Personalized AI Knowledge Assistants — Chatbots for the Enterprise
If you’re a CTO, CIO, ML engineer, or simply interested in technology like chatGPT and LLMs, you may be curious about where it’s headed next, especially as it relates to training your data.
The recent acquisition of MosaicML by Databricks for a whopping $1.3 billion highlights the increasing significance of AI in the enterprise industry. As a result, the question arises: will personal AI knowledge assistants become more prevalent? Our team believes so. In this article, we’ll share our background and provide guidance on training your data and creating your own customized AI-based knowledge assistants (chatbots).
We have been working in this field since December 2019 and currently have two pending patents on personal knowledge assistants. During the summer of 2022, we incorporated chat into our product using a Roberta model months before chatGPT. This was the beginning of numerous versions that eventually led to bundleIQ’s conversational AI, ALANI.
Our goal is to assist individuals and businesses in comprehending and utilizing the vast amounts of information available to them. By transforming data into a conversational AI-powered knowledge base, we enable them to unlock its full potential. McKinsey’s research indicates that data is currently being underutilized, and we aim to address this issue.
Data is not being effectively used by organizations today due to sporadic applications, legacy technology limitations, manual data organization, and siloed environments. These challenges hinder organizations from fully leveraging the value of data and making data-driven decisions. However, there are steps that organizations can take to overcome these challenges and use data more effectively, such as upskilling employees, adopting cloud-enabled data platforms, and treating data as a product.
We set out to provide a smooth and effortless conversational AI/chat experience for all our users, be it individuals or companies, while keeping in mind the challenges posed by data management. To achieve this, we’ve simplified the process of collecting information from both internal and external sources. Our approach involves using different methods such as API import, web clipping, and custom uploads, all integrated into the web application. With our intelligent processing methods, we’ve eliminated the necessity for complex machine-learning pipelines.
Click here to get access to our enterprise beta.
Creating customized knowledge bases and extracting specialized insights is now just a few clicks away. Companies don’t have to worry about coding, connecting with Python libraries, or developing plugins. With bundleIQ Enterprise, you can enjoy a comprehensive and secure turnkey solution that can easily scale to meet your needs.
Want to see a demo? Click here to schedule a meeting.
