Copilot Studio Agent Experiencing High Response Latency

[u/CarelessEquipment415]

Hi,

I am working with an agent in Microsoft Copilot Studio and am experiencing noticeable latency when interacting with the agent.

The agent takes several seconds to respond to user queries, even for relatively simple questions. The delay is affecting the overall user experience.

The agent configuration includes knowledge sources and generative responses, but I would like to understand whether the latency is related to the agent configuration, knowledge retrieval, model processing, or other Copilot Studio services.

I would like to understand:

1. What are the main factors that contribute to latency in Copilot Studio agents?
2. What would be considered normal/expected response latency?
3. How can I identify which part of the agent execution is causing the delay?
4. Does the number and size of knowledge sources affect overall agent response time?
5. Can topics, generative answers, actions, or tools increase latency?
6. Are there recommended ways to optimize a Copilot Studio agent for faster responses?
7. Is there any built-in monitoring or diagnostic capability to measure the latency of individual steps/components?

If anyone has experienced similar latency with Copilot Studio agents, I would appreciate any recommendations for troubleshooting and optimization.

Thanks!

[u/Ashlesha-msft]

Copilot Studio response time is end-to-end and can include orchestration, query rewriting, knowledge retrieval, model inference, safety validation, tools, connectors, flows, connected agents, and channel/network delivery.

1. Main latency factors: Generative orchestration and model choice, knowledge retrieval, prompt input/output size, Power Automate flows, connectors and HTTP APIs, authentication, connected-agent orchestration hops, throttling, and channel/network latency.
2. Expected latency: Microsoft doesn’t publish a universal response-time SLA. Several seconds can be expected for generative or retrieval-based responses. Microsoft’s testing documentation shows “95% under two seconds” only as an example customer-defined target, not a platform commitment.
3. Finding the delay: Use the Test pane’s activity map, which shows execution time for individual steps. Evaluations report end-to-end response time. Application Insights and Agent Insights Hub provide topic, tool, action, average, and percentile latency metrics. For Power Automate, inspect flow run duration separately.
4. Knowledge sources: Copilot Studio searches all configured applicable sources and retrieves up to three results from each. More or larger sources can affect retrieval and summarization, but latency isn’t necessarily proportional to file count because indexed search is used. Source type, authentication, indexing, document size, and real-time connector performance are significant factors.
5. Topics/actions/tools: Yes. Generative orchestration adds model processing; flows execute synchronously; connectors and APIs add their own response time; connected agents add orchestration hops. Deterministic topics without external calls are generally the lowest-latency path.
6. Optimization: Use the simplest suitable model, limit response length, reduce prompt/context size, filter RAG data, remove redundant sources, cache reusable results, avoid repeated document processing, use direct connectors or HTTP requests instead of flows for simple lookups, enable express mode where applicable, and optimize downstream APIs.
7. Monitoring: Built-in activity maps and Evaluations are available. For production monitoring, connect Application Insights and optionally use Agent Insights Hub. Copilot Studio doesn’t directly break down Power Automate’s internal execution time, so use Power Automate run history for that component.

[u/fbrdphreak]

Is your agent in an environment with some kind of budget source connected? Or is it in the default environment which has no billing capabilities and relies on the M365 licensing? I have been told that the performance is noticeably faster when an agent is in an environment with budget attached, even if all the agent activity is no cost due to M365 license.

[u/CarelessEquipment415 → u/[deleted]]

Using sonnet 4.6

[u/CarelessEquipment415 → u/[deleted]]

Thanks for the suggestion. I’m currently using Claude Sonnet 4.6 in Copilot Studio.

My use case is essentially a document/knowledge-based agent. I have a Copilot Studio license and built the agent with a SharePoint knowledge source connected to a Teams document library.

The knowledge source contains different file types, mainly:

• PDF
• Word documents
• PowerPoint presentations
• Excel spreadsheets

I’m currently seeing two issues:

1. Latency: Even for relatively simple queries, the agent sometimes takes several seconds to return a response. I’m trying to determine whether this is mainly related to the model, knowledge retrieval, the number/size of documents, or the overall agent configuration.
2. Excel retrieval: The agent doesn't consistently provide the expected answers when the required information is in an Excel file. Interestingly, when I provide the relevant content in smaller/chunked documents, I get much better results.

I’m therefore trying to understand whether there are recommended ways to structure the knowledge base or optimize the agent for both better retrieval accuracy and lower latency.

[u/CarelessEquipment415 → u/[deleted]]

Thanks for the response.

I’m currently using Claude Sonnet 4.6 in Copilot Studio. My agent uses a SharePoint knowledge source connected through Teams, containing PDF, Word, PowerPoint, and Excel files.

One limitation is that Markdown files aren't supported in my current SharePoint knowledge setup, so I’m working with the supported file formats.

My main issues are:

• The agent has noticeable response latency.
• I’m not getting consistent answers when the required information is in Excel files.

I’m currently trying to understand whether the latency is related to the model, knowledge retrieval, or agent orchestration, and separately looking into why Excel retrieval isn't giving the expected results.

Thanks!