How to build accurate data chatbot?

At C&F, we understand the business's current needs. We build solutions with more than 95% accuracy, using advanced techniques and a knowledge base built accordingly. This includes information about the data's structure, sample questions from users, additional information about definitions and concepts used by users, and finally, information about accepted data conventions and ways of coding information.

KPI calculations

Calculating various metrics, specific to the dataset, is an important data chatbot skill. Make the chatbot recognize KPI definitions written by users and apply them in SQL queries, so that users can easy get information they need. This will enhance end user experience with the chatbot.

Explain query

Give the chatbot functionality, to show the actual SQL query executed by the chatbot to pull the data. This will let advanced users investigate the actual SQL query and give the bot additional instructions, if needed. Additionally, let the chatbot explain and paraphrase the SQL in natural language when providing the response. This will build additional confidence with the solution for less tech savvy users.

Advanced domain-knowledge ingestion

Multiple types of domain knowledge like data metamodel, commonly used business terms, data coding, are used to control chatbot’s understanding, correct mistakes, and give persistent instructions. Because LLM models are trained on general knowledge, but don’t have specific corporate domain knowledge, this information needs to be provided externally when designing the chatbot solution.

Integrating with organization’s infrastructure and compliance regulations

Meet all internal regulations, use only audited models, control user’s access. Data chatbots are no different from other corporate applications and should meet the same requirements.

Conversational interfaces deliver the best possible experience for business users to interact with data and are the future for making informed decisions in real-time. Combined with graphical visualizations, data chatbots provide easy access to data stored in the database and perform data analysis and visualization on the fly.

Overview

Data Chatbots can help improve user interactions with data by performing real-time data analysis and visualizations. Powered by natural language processing, machine learning, and artificial intelligence, our AI chatbots leverage generative AI tools and use many data points to provide accurate relevant information. They are designed to understand your business’s unique needs, with custom solutions tailored to be relevant with your organization, including sample questions from users, information about the data’s structure, and information about accepted data conventions and ways to code information. By integrating an AI chatbot with your organization’s infrastructure, you can make it easier for users to interact with data and make informed decisions in real-time.

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