Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
LastMile AI
BugHerd
Marker.io
Usersnap
Userback
Pastel
Bird Eats Bug
Bugasura
Bugfender
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.
BugHerd is the world's leading website feedback and bug-tracking tool. Globally, thousands of leading agencies and marketing teams love it for the ease and collaboration it brings to their website projects.
BugHerd has revolutionised the way agencies collect and manage website feedback from clients and internal teams. It is perfect for teams and individuals involved in website design and development. With BugHerd you can easily pin feedback directly to specific elements of the web pages. It acts as a transparent layer on the website that is visible only to you and your team. Submitted feedback and bugs are sent to a central Kanban task board that provides all stakeholders with full visibility of the project.
Get started in 3 easy steps:
STEP 1
Go to bugherd.com and click Start 14-day Free trial.ย
STEP 2
Sign up to create your first project. You can test BugHerd out on any website. It will only be visible to you.
STEP 3
And voila! You can start collecting feedback and invite others to try it out with you. Itโs that simple.
Langfuse BugHerdBugHerd is particularly recommended for web development teams, digital agencies, and product managers who are responsible for maintaining and improving websites. It is also a great fit for teams who work closely with clients and require an easy way to collect and manage client feedback directly in the context of the website in question.
Based on our record, Langfuse should be more popular than BugHerd. 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 / 13 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 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
Solutions like https://bugherd.com/ might make the issue context capture part more accurate. - Source: Hacker News / 4 months ago
This is a great idea, but scanning through appears to be basically https://bugherd.com/ ? Source: over 3 years ago
Competitors There are a few competitors out there that do something very similar (see https://ruttl.com/, https://usepastel.com/, https://bugherd.com/, https://www.markup.io/). This seems to suggest that there seems to be a general market for such a product. Source: over 3 years ago
Currently using BugHerd for web QA (love it) and looking for something similar for email. Source: over 3 years ago
Bugherd is good for this. Used it extensively when I worked for a web agency and it saved so much time. https://bugherd.com/. - Source: Hacker News / almost 4 years ago
Helicone AI - Open-source LLM Observability for Developers
Marker.io - Visual feedback and bug reporting tool for websites
LangSmith - Build and deploy LLM applications with confidence
Usersnap - Usersnap is a customer feedback software for SaaS companies that need to constantly improve and grow their products.
LangChain - Framework for building applications with LLMs through composability
Userback - Userback empowers product teams to collect, understand, and act on user feedback with unprecedented speed and clarity.