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AWS Glossary

Amazon Q

Amazon Q is the AWS family of generative AI assistants — Q Business, Q Developer, Q in QuickSight, and Q in Connect — designed for enterprise workloads with permission-aware data access.

Definition

Amazon Q is AWS’s umbrella brand for enterprise generative AI assistants, each built for a specific persona. Amazon Quick Suite (2026) is the forward path for net-new enterprise assistant buyers — unifying Quick Index, Quick Research, Quick Flows, Quick Automate, and Quick Sight. Amazon Q Business remains supported for existing customers but closes to new signups after July 31, 2026. Q Business capabilities include permission-aware conversational search over SharePoint, Confluence, S3, Salesforce, ServiceNow, and others. Amazon Q Developer provides IDE-integrated coding assistance (see Q Developer). Amazon Q in QuickSight adds natural-language BI on governed datasets. Amazon Q in Connect delivers real-time agent assist in contact centers. For custom production agents, compare with Bedrock AgentCore in our enterprise decision guide.

When to use it

  • Enterprise knowledge search and Q&A where answers must respect document ACLs and not leak cross-department data (Q Business).
  • Employee self-service across HR policies, IT runbooks, and internal wikis without building a custom RAG stack.
  • Executive and analyst BI questions on curated QuickSight datasets with governed semantic layers (Q in QuickSight).
  • Contact center augmentation — live suggestions, summarization, and knowledge retrieval during calls (Q in Connect).
  • Organizations already standardized on IAM Identity Center for SSO across AWS and business apps.

When not to use it

  • Custom customer-facing chatbots with unique UX — Q Business is an admin-configured enterprise assistant, not a white-label embeddable widget framework.
  • Deep AWS infrastructure automation beyond coding — operational runbooks may still need custom Bedrock Agents or Lambda workflows.
  • Replacing a mature data catalog — Q Business improves retrieval but does not fix broken source-system permissions or stale content governance.

Tips

  • Audit source-system ACLs before connecting SharePoint or Confluence — Q inherits permissions; garbage ACLs in means garbage answers out.
  • Roll out Q Business Pro when you need Q Apps, actions (write-back), and higher limits; Lite fits read-only pilot teams.
  • For QuickSight, invest in Q Topics (governed semantic layer) before inviting broad user access — ungoverned NL queries produce wrong joins.
  • Use IAM Identity Center as the identity hub; map IdP groups to Q subscription tiers consistently.
  • Enable CloudTrail and admin analytics to monitor prompt patterns and data source usage for security reviews.

Gotchas

Serious

  • Connecting sensitive repositories without DLP review — Q can surface excerpts from mis-permissioned files users should never see; fix ACLs first.
  • Treating Q Business answers as authoritative for regulated decisions — human review remains required for compliance-critical outputs.

Regular

  • Confusing Q Business with Amazon Kendra alone — Kendra is retrieval infrastructure; Q Business is the full assistant experience with orchestration.
  • Skipping training for Q in QuickSight — analysts must understand Topic boundaries and when to distrust generative SQL.
  • Mixing Q Developer free tier across a large engineering org — monthly caps block teams mid-sprint; standardize Pro for production engineering.

Official references

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