Why Agentic AI Needs an Economic Layer？ скачать в хорошем качестве

Why Agentic AI Needs an Economic Layer？

​Karen Sheng, Chief Product Officer @ AIsaIn this session from the Data for AI meetup, demonstrates how to empower developers to build and monetize AI agents faster using a unified interface. 🔍 What’s Inside this Demo: Unified API Access: How AIsa provides a single gateway to 50+ state-of-the-art LLMs (including the latest Qwen and thinking models) alongside real-world data endpoints like Twitter, YouTube, and Scholarly search. Agentic Architecture in Action: A deep dive into a "Scoring Agent" that runs parallel queries across academic and web sources to evaluate facts and reconcile conflicting information. The Economic Layer: Exploring the shift from subscription models to usage-based pricing and how AIsa enables developers to monetize their AI products seamlessly. Live Demo & Synthesis: Watch how the agent performs meta-analysis on complex queries and provides a confidence-scored synthesis of results. 💡 Key Takeaway: Building an AI agent is only half the battle; ensuring it has access to trusted data and a sustainable economic model is what makes it production-ready.