Simple Scraper VS Langfuse
Compare Simple Scraper VS Langfuse and see what are their differences
A simple way to keep all your data under control. Build your own business applications in just 4 minutes.
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Simple Scraper
Octoparse
Diggernaut
Scraper API
Agenty
eScraper
Crawlbase
artoo.js
Langfuse
Helicone AI
LangSmith
LangChain
Braintrust.dev
Portkey
Openlayer
PromptLayer
Simple scraper is the easiest way to scrape the web โ turn any website into an API in seconds and use ready-made scraping recipes to scrape popular sites with ease.
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.
Simple Scraper LangfuseLangfuse might be a bit more popular than Simple Scraper. We know about 28 links to it since March 2021 and only 22 links to Simple Scraper. 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.
Data extraction: https://simplescraper.io A project that I launched on HN that became a business. Simplescraper rode the no-code wave of a few years back ('instant structured data without parsing html'). Now working on increasing the surface area for AI agents: MCP support, screenshots API, and (experimentally) x402^ ^ https://simplescraper.io/blog/x402-payment-protocol/. - Source: Hacker News / 5 months ago
1. Clicking the box programmatically โ possible but inconsistent 2. Outsourcing the task to one of the many CAPTCHA-solving services (2Captcha etc) โ better 3. Using a pool of reliable IP addresses so you don't encounter checkboxes or turnstiles โ best I run a web scraping startup (https://simplescraper.io) and this is usually the approach. It has become more difficult, and I think a lot of the AI crawlers are... - Source: Hacker News / about 1 year ago
Making my data extraction Saas (https://simplescraper.io) more LLM friendly. Markdown extraction, improved Google search, workflows - search for this terms, visit the first N links, summarize etc. Big demand for (or rather, expectation of) this lately. - Source: Hacker News / almost 2 years ago
Things are much easier for one-person startups these daysโit's a gift. I remember building a todo app as my first SaaS project, and choosing something called Stormpath for authentication. It subsequently shut down, forcing me to do a last-minute migration from a hostel in Japan using Nitrous Cloud IDE (which also shut down). Just pain upon pain.[1] Now, you can just pick a full-stack cloud service and run with it.... - Source: Hacker News / about 2 years ago
Simplescraper โ Trigger your webhook after each operation. The free plan includes 100 cloud scrape credits. - Source: dev.to / over 2 years 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 / about 1 month 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 / 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 / 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 / 3 months ago
Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.
Helicone AI - Open-source LLM Observability for Developers
Diggernaut - Web scraping is just became easy. Extract any website content and turn it into datasets. No programming skills required.
LangSmith - Build and deploy LLM applications with confidence
Scraper API - Scale Data Collection with a Simple API.
LangChain - Framework for building applications with LLMs through composability