AI apps and agents: choosing your Marketplace offer type

Choosing your Marketplace offer type is one of the earliest—and most consequential—decisions you’ll make when preparing an AI app for Microsoft Marketplace. It’s also one of the hardest to change later.

This post is the second in our Marketplace‑ready AI app series. Its goal is not to push you toward a specific option, but to help you understand how Marketplace offer types map to different AI delivery models—so you can make an informed decision before architecture, security, and publishing work begins.

This post is part of a series on building and publishing well-architected AI apps and agents on Microsoft Marketplace.

Why offer type is an important Marketplace decision

Offer type is more than a packaging choice. It defines the operating model of your AI app on Marketplace:

• How customers acquire your solution
• Where the AI runtime executes
• Determining the right security and business boundaries for the AI solution and associated contextual data
• Who operates and updates the system
• How transactions and billing are handled

Once an offer type is selected, it cannot be changed without creating a new offer. Teams that choose too quickly often discover later that the decision creates friction across architecture, security boundaries, or publishing requirements.

Microsoft’s Publishing guide by offer type explains the structural differences between offer types and why this decision must be made up front.

How Marketplace offer types map to AI delivery models

AI apps differ from traditional software in a few critical ways:

• Contextual data may need to remain in a specific tenant or geography
• Agents may operate autonomously and continuously
• Control over infrastructure often determines trust and compliance
• How the solution is charged and monetized, including whether pricing is usage‑based, metered, or subscription‑driven (for example, billing per inference, per workflow execution, or as a flat monthly fee)
• The buyer’s technical capability, including the level of engineering expertise required to deploy and operate the solution (for example, SaaS is generally easier to consume, while container‑based and managed application offers often require stronger cloud engineering and DevOps skills)

Marketplace offer types don’t describe features. They define responsibility boundaries—who controls the AI runtime, who owns the infrastructure, and where customer data is processed.

At a high level, Marketplace supports four primary delivery models for AI solutions:

• SaaS
• Azure Managed Application
• Azure Container
• Virtual Machine

Each represents a different balance between publisher control and customer control. The sections below explain what each model means in practice.

Check out the interactive offer selection wizard in App Advisor for decision support. Below, we unpack each of the offer types.

SaaS offers for AI apps

SaaS is the most common model for AI apps and agents on Marketplace—and often the default starting point.

With a SaaS offer, the AI service runs in the publisher’s Azure environment and is accessed by customers through a centralized endpoint. This model works well for:

• Multi‑tenant AI platforms and agents
• Continuous model and prompt updates
• Rapid experimentation and iteration
• Usage‑based or subscription billing

Because the service is centrally hosted, publishers retain full control over deployment, updates, and operational behavior. For multi-tenant AI apps, this also means making early decisions about Microsoft Entra ID configuration—such as how customers are onboarded, whether access is granted through tenant-level consent or external identities, and how user identities, roles, and data are isolated across tenants to prevent cross-tenant access or data leakage.

For official guidance, see the SaaS section of the Marketplace publishing guide and the AI agent overview, which describes SaaS‑based agent deployments. Plan a SaaS offer for Microsoft Marketplace.

Azure Managed Applications for AI solutions

In this model, the solution is deployed into the customer’s Azure subscription, not the publisher’s. There are two variants:

• Managed applications, where the publisher retains permissions to operate and update the deployed resources
• Solution templates, where the customer fully manages the deployment after installation

This model is a strong fit when AI workloads must run inside customer‑controlled environments, such as:

• Regulated or sensitive data scenarios
• Customer‑owned networking and identity boundaries
• Infrastructure‑heavy AI solutions that can’t be centralized
• Willingness or need on part of the customer or IT team to tailor the app to the needs of the end customer specific environment

Managed Applications sit between SaaS and fully customer‑run deployments. They offer more customer control than SaaS, while still allowing publishers to manage lifecycle aspects when appropriate.

Marketplace guidance for Azure Applications is covered in the publishing guide. For more information, see the following links:  Plan an Azure managed application for an Azure application offer.

Azure Container offers for AI workloads

With container offers, the customer runs the AI workload—typically on AKS—using container images supplied by the publisher. This model is best suited for scenarios that require:

• Strict data residency
• Air‑gapped or tightly controlled environments
• Customer‑managed Kubernetes infrastructure

The publisher delivers the container artifacts, but deployment, scaling, and runtime operations occur in the customer’s environment. This shifts operational responsibility, risk and compute costs away from the publisher and toward the customer.

Container offer requirements are covered in the Marketplace publishing guide. Plan a Microsoft Marketplace Container offer.

Virtual Machine offers for AI solutions

Virtual Machine offers still play a role, particularly for specialized or legacy AI solutions.

