Common AI scrapers/crawlers in the market are redundantly inefficient and expensive. Strategy: 1. Reduce AI dependency for html parsing, by sampling multiple html docs to build custom parsers that is self healing. 2. Use AI in analyzing webpages to figure most efficient way to scrape. This leads to: 1. Cheaper, Cleaner and Faster processing. 2. No hallucinations. 3. Better token economics. Unique offering: 1. Infinite concurrency. 2. PAYG for users. 3. Result storage and API retrieval.
Hey guys! I'm building Wraith Bytes because using external tools like FireCrawl which are all very expensive also I keep running into situations where my LLMs run out of context easily during research and start hallucinating because of too much noise in the data, also my inability to instantly retrieve 100s of pages simultaneously due to rate limits.
Let me know what you guys think, I appreciate all feedback! Thank you.
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