AI should automate tedious and un-creative work, and data entry tasks definitely fit this description. Rule-based RPA will likely be replaced by fine-tuned AI agents for things like form filling and similar.
Can you share some data on costs and scalability?
At Kadoa, we're working on fully automating unstructured data ETL from websites, PDFs, etc. We quickly realized that doing this for a few data sources with low complexity is one thing, doing it for thousands of sources daily in a reliable, scalable, and cost-efficient way is a whole different beast.
Using LLMs for every data extraction would be way too expensive and very slow. Instead, we use LLMs to generate the scraper and data transformation code and subsequently adapt it to website changes, which is highly efficient.
We're trying our best not to move into the web scraping space -- we're focusing on automating uncreative, boring, tedious tasks.
We've seen a lot of success going after form-filling on government websites, which would usually be very boring, but happens to work pretty well for us
Can you share some data on costs and scalability?
At Kadoa, we're working on fully automating unstructured data ETL from websites, PDFs, etc. We quickly realized that doing this for a few data sources with low complexity is one thing, doing it for thousands of sources daily in a reliable, scalable, and cost-efficient way is a whole different beast.
Using LLMs for every data extraction would be way too expensive and very slow. Instead, we use LLMs to generate the scraper and data transformation code and subsequently adapt it to website changes, which is highly efficient.