DataGPT, a California-based startup, has emerged from stealth mode with the launch of its AI Analyst, a conversational chatbot designed to help teams understand their datasets by communicating in natural language. The AI tool combines a large language model with the analytics engine of DataGPT to provide relevant insights and answer questions about business data. DataGPT aims to simplify the consumption of insights from data, allowing anyone in a company to talk directly to their data. The software offers instant results and bridges the gap between rigid reports and informed decision-making. By using generative AI, DataGPT enables users to have a conversational experience with their data and obtain prompt, clear answers to essential business questions.
DataGPT’s AI analyst works by setting up a use case for a specific area of business or predefined key performance indicators (KPIs). Users can then interact with the AI analyst through a chatbot or a more traditional interface and access visualizations and key metrics. The backend of DataGPT involves three layers: a data store, a core analytics engine, and an analyst agent powered by a large language model. When a user asks a question, the analytics engine analyzes the data, computes impacts and statistical tests, and retrieves the results in a conversational format.
The benefits of using DataGPT include accelerating time to insights, making critical business decisions more quickly, and saving analysts’ time for more pressing tasks. DataGPT’s lightning cache database is faster than traditional databases and can run queries much faster than standard business intelligence tools, while reducing analysis costs. These attainable insights can unlock up to 15% revenue growth for businesses and free up time for busy data teams. DataGPT plans to open source its database in the future.
DataGPT has raised $10 million in funding and currently covers 80% of data-related questions. The company plans to expand its capabilities to cover cohort analysis, forecasting, and predictive analysis. This expansion could give DataGPT an edge in a market where many vendors are incorporating generative AI into their data analytics offerings. DataGPT differentiates itself with its analytical engine, which combines contextual comprehension with logical analysis and interpretation.
As the market for data analytics continues to evolve, DataGPT aims to provide a new data experience that combines the power of a large language model with advanced analytics. The company believes that its approach sets it apart from other solutions that either lack depth of analysis or only offer narrow reports and dashboard outputs. By delivering a seamless and user-friendly experience, DataGPT empowers enterprise data leaders to gain valuable insights and make informed decisions.
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