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AwsAmazon BedrockAgentcoreSagemakerAmazon QMicrosoft TeamsAI AgentsRagLLMMLOpsAIDevOps

Amazon Bedrock, AgentCore, SageMaker & Q: Agents in Microsoft Teams

FDE playbook: which AWS service to use, first Teams agent path, and calendar estimates for RAG, MLOps, and LLM apps

Balinder WaliaJuly 21, 20262 min read

How Amazon Bedrock, Bedrock AgentCore, SageMaker, and Amazon Q fit together — and how an FDE ships a first business agent into Microsoft Teams. For the full setup guide, tooling list, and calendar estimates, read the long article.

Amazon Bedrock AgentCore SageMaker Amazon Q agents in Microsoft Teams

The one-paragraph version. Use Amazon Bedrock for managed foundation models and RAG knowledge bases. Use Bedrock AgentCore as the runtime for custom agents (memory, tools, identity, observability). Use SageMaker when you need custom training, fine-tuning, or MLOps pipelines. Use Amazon Q (Business / Developer) when you want a productised employee or builder assistant with less engineering. Put agents where people already work — Microsoft Teams — via a Bot Framework / Azure Bot relay into AgentCore Runtime, with Entra ID for auth.

Who does what in the AWS stack

Service Best for Not for
Amazon BedrockServerless FMs, Guardrails, Knowledge Bases (RAG), Agents APIsTraining large models from scratch
Bedrock AgentCoreCustom agent runtime, Gateway tools (incl. Teams Graph), Identity, MemoryLow-code “chat with my docs” only
Amazon SageMakerTrain / fine-tune / host custom models, Pipelines, Feature Store, MLOpsFastest path to a Teams chatbot MVP
Amazon QEmployee knowledge assistant; developer coding help on AWSDeeply custom multi-agent products

Recommended business pattern

  1. Week 0–2: Stand up Bedrock + Knowledge Base RAG on a pilot corpus; enable Guardrails.
  2. Week 2–4: Package a production agent on AgentCore Runtime; connect tools via Gateway (SharePoint, CRM, Teams Graph).
  3. Week 3–5: Ship a Teams bot that relays messages to AgentCore; keep sessions with teams-{aadObjectId}-{conversationId}.
  4. Parallel / later: SageMaker for custom classifiers or fine-tunes; Amazon Q Business for org-wide Q&A with less build.

First agent in Teams (FDE snapshot)

Minimum path that works in production-minded pilots:

  • Azure Bot + Teams app registration (Entra ID)
  • AWS Lambda (or container) as Bot messaging endpoint
  • POST to AgentCore Runtime /invocations with JWT
  • Bedrock Knowledge Base for RAG; Guardrails for safety
  • Pilot channel, human feedback loop, CloudWatch traces

Expect roughly 3–6 weeks for a scoped internal agent (one department, one knowledge source, read-mostly tools) with an FDE + platform engineer + security review. Full MLOps + multi-agent + write-actions into line-of-business systems is a quarter+.

Time boxes (indicative)

Workstream Calendar (FDE-led)
Bedrock chat + Guardrails MVP3–5 days
Knowledge Base RAG (one corpus)1–2 weeks
AgentCore agent + 2–3 tools2–3 weeks
Teams bot + admin publish pilot1–2 weeks (overlap)
Amazon Q Business (managed assistant)1–3 weeks
SageMaker fine-tune + endpoint + MLOps4–8+ weeks

Read the long version

The long article covers architecture diagrams in prose, step-by-step Teams first-agent setup, Entra ID with AgentCore Identity, tool Gateway targets, FDE training curriculum, requirements/tooling checklists, and phased estimates for LLM apps, RAG, and MLOps. Published by Workstation.