Semantic Kernel Agent Orchestration - Sequential Orchestration (Series 3/5)

First Topic by Mourtaza Fazlehoussen: Sequential Orchestration
In the sequential pattern, agents are organized in a pipeline. Each agent processes the task in turn, passing its output to the next agent in the sequence. This is ideal for workflows where each step builds upon the previous one, such as document review, data processing pipelines, or multi-stage reasoning.

Why Multi-agent Orchestration?
Traditional single-agent systems are limited in their ability to handle complex, multi-faceted tasks. By orchestrating multiple agents, each with specialized skills or roles, we can create systems that are more robust, adaptive, and capable of solving real-world problems collaboratively. Multi-agent orchestration in Semantic Kernel provides a flexible foundation for building such systems, supporting a variety of coordination patterns.

Orchestration Patterns
Semantic Kernel supports several orchestration patterns, each designed for different collaboration scenarios. These patterns are available as part of the framework and can be easily extended or customized.

Second Topic by Vishnu Jaiswal: Designing a Multi-Agent AI Hotel Receptionist, Cloud IVR and Conversational Automation
This session presents the architecture and engineering choices behind an AI-powered hotel receptionist, built with Python, FastAPI, and Azure AI services (Speech, LLM). The project connects real phone calls to a cloud-hosted, multi-agent conversational backend using telephony platforms such as KooKoo and Exotel.

Key highlights :-
Multi-agent orchestration: How multiple specialized AI agents (front desk, booking, food orders) collaborate to understand guest intent and automate responses.

Speech pipeline :- Integrating Azure Speech-to-Text, language models for reasoning, and dynamic Text-to-Speech for real-time guest interactions.

Cloud IVR integration :- How call flows connect telephony platforms to webhooks and return audio playback.

Resilience and troubleshooting :- Lessons learned in handling cloud IVR delays and considerations for future platform migration plus tips on adapting the solution for any call provider.

Extensible, production-ready patterns :- Design approaches that allow the receptionist to scale to new domains (housekeeping, spa) with minimal code changes.

The talk will dive into the backend orchestration, code structure, and integration strategy equipping you with real insights on deploying practical multi-agent AI for the hospitality industry.