LLM-ready Web Search and Extraction
Web search and extraction toolkit for reliable grounding in LLM applications.
- C#
- .NET
- Web Extraction
- Search
- LLM Grounding
- HTML Parsing
The Challenge
LLM applications only produce reliable results when they can work with current and traceable sources. Traditional web scraping is often not enough: content needs to be found, extracted, cleaned, and delivered in a format language models can use.
The Solution
web-explorer combines web search, extraction, and normalization into a toolkit for LLM grounding. The focus is reliable information retrieval and clean handoff into AI workflows.
Architecture Highlights
- Search and extraction: Web pages are not only fetched, but processed for usable information.
- LLM-ready output: Content is normalized so it can be passed into AI pipelines.
- Robust web automation: The project builds on deep experience with HTTP automation, HTML parsing, and data quality.
- Grounding focus: Source-based answers are supported technically instead of only encouraged through prompting.
The Result
The project modernizes classic web scraping expertise for the AI context. It shows how web data can become reliable context for LLM systems.