Digest, a product by Fahamu AI, is an innovative solution designed to simplify the process of finding specific information from document archives and databases. It is particularly beneficial for knowledge workers like lawyers, scientific researchers, manufacturers, and individuals working in NGOs who deal with a lot of documentation and data on a regular basis.
Key Features:
A) Ask Questions About Your Documents: Digest allows users to ask questions about their documents and performs tasks with AI. This feature makes it easy to find specific information without having to manually search through each document.
B) Single Access Point: Digest provides a single access point for all information, eliminating the need for users to know where the information is located. This feature significantly reduces the time and effort required to find information.
C) AI-Powered Answers: Users simply need to ask a question about what they want to know, and if the information is contained in the data, they receive the answer along with information about the sources for the answer. This AI-powered feature makes Digest a highly efficient and user-friendly tool.
As someone who hasn't tried the product yet, I'm intrigued by its potential to revolutionize the way we manage and interact with documents. It seems like a promising tool that could save a lot of time and effort for individuals and organizations dealing with large volumes of documents and data.
However, I have a few questions to understand the product more:
1- How does Digest handle the privacy and security of the documents and data it processes?
2- Can Digest integrate with other document management systems or cloud storage platforms?
3- How does the AI in Digest understand and interpret the context of the questions asked by the users?
Thank you very much for your review and questions, Deniz.
1. Privacy: Our system is private by design, meaning that We are not training any models on user data. When requested to, we train only on that specific client's data, ensuring that no data mixing occurs.
2. We already cater for more than 20 data types and are working on integrating Dropbox, MS Sharepoint, Drive, Amazon S3 and Azure Blob Storage.
3. We use search to find the most relevant context from the user's data source, and the AI answers questions based on that context. See this talk by myself on the kinds of challenges one can encounter when using search in this way, and how to resolve some of them: https://youtu.be/qwQ-H61g2Ec
