Adding AI to the Web Scraping Tech Stack

Adding AI to the Web Scraping Tech Stack

Web data providers recognize that they can use AI to help scale web scraping. Writing and maintaining manual code are scalability killers. AI is effective for helping teams scale up the creation and maintenance of web crawlers and extractors making it easier to add new sources to solve additional business cases. 

Zyte and other vendors have made it easy for companies to benefit from all the AI research without having to make a capital investment. They’ve incorporated machine learning (ML) and large language models (LLM) into their web scraping tech stacks and products.

LLMs have their place in a web scraping stack. They shine when used to gather the insightful but hard to scrape data buried in the unstructured text of a website. It’s best to use a traditional web scraping stack to collect the unstructured data from the website and pass that data to the LLM to extract the additional data points. 

Incorporating LLMs into your own web scraping stack raises additional concerns. LLMs are too costly to run as a complete web scraping solution. Additional QA is critical as LLMs can hallucinate. A robust process for testing and correcting errors is needed. Extra scrutiny for legal compliance is needed when incorporating third-party AI systems into your stack to protect your and your client’s data. For example, you want to prevent the third-party AI system from using your data to train their models.

⚡ Tip 4: Use Zyte API’s AI Scraping to take advantage of AI without the capital investment

LLMs are general systems and aren’t built to be a complete web scraping solution and require substantial processing power to run. Using them in most situations isn’t cost-effective when traditional methods are cheaper. Also, LLMs in web scraping must integrate into other solutions for website bans and rendering. 

However, generative AI doesn’t have to be a massive expense in your scaling project — outsource it to a third-party vendor.

Zyte API uses a supervised ML model built for extracting structured data and it’s 

• 50x cheaper,

• more accurate than larger LLMs,

• highly accurate because it uses a human-in-the-loop to correct site-specific issues and retrain the model on specific edge cases.

Zyte API AI Scraping extracts data into legally compliant schemas without the time-intensive task of writing and rewriting xpaths or selectors. We taught our model to find structured data without coding the instructions, making it quick and unbreakable. Want to gather data in the unstructured text too? Zyte API can integrate with your LLM of choice.

Continue to the next chapter 6. The In-house vs outsourced question