs

• Uses deep generative audio models (proprietary TTS models)
• Specializes in voice quality, emotion control, multilingualism
• Offers features like voice cloning, speech-to-speech transformation
• Likely uses LLMs internally for emotion modeling or context understanding, but LLMs are not central to the offering

Conclusion: Not a wrapper around LLMs. It’s a standalone voice synthesis engine, often used alongside LLMs in other products (like VAPI, or custom voice assistants).

📞 VAPI (Voice API)

• Built as a voice interface layer on top of:
  • LLMs (e.g., OpenAI GPT-4, Claude)
  • STT engines (e.g., Whisper, Deepgram)
  • TTS engines (e.g., ElevenLabs, PlayHT)

• Provides the tools to manage:
  • Conversational flow
  • Interruptions & latency
  • Audio streaming & telephony (VoIP, PSTN)
• Offers developer SDKs and APIs to wire up voice bots with minimal code