At Reworkd, we're working on multimodal LLM agents that serve as the simplest way to extract web data at scale. Customers come to us with lists of 100s to 1000s of websites along with a data schema. Our agents traverse these websites, understand their structure, and generate code to extract data from them. We've been working on LLM agents since their inception and have received over 30k stars on GitHub and 1M+ users across previous agent products. If you're interested in our pilot program, shoot us an email!
Software engineer and open source enthusiast. Also a co-founder @ Reworkd AI
Co-founder @ Reworkd AI. Combined major in Science @ UBC. Previously worked at STEMCELL Technologies
Co-Founder & CTO of Reworkd AI - Pushing the boundaries of AGI agents. Deeply passionate about open-source, software architecture, engineering leadership, and emojis 🚀😀
Collecting, monitoring, and maintaining a web data pipeline can be complex and time-consuming, especially at scale. Traditional methods often struggle with issues such as pagination, dynamic content, bot detection, and site changes, all of which can compromise data quality and availability.
To address web data needs, businesses are often faced with either building out an internal engineering team or outsourcing to a low-cost country. The former can be expensive, while the latter is often unsustainable and requires significant management oversight.
Recognizing the inefficiencies of traditional data collection methods, Reworkd was developed to simplify your web data pipeline. Simply provide us with a list of websites and the schema you want the data mapped to, and we will handle the rest.
At its core, Reworkd uses LLM code generation to enable companies to rapidly scale their extraction efforts across thousands of websites. Additionally, we offer: