SE Framework for enterprise agentic workforces

Run your
agentic workforce
- not another AI demo.

The SE Framework gives clients a governed environment to subscribe to, configure, operate, and scale virtual AI workforces. Use Stokedge-hosted agents for speed — or deploy the full control plane and runtime into your own cloud or on-prem estate when security, sovereignty, or regulation demands it.

Hosted SaaS or customer-managed Microsoft Agent Framework aligned Azure-first architecture Multi-tenant by design
Deployment model

One framework. Two operating models. Same agentic workforce.

Option 2 · Customer-managed

Deploy the full SE stack in your cloud or on-prem infrastructure.

Enterprises can run the SE Framework inside their own Azure tenant, private cloud, Kubernetes estate, or on-prem environment while preserving the same agent, skill, tool, policy, and observability model.

  • Customer-controlled data plane, identity boundary, and network perimeter
  • AKS/container-based runtime with portable deployment patterns
  • Integration with enterprise identity, APIs, data stores, and monitoring
  • Appropriate for regulated, sovereign, or highly sensitive workloads
Core capabilities

The control plane TDMs need before agents touch real work.

ID

Tenant & identity foundation

Logical tenant isolation, enterprise SSO, user and service identity, authorization boundaries, and consent-aware access to tools and data.

OIDC · OAuth2/OBO · RBAC · tenant context
AG

Agent workforce registry

Register, configure, version, and operate role-based agents such as sales assistants, service triage agents, operations analysts, and domain specialists.

agents · prompts · versions · assignments
CP

Capability packs

Package reusable agent templates, skills, tools, prompts, policies, workflows, and industry accelerators for controlled reuse across tenants and deployments.

templates · policies · workflows · reusable assets
SK

Skills, tools & MCP integration

Expose business systems safely through typed tools, MCP servers, APIs, connectors, and isolated execution environments with policy validation before action.

MCP · OpenAPI · APIM · tool allow-listing
OR

Agent & workflow orchestration

Coordinate agent-to-agent delegation, workflow-driven execution, escalation paths, retries, budgets, and human approvals for high-value business processes.

Microsoft Agent Framework · workflows · delegation
GR

Guardrails & policy enforcement

Apply execution budgets, approval gates, argument validation, sensitive data redaction, prompt-injection defenses, and audit controls across all agent actions.

policy engine · approvals · validation · audit
ME

Memory & knowledge grounding

Manage short-term run context, long-term tenant memory, RAG hints, semantic search, and scoped context sharing across agents without uncontrolled data leakage.

Cosmos DB · Azure AI Search · vector/RAG
OB

Observability & operations

Give platform teams traceability across agent runs, tool calls, model usage, cost, failures, approvals, and operational health from pilot to production scale.

Azure AI Foundry · telemetry · replay · cost ledger
MK

Marketplace & onboarding

Help clients discover approved capability packs, onboard teams, subscribe to agents, and manage usage without turning every rollout into a custom project.

catalog · onboarding · subscription · usage
Reference architecture

A governed agentic stack, not a collection of demos.

Discuss deployment model ↗
L1 · Experience

Client workspace

Onboarding UI
Agent console
Marketplace
Approvals inbox
L2 · Control plane

SE governance core

Tenant management
Agent registry
Capability packs
Policy engine
L3 · Runtime

Agent execution

Microsoft Agent Framework
Azure AI Foundry
Workflow orchestration
Run context
L4 · Integration

Tools & data

APIM / MCP servers
Enterprise APIs
Cosmos DB
Azure AI Search
L5 · Operations

Trust & control

Audit trail
Telemetry
Cost management
Security monitoring
Enterprise controls

Built for the teams that have to approve, operate, and defend the platform.

01

Isolation model

Tenant-scoped configuration, data, memory, tools, and policy boundaries designed for multi-client operation and customer-managed deployments.

02

Policy-first execution

Agents do not get unrestricted access. Tool use is mediated through schema validation, authorization, approvals, and execution limits.

03

Human control points

Risk-based approval flows keep humans in charge of side-effecting actions, sensitive decisions, and exception handling.

04

Operational evidence

Every relevant run, decision, tool call, escalation, and policy outcome is observable and auditable for technical and business stakeholders.

Adoption path

From first agent to managed virtual workforce.

Step 1

Assess the workload

Identify the process, data sources, tools, approval points, and success metrics for the first virtual workforce scenario.

Step 2

Configure the workforce

Select agent roles, activate capability packs, bind tools, configure prompts, and set guardrails per tenant or deployment.

Step 3

Run under supervision

Deploy into production with controlled scope, telemetry, human approval gates, cost tracking, and weekly operational review.

Step 4

Scale the operating model

Expand to additional teams, processes, agents, and capability packs while preserving governance and platform consistency.

Deployment options

Choose the operating boundary that matches your risk profile.

FY26
Tier 2 · Private cloud deployment

Your Azure tenant

Best for enterprises that want the SE Framework inside their own cloud boundary while keeping Azure-native implementation patterns.

  • AKS runtime and Azure AI Foundry alignment
  • Customer-controlled identity, networking, and data stores
  • Integration with internal APIs via APIM and MCP
  • Enterprise monitoring and security tooling
FY27
Tier 3 · On-prem / hybrid

Customer-controlled estate

Best for regulated workloads, sovereignty requirements, or environments where data and execution must stay within a private perimeter.

  • Containerized runtime portability
  • Private network and data residency control
  • Configurable telemetry and redaction model
  • Deployment architecture agreed case by case
2modes
hosted subscription or customer-managed deployment
9core
platform capability areas for operating agentic workforces
5layers
experience, control plane, runtime, integration, and operations
1model
consistent governance across SaaS, cloud, and on-prem deployments
SE is designed for the moment when a client stops asking whether an agent can work — and starts asking how to govern a workforce of them in production.
Stokedge architecture principle · agentic workforce platform
Get started

Start with one workforce scenario, then scale the platform.

We will map the first target process, recommend the right deployment model, define the tenant, agent, skill, tool, memory, and governance setup, and produce the technical architecture needed to move into implementation.

se/workforce-setup.json ● governed
// Virtual workforce configuration example
{
  "tenant": "contoso-eu",
  "deploymentMode": "hosted-se-environment",
  "workforce": {
    "name": "sales-operations-workforce",
    "agents": ["lead-qualifier", "quote-assistant", "crm-updater"]
  },
  "guardrails": {
    "toolAllowList": "approved-sales-tools",
    "humanApproval": "required-for-side-effects",
    "maxRunBudget": 12.50
  }
}