Designing Multi-Agent Deep Search Systems - 5 Seats Left

2024-06-18 · Source: To Data & Beyond · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems, Software Development & Engineering · Depth: Advanced, quick

Summary

A technical workshop titled "Designing Multi-Agent Deep Search Systems" is scheduled for Saturday, May 16, 2026, from 17:00 to 18:30 EEST, with only five seats remaining. This 1.5-2 hour session focuses on architecting deep search agents that extend beyond basic retrieval. The workshop will cover designing agentic workflows for planning searches, utilizing various tools, collecting and validating evidence from multiple sources, handling contradictions, reasoning about temporal data, merging findings into structured outputs, and iterative improvement. It emphasizes core components, design decisions, tradeoffs, and patterns for building reliable deep search systems, without delving deeply into implementation code. Attendees will receive a live workshop, recording, slide deck, technical notes, an architecture blueprint, and a tool design reference.

Key takeaway

For AI Architects and AI Engineers designing advanced information retrieval systems, understanding multi-agent deep search architectures is crucial. You should consider attending this workshop to gain insights into designing robust systems that can plan, validate, and merge information from diverse sources, ensuring higher quality and more reliable search results than traditional RAG approaches.

Key insights

Architecting deep search agents requires multi-agent workflows for planning, execution, validation, and iterative refinement.

Principles

• Deep search agents go beyond basic RAG.
• Validation agents improve information quality.
• Temporal reasoning prevents outdated conclusions.

Method

Design an agentic workflow that plans searches, uses diverse tools, collects and validates evidence, handles contradictions, reasons about dates, merges findings, and improves iteratively.

In practice

• Implement planner and executor agents.
• Incorporate validation and merging agents.
• Utilize OCR and video-to-text tools.

Topics

• Multi-Agent Systems
• Deep Search Agents
• Agentic Workflow Design
• Information Validation
• Temporal Reasoning

Best for: AI Architect, AI Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by To Data & Beyond.