Improving Chatbot Builder with AI Agents

Dataforest developed a solution that enables chatbot builder users to upload a file containing information about their industry, products or services, and target audience. This data is then used for model training, allowing chatbot owners to create a chatbot customized to their specific business needs and characteristics.

Developed a scalable AI solution featuring robust machine learning algorithms and natural language processing capabilities. Leveraged the LLM approach using the latest ChatGPT model. Additionally, implemented an efficient caching mechanism and Retrieval Augmented Generation (RAG) to ensure timely and accurate communication of companies’ information.

They support all three languages, generate predefined messages, and deliver high-quality dialogues. We use the language classification of customer messages to ensure that the response will be in the relevant language from the list of supported languages: Portuguese, English, and Spanish.

• Dataforest developed a solution that utilizes Qdrant to cache users’ messages and responses. This speeds up responses to frequently asked questions by reusing stored information, while also reducing costs of LLM services.

‍

• Dataforest created a solution architecture incorporating LLMs assigned specific tasks based on user inquiries. Utilizing the AI agent GPT-3.5-turbo, it categorizes user intents and directs them across different chatbots to achieve their objectives.

‍

• The solution uses the Haiku model to generate pre-written messages for common scenarios such as greetings and responses to irrelevant questions.