The potential of RAG - Practical use cases for your organisation.
If you are implementing RAG in your organization, but can’t think of many ways in which it can be useful, read on. 🤔🤔
One of the reasons is that you need genuine use cases that will add value to your users. The more such use cases you find, the more traction your solution will gain. ⭐
Let’s see how to find these use cases.
1️⃣ The first thing to do is to find the long and complex documents in your organization. There are some such documents that every organization has- contracts, RFPs, proposals and so on.
2️⃣ Then there are those documents that are specific to your organization or your domain. Here are some examples:
👉 Standards and specifications: your team designs a solution that has to comply with certain standards. Or they may have to refer to specifications of materials and components.
👉 Compliance notifications: Regulatory authorities in banking, telecommunication, insurance, equity markets etc issue notifications from time to time that your organization has to implement.
👉 Project reports: your teams create lengthy project reports and solution designs that are very useful, but are equally hard to read.
👉 Court judgements: you are a law firm. You have to go through the judgements of the courts and tribunals in your field.
Long and complex documents are good targets for RAG, as the users find it difficult to go through them. RAG makes it easy for the reader to ask questions on the document, but you have to give them a few more facilities. Let’s see a few examples.
🔸The users usually have a set of fixed questions. They do not like to repeat them every time. So you should provide a way in which predefined questions can be configured and the answers will be kept ready for the user after the document is ingested.
🔸Some of these questions may be dependent on the document. For example, commercial terms are important in a contract with a supplier, but they are not part of a non-disclosure agreement. This suggests that your system should learn about the document using some system prompts; and help the users to ask the right questions.
🔸One of the ways in which you can help the user is to create a relevant summary automatically. The users can read the summary before asking pertinent questions. You can also create a document map to further help the user.
🔷Another useful feature is comparing two documents. This is very useful for versions of the same document, such as contracts or specifications.
In the next post, we will see use cases for a set of documents.
🌱🌱🌱🌱💐🌱🌱🌱🌱🍁🌱🌱🌱🌱🌺🌱🌱🌱🌱🌻🌱🌱🌱🌱🌷🌱🌱
How do LLMs do all these things? I have explained in my book 📙‘Decoding GPT: an intuitive understanding of Large Language Models’📙
Amazon: https://amzn.to/3HNwbhG
By Devesh Rajadhyax
Co-Founder, Cere Labs
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