BBI Brandboost’s AI bot development process is broken down into several key phases. First, we begin by analysing the blueprint of the AI bot, which includes dissecting the bot’s intended use, creating user profiles, and ensuring a design that specifically caters to the needs and behaviors of the target audience.
Next, we move on to narrating problem stories, which involves anticipating challenges and queries that the AI bot may face, and laying a solid foundation to ensure the bot is well-equipped to handle real-world scenarios. BBI Brandboost also gathers knowledge by collecting information from various sources such as Excel spreadsheets, Word documents, and web pages to empower the AI bot with extensive information.
Once we have gathered this information, BBI Brandboost moves on to selecting the right LLM, or Large Language Model. We choose the LLM by evaluating models based on their strengths and considering cost-effectiveness to align with the client’s budget. Then, we train the LLM by importing data in a vector format, which is then processed by the LLM.
Following the training phase, BBI Brandboost focuses on efficient data management to ensure tailored information access for different user types. We then deploy the AI bot onto web or mobile platforms through a customizable widget, and integrate it seamlessly to enrich the user experience.
The final step in BBI Brandboost’s AI bot development process involves continuous refinement and management. This includes ongoing evaluation to constantly refine the bot, identify knowledge gaps and areas for improvement, and ensure it evolves dynamically. User feedback is also integrated throughout this process to understand interactions and allow the bot to continually evolve and meet user needs more effectively.