The LLM powered scraper for LLM Apps
No need to manually tune your scraper for individual websites and apps, NeroBot analyzes webpages like a human engineer for optimal structured outputs.
What makes us different
NeroBot reads webpages like a human by using power full LLMs like ChatGPT so you get clean structured text for all your favorite sources.
Clean text for embeddings
If you have worked with embeddings, you know the importance of clean text for your chunks. NeroBot automates extraction so you always get only the article content, no mess.
Structured markdown for inference
Get the most from your datasources with our AI-extracted HTML that is perfect for providing tables in markdown to your LLM prompts.
Metadata Extraction
Automatically get categories and other metadata to use for metadata filtering for large enterprise vector stores, a proven technique for optimizing similarity searches.
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A crawler that just works, no setup required.
Efficient crawling, backed by auto-configured proxies and enhanced with real-time page rendering optimization.
Advanced Anti-bot
Our browser technology mimics traditional users by using finger printing and proxy networks and captcha solving to avoid anti bot measures.
Browser Vision
Automatic JS rendering when required keeps your crawler moving as fast as possible while ensuring the page loads your desired content.
Automated Page Processing
Simply set your preferences – whether it’s filtering out search results or more – and let our system handle the intricacies. Zero stress, maximum results.
Fully automated features
We built the entire platform from the ground up using the latest LLMs and AI tools, enabling a completely turn-key suite of web extraction tools.
Extract
Clean text, HTML, and metadata for documentation, knowledge bases, and news.
Crawl
Strategic crawler looks for sitemap to get optimal results with minimal user input.
Enrich
Arbitrary insights and answers on your leads database, perfect for salesforces.
Open API Spec
Built to standard specifications making it easy to integrate to any tech stack.
Multi-language
Select your target languages to ensure no duplicate pages are processed.
Usage based billing
Pay for what you use, easily scale up/down without worrying about managing servers.
Crawling and parsing is simple with an AI Assistant.
Integrated with all the tools you already know and love
Frequently found problems
Throughout our development of LLM powered applications we have found frequent problems voiced from the community.
My crawler is getting blocked
Web crawlers often face restrictions and blocks due to website security protocols and bot management solutions. Navigating through these barriers while respecting site regulations and ensuring data integrity is a significant challenge.
Tables not interpretable by ChatGPT
The extraction and comprehension of tabulated data are crucial for detailed analysis. However, making these tables interpretable by machine learning models like GPT models is a challenge due to format inconsistencies and complex structures.
Parser is not generalizing
Creating a parser that effectively handles a variety of formats, structures, and content types is challenging. Many parsers are specialized, leading to a lack of generalization and adaptability, which is essential for processing diverse web content.
Poor results for large vector databases
As the volume of data increases, achieving accurate and speedy search results becomes a challenge. Large vector databases require optimized handling and processing to ensure that search results are not only accurate but are delivered in a timely manner.
How can I leverage metadata for search
Metadata enhances the searchability and accessibility of data but leveraging it effectively can be a hurdle. Ensuring it’s comprehensive, accurate, and consistently formatted is essential to optimize search results and deliver precise, valuable insights.
My scraper is returning navigation items
Web scrapers occasionally retrieve non-target data such as navigation items, ads, or other unrelated content. This can result in a cluttered and inefficient data extraction process, requiring additional cleaning and filtering steps.
Perfect for LLM Apps and AI Agents
