Langfuse
Helicone AI
LangSmith
LangChain
Braintrust.dev
Openlayer
PromptLayer
Portkey
dataprep.dev
Microsoft Office Excel
Google Sheets
Airtable
Apache OpenOffice Calc
Apple Numbers
Pyspread
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.
dataprep.dev is a 100% local, pure-browser data processing engine designed to solve the biggest headaches in data preparation: Excel crashes and privacy risks.
Powered by cutting-edge DuckDB-Wasm technology, our toolkit brings database-level performance directly into your browser tab. Your data never leaves your device. No servers, no uploads, no GDPR headaches.
Stop fighting with bloated spreadsheet software. Clean locally, analyze anywhere.
Langfuse dataprep.devdataprep.dev's answer:
I was trying to clean up a massive, messy Shopify order export. Excel kept freezing, and I absolutely refused to upload sensitive customer emails to random online converters. I got so frustrated that I decided to stop complaining and build a local-first toolkit to solve my own workflow nightmare.
dataprep.dev's answer:
1, Indie hackers and solo founders. 2, Boutique digital marketing agencies. 3, Privacy-conscious data freelancers.
dataprep.dev's answer:
Most data tools force you to upload your CSVs to their servers. We don't. We compiled DuckDB into WebAssembly, meaning you get a blazing-fast, database-level engine running entirely inside your local browser tab. It's 100% private and works instantly.
dataprep.dev's answer:
If you try to open a 2GB CSV in Excel, it freezes and crashes. If you use Python Pandas, you have to write code and manage environments. dataprep.dev gives you the power of code (SQL queries, regex, merging 50 files) with a simple drag-and-drop UI, without ever freezing your computer.
dataprep.dev's answer:
E-commerce sellers flattening messy Shopify exports, performance marketers cleaning ad reports, and data analysts who need to anonymize PII (GDPR compliance) before feeding datasets to AI models like ChatGPT.
dataprep.dev's answer:
DuckDB-Wasm is the core data engine handling the heavy lifting. The frontend is built with React/Next.js and styled with Tailwind CSS. It's a modern, serverless architecture.
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 / 29 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 2 months 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
Microsoft Office Excel - Microsoft Office Excel is a commercial spreadsheet application.
LangSmith - Build and deploy LLM applications with confidence
Google Sheets - Synchronizing, online-based word processor, part of Google Drive.
LangChain - Framework for building applications with LLMs through composability
Airtable - Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.