Chatbots are beneficial to enterprises in numerous ways. As technology evolves, we may see the...
Making ChatGPT Enterprise-Ready with Enterprise Bot: Key Features for Secure and Efficient Automation
ChatGPT has transformed the way businesses interact with their customers and handle routine tasks. However, the increasing popularity of it has also raised concerns about privacy, security, and control. Enterprises need a conversational AI / Chatbot that can meet their specific requirements and protect their confidential information.
ChatGPT does a great job on listing the main concerns by itself :) but that doesn't mean we cannot make it Enterprise ready.
We have been working on solving exactly some of these problems while leveraging the power of one of the most powerful language models of our time. Our goal was to offer a solution to make GPT-3 and ChatGPT, the advanced language model developed by OpenAI, enterprise-ready.
In this article, we will discuss how Enterprise Bot enables ChatGPT to meet the specific needs of enterprises by focusing on four key features.
- Lack of Personalization and limited understanding of Context: Enterprise Bot unlike ChatGPT connects with enterprise core system. This allows it to be aware of the customer, their needs and preferences. This understanding is fed to ChatGPT to ensure that it becomes more contextually aware and transforming the response quality.
- Bias and response restrictions: ChatGPT is trained on general data and does not restrict its responses to an enterprise’s dataset. This limitation can open an enterprise to risks. To mitigate this Enterprise Bot leverages its patent pending technology DocBrain to offer a feature that restricts the responses of ChatGPT to the information provided by the company via documents or its website. This ensures that the information provided by the bot is relevant and accurate and prevents it from accessing information from other sources that either are not relevant or not compliant with the company’s requirement.
Here is the link to Azure OpenAI documentation, which provides more information on the data retention policy that is better suited for enterprise use compared to using the OpenAPIs without Azure.
- Maintenance and updates: ChatGPT is trained with data up to 2021. This means that for all the newer products and data, it presently does not have that information. As Enterprise Bot's DocBrain has information about your website and other knowledgebases that are updated daily, it can provide the right context and information to ChatGPT to ensure it provides accurate answers to your customers.
- Reference Links for Auditing: Auditability is critical for enterprises to ensure that not only is the information provided but it was accurate and to understand where the information came from. Enterprise Bot includes reference links to audit the source of the information provided by ChatGPT. This enables enterprises to track the origin of the information and verify its accuracy, which is particularly important when dealing with sensitive information.
- Integration with existing systems allowing automation: Enterprise Bot also offers additional automation options, such as task automation and workflow management, to enhance the functionality of ChatGPT. This enables the chatbot to not only respond to user requests but also to complete them. This is essential for good CX and delight. For example, if a customer asks to block their credit card, they want to be able to immediately do so and not just get an answer on how they can do this by following some complicated steps. By combining ChatGPT with Enterprise Bot you can do exactly these functions.
In conclusion, if you are looking at deploying ChatGPT, Google’s Bard or similar LLM models speak to us and we can make the journey much more secure, compliant and faster.