Langfuse
Helicone AI
LangSmith
LangChain
Braintrust.dev
Openlayer
Portkey
LastMile AI
SecondStack
liteLLM
Portkey
Merlin Unified API
OpenRouter
TrueFoundry AI Gateway
VoidLLM
ZenMux
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.
SecondStack gives an entire organization access to AI without handing its data to third-party clouds.
The platform ships three end-user workspaces โ Chat for everyday work, Code for engineering teams, and Agent for automation โ running on top of an enterprise LLM gateway that connects to the model providers you choose (OpenAI, Anthropic, Google, and others). Platform and security teams manage everything centrally: who can use which models, what each team spends, and where data lives โ inside your own infrastructure.
Because SecondStack is self-hosted, prompts, files, and knowledge bases never leave your environment. For teams that prefer not to operate it themselves, a managed deployment run by the SecondStack team is also available.
Pricing is not per-seat, so rolling AI out to the whole company does not multiply the bill. Deployment and operations are backed by an ISO 27001-certified implementation partner.
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Based on our record, Langfuse seems to be more popular. 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.
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 / 24 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 / about 1 month 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 2 months 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 2 months 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 / 2 months ago
Helicone AI - Open-source LLM Observability for Developers
liteLLM - One library to standardize all LLM APIs
LangSmith - Build and deploy LLM applications with confidence
Portkey - Build production-grade & reliable AI apps with Portkey
LangChain - Framework for building applications with LLMs through composability
Merlin Unified API - One Super API for all AI models (with 90% less error rates)
