Designing Multi-Agent Deep Search Systems - 10 Seats Left

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

Summary

A technical workshop titled "Designing Multi-Agent Deep Search Systems" is scheduled for Saturday, May 16, 2026, from 17:00 - 18:30 EEST, with only 10 seats remaining. This 1.5-2 hour session focuses on architecting deep search agents that extend beyond basic retrieval. It 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. The workshop emphasizes core components, design decisions, tradeoffs, and patterns for building reliable deep search systems, providing a live session, 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. This workshop provides a structured approach to building reliable systems that can plan, execute, validate, and merge information from diverse sources, addressing complex challenges like temporal reasoning and conflict resolution. Consider attending to gain practical design patterns and a system blueprint for your next-generation search applications.

Key insights

Deep search agents require multi-agent architectures for planning, execution, validation, merging, and iterative improvement.

Principles

• Deep search differs from basic RAG.
• Validate information quality rigorously.
• Manage temporal data for accuracy.

Method

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

In practice

• Implement planner and executor agents.
• Utilize OCR and video-to-text tools.
• Score source reliability for validation.

Topics

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

Best for: AI Architect, AI Engineer

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