Vapi VS Langfuse
Compare Vapi VS Langfuse and see what are their differences
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Vapi
Retell AI
Bland AI
Eleven Labs
Voiceflow
Deepgram
Bolna
Smith.ai
Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
PromptLayer
Langfuse is an open-source LLM engineering platform designed to empower developers by providing insights into user interactions with their LLM applications. We offer tools that help developers understand usage patterns, diagnose issues, and improve application performance based on real user data. By integrating seamlessly into existing workflows, Langfuse streamlines the process of monitoring, debugging, and optimizing LLM applications. Our platform's robust documentation and active community support make it easy for developers to leverage Langfuse for enhancing their LLM projects efficiently. Whether you're troubleshooting interactions or iterating on new features, Langfuse is committed to simplifying your LLM development journey.
LangfuseNo features have been listed yet.
Based on our record, Langfuse should be more popular than Vapi. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The Vapi platform helps developers build and deploy voice agents and AI products in Python, React, and TypeScript. It provides two ways to make intelligent voice apps. It's assistant's option allows you to create simple conversational services that may require a single system prompt for the underlying model's operations. - Source: dev.to / 4 months ago
It can make/take phone calls[0], but they need to be prompted on the nature of the call, the data they need, and how to collect it. They can also output the results of the call via API. An AI agent from Masterworks recently called me using this technology. [0] https://vapi.ai/. - Source: Hacker News / 5 months ago
### Resources **VAPI Documentation:** [vapi.ai/docs](https://vapi.ai/docs) โ Voice agent API, webhook integration, real-time call transcription, intent detection endpoints, assistant configuration, function calling. **Twilio Voice API:** [twilio.com/docs/voice](https://twilio.com/docs/voice) โ Phone integration, call handling, webhook callbacks, TwiML response formatting, call status tracking. **GitHub... - Source: dev.to / 6 months ago
## Resources **VAPI**: Get Started with VAPI โ [https://vapi.ai/?aff=misal](https://vapi.ai/?aff=misal) **VAPI Documentation:** Official [VAPI API reference](https://docs.vapi.ai) covers WebSocket voice streaming, real-time transcription configuration, and function calling patterns for conversational AI. **Twilio Voice API:** [Twilio Media Streams](https://www.twilio.com/docs/voice/media-streams) documentation... - Source: dev.to / 6 months ago
Paul Atreides uses the Voice as a tool for control and assertion. Imagine commandeering an AI agent with this voice. We built an AI agent using Composio, Vapi, and OpenAI TTS integrated with Gmail, Slack, and Google Calendar. It can summarise emails, schedule meetings, and search for Slack messages. Your entire morning routine is stress-free. - Source: dev.to / 10 months ago
In this project we will build a Python banking assistant agent using Strands Agents and make it observable and continuously evaluated using Langfuse โ step by step. - Source: dev.to / 6 days ago
Langfuse is the open-source standard for LLM observability. It traces every LLM interaction โ prompts, completions, latency, token usage, cost โ and provides the tooling to debug, evaluate, and optimize LLM applications in production. Think of it as "Datadog for LLM calls" with a focus on prompt engineering workflows. - Source: dev.to / 25 days ago
You're monitoring production traffic. You need Langfuse / Phoenix / Helicone / Braintrust for that. Online eval is a different problem class: implicit feedback, drift detection, hallucination rates on your data, not on HellaSwag. - Source: dev.to / about 1 month ago
Gateway or proxy attribution. A reverse proxy in front of the model-provider API records the request, computes the cost, and exposes per-customer breakdowns. Open-source options include Helicone, LiteLLM, Langfuse, and OpenLLMetry. Hosted equivalents serve as the AI cost observability layer for teams that want centralized visibility: LangSmith, Datadog LLM Observability, Arize Phoenix. Adds a network hop.... - Source: dev.to / about 1 month ago
Same approach works with Langfuse, Phoenix, Braintrust, or your existing OTel pipeline โ the metadata.userId pattern is the universal part. - Source: dev.to / about 2 months ago
Retell AI - API that enables developers to build human-like voice agents
Helicone AI - Open-source LLM Observability for Developers
Bland AI - An AI Phone Calling API
LangSmith - Build and deploy LLM applications with confidence
Eleven Labs - The most realistic and versatile AI speech software, ever. Eleven brings the most compelling, rich and lifelike voices to creators and publishers seeking the ultimate tools for storytelling.
LangChain - Framework for building applications with LLMs through composability