VM offers package a pre‑configured AI environment that customers deploy into their Azure subscription. Compared to other models, they offer:

• Updates and scaling are more tightly scoped
• Iteration cycles tend to be longer
• The solution is more closely aligned with specific OS or hardware requirements

They are most commonly used for:

• Legacy AI stacks
• Fixed‑function AI appliances
• Solutions with specialized hardware or driver dependencies

VM publishing requirements are also documented in the Marketplace publishing guide. Plan a virtual machine offer for Microsoft Marketplace.

Comparing offer types across AI‑specific decision dimensions

Rather than asking “which offer type is best,” it’s more useful to ask what trade‑offs you’re making.

Key lenses to consider include:

• Who operates the AI runtime day‑to‑day
• Where customer data and AI prompts inputs and outputs are processed and stored
• How quickly models, prompts, and logic can evolve
• The balance between publisher control and customer control
• How Marketplace transactions and billing align with runtime behavior

Different AI solutions land in different places across these dimensions. The right choice is the one that matches your operational reality—not just your product vision.

Note: If your solution primarily delivers virtual machines or containerized workloads, use a Virtual Machine or Container offer instead of an Azure Managed Application.

Supported sales models and pricing options by Marketplace offer type

Marketplace offer types don’t just define how an AI app and agent is deployed — they also determine how it can be sold, transacted, and expanded through Microsoft Marketplace. Understanding the supported sales models early helps avoid misalignment between architecture, pricing, and go‑to‑market strategy.

Supported sales models

What these sales models mean

• Transactable listing
  A Marketplace listing that allows customers to purchase the solution directly through Microsoft Marketplace, with billing handled through Microsoft.
• Public listing
  A listing that is discoverable by any customer browsing Microsoft Marketplace and available for self‑service acquisition.
• Private offers
  Customer‑specific offers created by the publisher with negotiated pricing, terms, or configurations, purchased through Marketplace.
• Resale enabled
  Using resale enabled offers, software companies can authorize their channel partners to sell their existing Marketplace offers on their behalf. After authorization, channel partners can independently create and sell private offers without direct involvement from the software company.
• Multiparty private offers
  Private offers that involve one or more Microsoft partners (such as resellers or system integrators) as part of the transaction.
• Azure IP Co‑sell eligible
  When all requirements are met this allows your offers to contribute toward customers' Microsoft Azure Consumption Commitments (MACC). 

Pricing section

Marketplace offer types determine the pricing models available. Make sure you build towards a marketplace offer type that aligns with how you want to deploy and price your solution.

• SaaS – Subscription or flat‑rate pricing, per‑user pricing, and usage‑based (metered) pricing.

• Container – Kubernetes‑based offers support multiple Marketplace‑transactable pricing models aligned to how the workload runs in the customer’s environment, including per core, per core in cluster, per node, per node in cluster, per pod, or per cluster pricing, all billed on a usage basis. Container offers can also support custom metered dimensions for application‑specific usage. Alternatively, publishers may offer Bring Your Own License (BYOL) plans, where customers deploy through Marketplace but bring an existing software license.

• Virtual Machine – Usage-based hourly pricing (flat rate, per vCPU, or per vCPU size), with optional 1-year or 3-year reservation discounts. Publishers may also offer Bring Your Own License (BYOL) plans, where customers bring an existing software license and are billed only for Azure infrastructure.
• Azure Managed Application – A monthly management or service fee charged by the publisher; Azure infrastructure consumption is billed separately to the customer.

Note: Azure Managed Applications are designed to charge for management and operational services, not for SaaS‑style application usage or underlying infrastructure consumption.

Buyer‑side assumptions to be aware of

For customers to purchase AI apps and agents through these sales models:

• The customer must be able to purchase through Microsoft Marketplace using their existing Microsoft procurement setup
• Marketplace purchases align with enterprise buying and governance controls, rather than ad‑hoc vendor contracts
• For private and multiparty private offers, the customer must be willing to engage in a negotiated Marketplace transaction, rather than pure self‑service checkout

Important clarification

Supported sales models are consistent across Marketplace offer types. What varies by offer type is how the solution is provisioned, billed, operated, and updated. Sales flexibility alone should not drive offer‑type selection — it must align with the architecture and operating model of the AI app and agent.

How this decision impacts everything that follows

Offer type decisions ripple through the rest of the Marketplace journey. They directly shape:

• Architecture design choices
• Security and compliance boundaries
• Fulfillment APIs and billing integration
• Publishing and certification requirements
• Cost, scalability, and operational responsibility

Follow the series for updates on new posts.

What’s next in the journey

With the offer type decision in place, the focus shifts to turning that choice into a production‑ready solution. This includes designing an architecture that aligns with your delivery model, establishing clear security and compliance boundaries, and preparing the operational foundations required to run, update, and scale your AI app or agent confidently in customer environments. Getting these elements right early reduces rework and sets the stage for a smoother Marketplace journey.

Key resources

See curated, step-by-step guidance to help you build, publish, or sell your app or agent (no matter where you start) in App Advisor

Quick-Start Development Toolkit

Microsoft AI Envisioning Day Events 

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