Building an NLP legal clause rewriter that improves clause clarity and reduces risk | Case Study
How we leveraged large language models to build a legal clause rewriting pipeline that generates stronger language and more clarity in legal clauses
Width.ai helps warehouses and other inventory storing businesses automate out and optimize huge chunks of their entire business process (yes entire, seriously, we’ve seen 22%+ easy) by building custom software solutions for warehouse automation that use machine learning and computer vision. One of the most important parts of growing your inventory business is being able to scale efficiently and optimize your warehouse space to store your cash-growing asset (inventory). These automations allow you to completely remove these hours from your inventory cycle, making you insanely profitable. There are several tools we use that help companies build these automation systems that you must have in 2020 if you are serious about scaling your warehouse or inventory and automating your business.
In terms of automation, this python library is going to be one that you turn to quite a bit. With the large increase in robotics in warehousing, computer vision is becoming one of the most important tools needed. No matter who is on the floor managing inventory, man or robot, you need a way to quickly read labels and barcodes to pass data and information to backend systems, or to alert suppliers of what product you’ve received and which orders are finished. The robust nature of OpenCV allows you to solve much trickier computer vision problems in the warehouse, like custom labels and lots of SKUs, and gives you pretty in-depth functions that really allow you to customize your computer vision based reader. Personally we’ve seen this work really well with noisy labels that are hard for other libraries and tools to extract the information needed. As upstream product manufacturers change the label format, move barcodes and remove fields, your label reading system adjusts and learns the new formats. If you’re a company that has large inventory or a warehouse looking to add computer vision to your arsenal, OpenCV is a great place to start.
Most custom automation solutions built for warehousing, especially machine learning and computer vision based ones, can become quite large and difficult to run as they scale in size (both the warehouse and the system). What you’ll find is that the normal office computer running your backend system will start to struggle and slow down your now newly built warehouse automation systems. Most of the time, moving to amazon web services to manage your software becomes the best route to take, given how inexpensive it is to run incredibly robust warehouse automation software solutions. You never want to take the chance you can’t complete an order on time or can’t instruct a robot what to do because your system can’t finish its run for you. Most of these tools being used in your automation are too powerful for a normal computer to run in a quick manner, and having dedicated servers in AWS is a great way to outsource these tools so you can continue on without seeing the effects. Most of the time you can set up your AWS configuration to only spend when it needs to, and keep a super cheap baseline the rest of the time. The custom nature of what a development company or firm will build means they will be more inclined to set up AWS to run your system, over a company that sells software as a bundled product.
For creating almost any long term automated warehouse solutions, being able to predict and forecast your current and future inventory levels is as important as it sounds. Eliminating inventory shortages and understanding what causes surplus is a vital part of any automation or warehouse optimization solution and can give you seriously profitable results within the first hour it’s built. Facebook Prophet is a time-series forecasting model that lets you do exactly what’s described above, gives you forecasting on where your inventory levels will be, and always adjusts to new data to allow you to be super precise with when you need to restock. We’ve taken this tool in the past and used it to give even deeper insights into inventory, allowing you to predict holiday season sales, least profitable products over an upcoming year, profitability of each square inch of inventory and so many more. The reason I put this after AWS is for a very specific reason. AWS will allow you to collect lots of data and give you a place to store it, which is needed for to give these predictions in the forecasting model.
One of the most important parts of most warehouse automation solutions is having the ability to automate decision making. Once you’ve got your warehouse data analytics and inventory information on the current status of everything related to your business, it's time to see the effects of true deep analytics kick in. Decision trees allow you to make calculated, smart decisions based on the information you’ve already collected, like a last step in a fully automated warehouse system. There are plenty of libraries that offer decision trees, my favorite being scikit learn, and lots of different versions of them for you to test out and find the best solution for your business. If you plan on using multiple ai models and tools to do a bunch of tasks in your warehouse, using some form of decision trees is a great way to help make your final decisions with the new ai analysis.
Note: Partially automated warehouse systems might not always need decision trees as being part of a final step, mostly when a user still has to input.
While your automation journey might not need these specific tools, and will probably require way more than just these libraries. It’s good to understand the most common things that are being used in your custom ai system and why they are there. And while there's many more things you will need, and we didn’t even discuss floor spacing optimization or much around that. These are the beginner tools needed to start moving to a fully automated warehouse system. I definitely suggest taking a look at this inventory management case study to understand how flexible these libraries are for anything related to building warehouse automation solutions
Are you a business that has a few warehouses or complex inventory that's hard to keep track of? Want a solution that’s completely customized for you, not some giant corporate solution that costs a fortune?
Do what other businesses do: https://www.width.ai/#contact
Let’s talk about showing you our custom warehouse automation systems!
A little bit about Width.ai:
We are a machine learning and data science consulting firm focused completely on building business tools to increase profitability for clients. We specialize in natural language and computer vision systems that allow us to build software solutions for warehouse automation and other sectors of business.
How we leveraged large language models to build a legal clause rewriting pipeline that generates stronger language and more clarity in legal clauses
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