Can you give a few examples, please?
Can you give a few examples, please?
A tool where you are given a picture/scan of a table and it spits out a table that can be pasted into Excel. This was at a bank where numerous people spent half their days manually typing in scanned documents into the same table in Excel. You would double a $70,000 a year financial analyst's productivity with this.
A portal to manage employee and employer documents. I.e where both you and your employer can easily access your T$ (Canadian tax form), offer letter, certifications, police checks, etc.
Software to manage which options a client ordered and what their selection was of that option as well as autogenerate the appropriate SQL queries from a client config template. The current process consisted of a mega word document with people fiddling around manually with it.
Happy to provide more.
Some of the scanned forms have marginal notes (probably okay to ignore these), but I've noticed some cases where the form had prefilled data crossed out with handwritten data replacing it.
Please let me know if a system exists that can deal with this idiosyncratic mess and coaxed to produce structured data of some sort without basically using MTurk behind the scenes. I would be interested in re-releasing the data into the public domain.
Our requirement was that the the software would need to read the number of separating lines in the table and output accordingly.
Maybe it can do this, idk. I was an intern at the time.
We were using tesseract for our attempt too.
Or said another way, it can be fun and also effective to "Do Things That Don't Scale" [http://paulgraham.com/ds.html].
The bottom line was that we were able to achieve very good results consistently, but the margin of error was not acceptable for our specific use case.
I worked with him to develop a Python script do basically automate half his job in a few hours that could have saved the company tens of thousands of dollars. The company didn't want to dedicate/hire an actual programmer to maintain it, so they kept paying employees to manually scrape the web.
The crazy part is the next summer he interned at a different company and literally the exact same thing happened. He re-made the original script, saved tons of work, and the new company still didn't end up using it after he left.
A manual process is robust, fault tolerant, and easy to adjust to new circumstances or changing business requirements.
A Python script is fixed, and they day it breaks down due to some slight change in scraped data, you have to pull in a developer to fix it. For a company without dedicated staff to support such automation, it is a high risk.
Ad-hoc automation can turn workflows into Rube Goldberg machines. A Python script here, an Excel macro there - soon nobody knows whats going on and nobody dares change anything.
Developers often think only one step ahead: It was manual, now it is automated with a script. Win! A business have to consider that larger picture - future support, maintainability, risk etc.
It may be lucrative for the friend to take the script and turn it into a product. but then they'll need to market, sell, document, optimize, and do a million other tasks.
There has always been a dead zone between "automated script that makes me work a bit more efficiently" and "product that can make everyone with this job work a bit more efficiently". Fortunately, new technology is narrowing this gap.
Managing attributes and taxonomies for ecommerce.
Capitalizable hour analysis for software projects.
That's just stuff from the last few weeks. None of these are hard to automate but the workflow integration is the tricky bit.
Also, what does "Capitalize hour analysis" mean?