notte's answer

Notte is built with Python and accessible via Python SDK or REST API. It performs deep DOM parsing and uses a semantic abstraction layer informed by graph-based reasoning — though the graph itself isn’t fully materialised in code. The SDK exposes a clean interface for LLM integration.

ScrapeOps's answer:

Python, Node.js, FastAPI, PostgreSQL, Redis, Docker, Kubernetes, Playwright, Selenium, BeautifulSoup, Puppeteer, React, TypeScript, AWS Cloud Infrastructure, OpenRouter for AI Models

notte's answer

Notte is purpose-built for LLM agents. It doesn’t just click DOM elements — it understands the intent behind them. That means faster, more reliable agents, no brittle scripts, and seamless integration via API or SDK. It replaces scraping + Playwright stacks with one clean abstraction layer.

ScrapeOps's answer:

Most scraping platforms focus on either infrastructure or extraction APIs. ScrapeOps combines both. Developers get proxies, anti-bot tools, monitoring, scheduling, debugging tools, prebuilt scraper examples, and AI-assisted scraper generation in one platform. We prioritize transparency and ownership, so developers receive code they can inspect, modify, and deploy within their own workflows instead of being locked into a proprietary extraction system.

notte's answer

Notte turns the web into structured, semantic maps tailored for LLMs — enabling perception, navigation, and action. Unlike traditional browser automation, Notte abstracts away fragile HTML into high-level actions and natural language descriptions, reducing hallucinations, tokens, and latency.

ScrapeOps's answer:

ScrapeOps helps developers build and operate web scrapers faster. Unlike many AI scraping tools that act as black boxes, ScrapeOps focuses on developer-first workflows with inspectable code, proxy infrastructure, monitoring, scheduling, and AI-powered scraper generation. Our newest product, ScrapeOps AI Scraper Generator, uses a schema-based approach to generate scraper code and then AI scores how correctly the scraper ran, helping developers understand output quality before using the data.

notte's answer

Developers building LLM agents, automation workflows, or AI-native applications. Early adopters in infra, QA, RPA, and AI tooling who want to go beyond brittle web scraping and fragile automation toward agentic, semantic control of the internet.

ScrapeOps's answer:

ScrapeOps is built for developers, data engineers, startups, SaaS companies, AI teams, researchers, and businesses that rely on web data. Typical users include teams building price monitoring tools, lead generation systems, market intelligence platforms, ecommerce analytics products, AI training pipelines, and large-scale web scraping infrastructure.

notte's answer

Notte was founded by Andrea and Lucas, two ML researchers who met at EPFL in 2019 and have been building together ever since. After working across top research labs, they saw a clear gap: existing browser automation tools weren’t built for LLMs. Notte is their response — a framework that makes the web usable for agents through structured, semantic understanding. It’s designed to bridge research and real-world execution.

ScrapeOps's answer:

ScrapeOps started after seeing how much time developers spend rebuilding the same scraping infrastructure over and over again. Building a scraper is only a small part of the challenge. Keeping it running through site changes, JavaScript rendering, anti-bot systems, proxy failures, and data quality issues is where most teams struggle. ScrapeOps was created to reduce that operational burden and help developers get from idea to reliable production scraping faster.

ScrapeOps's answer:

Thousands of developers worldwide, SaaS companies, Ecommerce intelligence platforms, Market research firms, Lead generation businesses, AI and machine learning teams, Data engineering teams, Digital agencies, Startup founders, Enterprise web data teams