Artificial intelligence (AI) is becoming increasingly important for businesses seeking to automate and streamline their operations. One of the most promising areas of AI is natural language processing (NLP), which involves teaching machines to understand and respond to human language. One way that businesses can leverage NLP is by using a chatbot to automate customer service, deliver quick analytical facts and generate to answers that employees might take hours of work to ascertain.
Chatbots can help businesses to improve customer satisfaction, reduce operational costs, and increase revenue. However, building an effective chatbot requires significant expertise in NLP and machine learning. This is where CSL can help. By leveraging state-of-the-art AI frameworks like ChatGPT, CSL delivers enterprise AI solutions that provide powerful natural language processing capabilities for chatbots and other applications.
Here are some of the ways CSL uses ChatGPT to deliver enterprise AI solutions:
Pre-trained models: ChatGPT provides pre-trained models that can be fine-tuned for specific use cases. This enables us to leverage the power of NLP without building new models. A perfect example would be a chatbot that can understand and respond to questions from vendors, the data can be restricted to open purchase orders, history of service and open tickets.
Custom training: ChatGPT also allows developers to train their own models on custom datasets. This can be useful for businesses with unique language requirements or specialized use cases. For example, we can train the model to understand industry-specific jargon or technical language.
Integration: ChatGPT can be integrated with a wide range of programming languages and frameworks, making it easy for CSL to incorporate NLP capabilities into their existing applications. This allows businesses to use the power of AI without having to build entirely new systems from the ground up. Your custom software solution can leverage ChatGPT quite effectively to get analytical questions answered quickly, saving time and money. Quick answers to questions like “What month of the year do we get the maximum number of orders from Acme Sports?”
Continuous learning: ChatGPT can also be used to build chatbots that can learn from customer interactions. By analyzing customer interactions, the chatbot can identify patterns and trends that can be used to improve its performance over time.
Data porting into ChatGPT can be accomplished from various sources.
- Data from an RDBMS like Microsoft SQL Server, Oracle, or MySQL can be pushed into ChatGPT to create an environment exclusively used for Enterprise business analysis questions and potentially to run noncritical reporting functions.
- Data from big data platforms like Google Bigquery, Hadoop, MongoDB, and others can be seamlessly pushed into ChatGPT if the context is clear. This can again be used for analytical purposes.
- Data from archived business documents scanned OCR files, and images can also be pushed into ChatGPT for a holistic analysis of historical information.
Like all generative AI platforms, ChatGPT is experimental, we do not recommend usage in a critical business environment or a 100% reliance on the abilities of the AI platform to deliver accurate data. However, this can become a tool to speed things up, and get you information without a multi-step process.
ChatGPT provides a powerful platform for custom software developers to build enterprise AI solutions that leverage the power of natural language processing. By using pre-trained models, custom training, integration, and continuous learning, businesses can build chatbots and other applications that provide a seamless and intuitive experience for customers.
Our experience with custom software systems puts us in a unique position to leverage ChatGPT for new and existing software systems, we have a dedicated team that has experience with ChatGPT experimental technologies that can assist you in getting a head start on your journey with AI.
