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Empowering Data-Driven Decisions: Embedding Trust in Text-to-SQL AI Agents
Simplify complex data environments for users utilizing reliable AI Agent systems towards better data-driven decision-making
What are the key factors that drive user’s trust and engagement in conversational data-driven AI applications?
Rising numbers of organizations internally adopting AI applications do not necessarily reflect higher user engagement scores. Trust scores when it comes to AI results are not within the critical decision-making range.
Introducing additional components to such applications becomes crucial to drive both engagement and trust of their users, ultimately leading organizations towards a more data-driven decision-making environment.
Table of Contents
1- Simplicity plays a crucial role in driving engagement (The Why)
2- Decision-Making Becomes Conversational (The What)
3- Building Trust in AI Data Applications (The How)
4 — Hands-On: Building Data Chat Room with Gradio, Postgres, and Langchain
