
Low Code, Copilots & AI Agents for Financial Services @Microsoft
In a recent YouTube video, Parag Dessai explains how Microsoft’s Copilot Studio now connects to a range of external agents and data services. He highlights new integrations that let Copilot Studio link with the Foundry Agent, the Fabric Data Agent, and any agent that supports the A2A protocol. As a result, makers can build multi‑agent workflows that pass context and tasks across systems without heavy custom coding.
Moreover, Dessai frames these improvements as part of Microsoft’s 2025 push toward more autonomous, composable agents. He shows practical scenarios where agents query live data, hand off tasks, and enrich outputs by combining strengths from different services. Therefore, the video presents both a technical walkthrough and a forward-looking view of agent orchestration in enterprise settings.
First, the video explains the mechanics behind the new links. Copilot Studio uses connectors and the agent flows interface to attach to external agents, while the A2A protocol provides a lightweight, secure channel for agent-to-agent messaging. In addition, the system exchanges context via structured JSON payloads so that an agent can pass user queries, session state, or intermediate outputs to another agent reliably.
Second, Dessai demonstrates specific integrations such as routing queries to the Fabric Data Agent for real‑time analytics and invoking the Foundry Agent for semantic data synthesis. He also references the broader toolkit, including the Model Context Protocol (MCP) and the Agents Client SDK for native app access. Consequently, Copilot Studio becomes a hub where multiple components collaborate in a more automated fashion.
Importantly, the video emphasizes reduced data silos as one primary benefit. By connecting agents directly to Fabric’s lakehouse through the Fabric Data Agent, teams can avoid manual data transfers and maintain fresh context for tasks like invoice processing or supplier discovery. Thus, organizations gain faster, more accurate insights that support operational decisions.
Furthermore, Dessai highlights scalability and customization as additional advantages. The A2A protocol enables chained actions and agent discovery, while features such as express mode aim to finish simple workflows in under two minutes. Additionally, integration with advanced models like GPT-5 in preview and governance tools such as the Agent 365 control plane lets enterprises tune performance and compliance for production scenarios.
However, the video does not shy away from tradeoffs that teams must balance. For example, while direct agent-to-agent communication reduces latency, it raises questions about responsibility for data accuracy and error handling when multiple agents work together. Consequently, architects must design clear failure modes and rollback strategies to avoid compounding mistakes across chained agents.
Additionally, Dessai points out governance and security complexities that grow with interoperability. Although the A2A protocol is designed to be secure, integrating many agents increases the surface area for misconfigurations and requires careful identity and access control. Therefore, teams must weigh the benefits of rapid automation against the overhead of formal testing, monitoring, and policy enforcement.
Finally, the video outlines practical steps for teams to get started and to operate safely at scale. Dessai recommends using Copilot Studio’s agent flows and Power Automate connectors to prototype small end‑to‑end scenarios, then gradually expand connections to the Foundry Agent and Fabric Data Agent as confidence grows. This staged approach reduces risk and helps teams discover integration pain points early.
Moreover, he stresses the need for continuous evaluation and observability, referencing tools like the unified activity map for testing and agent evaluation features for quality control. In short, organizations should combine experimentation with explicit governance, because balancing agility, reliability, and security is essential for multi‑agent systems to deliver long-term value.
In summary, Parag Dessai’s video delivers a clear and practical look at how Copilot Studio can connect to diverse agents and data services to create richer, more automated workflows. The integrations promise reduced context switching, faster execution, and broader ecosystem reach, while also introducing governance and operational tradeoffs that teams must manage. Therefore, watchers leave with both a roadmap for experimentation and a reminder that careful design will determine success when composing many agents into a single solution.
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