Goal Oriented Retrieval Agents // Zoe Weil

AI Agents in Production Virtual Conference. Advanced AI agent techniques. //Abstract At Faber Labs, we have built and patented the first-of-their-kind scalable specialized Agents that autonomously seek to maximize Conversion Rate (CR), Average Order Value (AOV), Return on Ad Spend Optimization (ROAS) With rapidly evolving variations on Agent-based RAG systems, the demand for highly efficient and goal-oriented retrieval systems is increasing. GORA (Goal-Oriented Retrieval Agents) is a pioneering system designed by Faber Labs to first-of-their-kind scalable specialized Agents that autonomously seek to maximize Conversion Rate (CR), Average Order Value (AOV), Return on Ad Spend Optimization (ROAS). We will explore how GORA distinguishes itself by embedding the overall system goal into its pipeline, ensuring that each component not only performs optimally but also cohesively works towards a unified business objective. Key aspects of GORA include its interactive feedback mechanism, which transitions from traditional static queries to dynamic conversational interactions, allowing for a more natural and effective user engagement. We will discuss the system’s ability to maintain low latency despite its complex architecture, emphasizing how efficient integration of components is crucial for user efficacy. //Bio Zoe is an experienced AI leader and angel investor with over 12 years in AI/ML and a deep focus on building innovative search and discovery systems. She has invested in AI-first startups like Tough Day, Starcycle, and Eden Labs. As SVP of AI at Citi, Zoe spearheaded the adoption of agentic AI across the firm, and during her time as a Staff Applied Scientist at Etsy, she led the development of personalized search and discovery. With three patents in large language models and a background in AI at NYU, she continues to be a leading voice in the AI revolution. A Prosus | MLOps Community Production