Inside Talk2DB: From Natural Language Queries to Insightful Visualizations

In this online session, you’ll explore how SoftServe’s Talk2DB solution enables business users to access structured data using natural language and instantly transform it into meaningful visualizations and reports.

We’ll dive into how Talk2DB leverages large language models (LLMs) to interpret user prompts, generate dynamic dashboards, and integrate seamlessly with enterprise data systems. You’ll also learn how the visualization component supports real-time decision-making and enhances the value of conversational analytics.

Whether you're developing your own Talk2DB solution or looking to integrate LLMs into your analytics stack, this session will provide hands-on insights, architectural learnings, and real-world takeaways.

By attending this session, you’ll:

- Understand how Talk2DB bridges natural language and data visualization
- Learn how LLMs interpret queries and generate dashboards in real time
- Explore the architecture behind scalable Talk2DB solution and visualization systems
- Discover integration strategies with data warehouses and enterprise platforms
- See how automated reports and visualizations drive better business decisions
- Gain practical insights from deploying Talk2DB in production environments

🎤 Speaker: Jorge Salazar, AI Consultant at SoftServe, draws on more than a decade of experience translating business challenges into AI solutions. His work spans classical ML, computer vision, and large language models, and he currently spearheads Talk2DB — SoftServe’s conversational-analytics solution that lets business users turn natural-language questions into instant answers in plain language and reports to share insights with other stakeholders. Holding a PhD in photophysics and optoelectronics from the University of Groningen, Jorge combines deep technical expertise with a clear, outcome-oriented approach to help organizations across healthcare, finance, and manufacturing unlock the value of their data

➡️ REGISTER HERE ➡️ https://hubs.ly/Q03xN_pb0