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HR Agent iconAI Agent

HR Agent

HR Agent that automates hr workflows using your data and tools.

The challenge

HR spends its week answering the same policy questions, with answers that vary by who replies and which version of the handbook they happened to open. Employees wait on a ticket for something already published, local policy differences get missed, and real cases queue behind routine admin.

The outcome

Microsoft Entra resolves entitlement before anything is retrieved, Azure AI Search finds the policy version that applies to that person, and a Microsoft Foundry agent answers with the citation and raises leave, letter or IT requests through Azure Logic Apps. Sensitive topics route straight to a human partner.

At a glance

Type
ai agents
Category
business

Next step

Move from solution to engagement.

Build This Solution

01 — Architecture

End-to-end architecture

An employee asks in Teams or the portal. Entitlement, location and the applicable policy version are resolved first, retrieval is trimmed to what that person is allowed to see, and the Foundry agent answers with the policy citation — raising leave, letter or IT actions where it can, and routing anything sensitive to a human partner.

EMPLOYEEEmployee /Managerask · request · caseCHANNELSMicrosoft Teamsin-flow HR assistantAzure Static WebAppsself-service portalAPPLICATIONAzure APIManagementHRIS & payroll APIsAzure ContainerAppsHR agent runtimeAI & AGENTMicrosoft FoundryAgentanswer · act · routeAzure OpenAImodelsanswers & summariesAzure AI Searchpolicy & handbookAzure AI ContentSafetysensitive topic guardDATA & PRIVACYAzure SQLcases & requestsAzure Cosmos DBconversation statePermissiontrimmingown data onlyRESOLUTION & INSIGHTHR workflowactionsleave · letters · ITHR partner reviewsensitive casesPower BI / Fabricvolume & resolutionDEVOPS & DELIVERYGitHubsource control & CIDockercontainer buildContainer Registryversioned imagesAgent releasedeploy with rollback
Figure 1 — End-to-end reference architecture for an employee service agent on the Microsoft stack.
  • Employee: Employee / Manager
  • Channels: Microsoft Teams, Azure Static Web Apps
  • Application: Azure API Management, Azure Container Apps
  • AI & agent: Microsoft Foundry Agent, Azure OpenAI models, Azure AI Search, Azure AI Content Safety
  • Data & privacy: Azure SQL, Azure Cosmos DB, Permission trimming
  • Resolution & insight: HR workflow actions, HR partner review, Power BI / Fabric

02 — Workflow

Process & decision workflow

How an employee question becomes a resolved case — identify, retrieve, answer, act and log, then branch. Routine, in-policy requests are self-served and closed with the policy cited, while sensitive topics go straight to an HR partner with confidentiality preserved.

1AskEmployee asks in Teams, the portal or byemail2IdentifyEntitlement, location and policy versionresolved3RetrieveHandbook, local policy and prior casessearched4AnswerGrounded response with the policycitation5ActLeave, letter, expense or IT requestraised6LogCase, resolution and satisfactionrecordedRoutine& in policy?Path 1 · routine requestSelf-serve and closeAnswered or actioned with the policycitedPath 2 · sensitive or exceptionHR partner takes the caseConfidential handoff with context andhistoryCase recordedAnswer, action and policyversion storedPolicy gap loggedUnclear guidance routed to theownerCloseemployee served
Figure 2 — Ask → identify → retrieve → answer → act → sensitivity branch → self-serve or HR partner.
  1. Ask: Employee asks in Teams, the portal or by email
  2. Identify: Entitlement, location and policy version resolved
  3. Retrieve: Handbook, local policy and prior cases searched
  4. Answer: Grounded response with the policy citation
  5. Act: Leave, letter, expense or IT request raised
  6. Log: Case, resolution and satisfaction recorded
  7. Path 1 · routine request — Self-serve and close: Answered or actioned with the policy cited
  8. Path 2 · sensitive or exception — HR partner takes the case: Confidential handoff with context and history

03 — Components

Key Microsoft components

Employee service is a privacy problem before it is a chat problem — retrieval, entitlement and actions all stay inside the Microsoft ecosystem.

  • Microsoft Teams iconMicrosoft TeamsIn-flow assistant where employees already work.
  • Azure Static Web Apps iconAzure Static Web AppsSelf-service portal for requests, letters and cases.
  • Azure API Management iconAzure API ManagementSecure gateway for HRIS, payroll and service-desk APIs.
  • Azure Container Apps iconAzure Container AppsAgent runtime and tool endpoints that scale with demand.
  • Microsoft Foundry Agent Service iconMicrosoft Foundry Agent ServiceAnswering, action and escalation orchestration.
  • Azure OpenAI models iconAzure OpenAI modelsGrounded answers, multilingual replies and case summaries.
  • Azure AI Search iconAzure AI SearchRetrieval over the handbook, local policy and prior cases.
  • Azure AI Content Safety iconAzure AI Content SafetyDetects sensitive topics and enforces tone guardrails.
  • Microsoft Entra permissions iconMicrosoft Entra permissionsEntitlement resolution and permission-aware retrieval.
  • Azure Logic Apps iconAzure Logic AppsLeave, letter, expense and IT request workflows.
  • Azure SQL iconAzure SQLCases, requests, resolutions and satisfaction records.
  • Azure Cosmos DB iconAzure Cosmos DBConversation state and per-employee session history.
  • Azure Blob Storage iconAzure Blob StorageHandbook sources, generated letters and case attachments.
  • Power BI / Microsoft Fabric iconPower BI / Microsoft FabricVolume, deflection, resolution and policy-gap dashboards.

04 — AI

What the agent consumes

The capabilities the agent applies to every request, and the line it does not cross.

AI capabilities embedded in the agent

  • Intent detection
  • Entitlement resolution
  • Retrieval-augmented generation
  • Policy citation
  • Multilingual answering
  • Form and letter generation
  • Workflow actions
  • Sensitive-topic detection
  • Permission-aware retrieval
  • Case summarisation
  • Knowledge-gap detection
  • Escalation routing

AI responsibility boundaries

The agent answers from the published handbook and the entitlements of the person asking, always citing the policy version. It does not decide grievance, disciplinary or performance outcomes, and it never exposes data belonging to another person. Wellbeing, harassment and pay disputes route straight to a human HR partner with confidentiality preserved.

05 — Personalization

Personalization & evolving process

The same methodology applies to every agent in the catalog. Tune the workforce profile, the service template, the policy rules and the value model — the page structure stays identical.

Workforce & policy profile

Define the countries, legal entities, languages, employment types and local policy variants in scope. The personas are the employee, the line manager, the HR partner and payroll.

06 — Impact

Key outcomes & business impact

Starting targets for the value case — validate each one against the customer baseline during discovery.

  • Query deflection50%+Routine policy questions never reach the HR inbox.
  • Response timeSecondsEmployees get a cited answer instead of a ticket number.
  • HR partner focus−45%Admin volume drops so partners handle real cases.
  • Policy traceability100%Every answer names the policy and version behind it.

Illustrative improvement index

Manual baseline = 100. Illustrative targets, not a commitment — confirm against the customer baseline.

10050HR admin volume10010Response time10055Onboarding effortManual baselineAI-assisted target
  • HR admin volume: manual baseline 100, AI-assisted target 50
  • Response time: manual baseline 100, AI-assisted target 10
  • Onboarding effort: manual baseline 100, AI-assisted target 55

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Derived automatically from our solution knowledge graph.

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