Sped up customer support response threefold and improved customer support satisfaction.

• ChallengeAutomated round-the-clock personalized client support with decreased operational costs
• SolutionPrompt engineering of ChatGPT-4 model to build an AI conversational chatbot
• Technologies and toolsOpenAI (embedding, GPT-4), AWS (Lambda, S3, RDS+pgvector), SAM, CI/CD, CRM Pipedrive-API

Client

At InData Labs, we performed ChatGPT prompt engineering for our own website virtual assistant. As an AI & Big data service provider, we recognize the significance of quality customer support at any stage of the clients’ relationships and development process.

In search of an innovative tool to interact with our website visitors and potential clients in a more intelligent, personalized, and conversational manner, we opted for a ChatGPT-4 model and deployed it as a virtual website assistant.

InData Labs chose to implement the smart chatbot trained on the website data about the services of the company to achieve advanced conversational client support and generate more complex and nuanced automated responses.

Challenge: automated round-the-clock personalized client support with decreased operational costs

The InData Labs team was challenged with customizing the GPT-4 flow and integrating specific documents with use cases to build our own Conversational AI chatbot for business process automation and customer human-like interaction. The solution must handle more complex queries and provide personalized experiences based on collected data. It also should support the lead generation process by capturing and qualifying incoming leads.

GPT-3 already used 175 billion parameters to gauge the connections within contexts. At the same time, its successor GPT-4 has been upgraded to the extent that it can pass a simulated bar exam in the top 10%. InData Labs, a large language consulting company, was tasked with customizing the latest advanced GPT-4 model on the proprietary data to scale customer experiences and reduce bounce rate by offering personalized and convenient customer engagement.

Solution: prompt engineering of ChatGPT-4 model to build an AI conversational chatbot

The main objective of ChatGPT prompt engineering was to make customer service more flexible and personalized owing to the top-notch technologies of the 4th GPT model.

InData Labs customized the existing ChatGPT toolkit, vectorizing documents for use in ChatGPT to serve the business’s needs. Any business that is also looking for ways to scale up the company, automate Q&A processes, and decrease operational costs, should consider implementing GenAI solutions.

After performing thorough research, our team has built a ChatGPT-based virtual assistant with cutting-edge NLP technologies. The project was split into the following phases:

• Set up algorithms and install the necessary libraries
• Prompt engineering of GPT-4 (OpenAI) for specific chat flow
• Documents entities retrieve and vectorize for document search
• Integrating external services to chatbot: email sending, CRM Pipedrive system
• Preparing CI/CD process via SAM and deploying chatbot to AWS serverless architecture.