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Ayka Consulting

Architecture Assessment

Enterprise AI Agent & MCP Architecture Assessment

Design the reference architecture your organization builds AI agents on, across Copilot Studio, Microsoft Foundry and Model Context Protocol (MCP).

Overview

Most organizations start with a handful of agents and quickly need a consistent way to build the rest. This assessment reviews how you are building agents today and designs the reference architecture that makes agent delivery repeatable: an enterprise agent factory covering platform choices, tool and data access through Model Context Protocol (MCP), identity and security, and data strategy.

We assess your agent architecture and your Azure AI Foundry environment (now Microsoft Foundry), then deliver a reference architecture and implementation roadmap that your teams can build against.

Who it's for
Organizations building AI agents.
Duration
3–4 weeks
Depending on the number of agents and platforms in scope.
Discuss this engagement

Customer challenges

Challenges we hear from customers

Every agent is built differently

Teams choose their own approach to orchestration, tools and memory, so nothing is reused and every agent is expensive to maintain.

Unclear platform choices

It is not obvious when to use Copilot Studio, Microsoft Foundry and Azure AI services, or custom code, or how they should work together.

Tool access without architecture

Agents need governed access to enterprise systems. Point-to-point integrations do not scale, and MCP needs a deliberate architecture around it.

Identity, security and data left to chance

Few organizations have defined how agents authenticate, what they are permitted to do, and how the data that grounds them is governed.

What we do

How the engagement runs

  1. 1

    Assess current and planned agents

    Inventory existing and planned agents, the platforms they run on and the patterns they follow, and identify gaps and duplication.

  2. 2

    Review Azure AI Foundry

    Review model deployments, agent services, evaluation, monitoring and cost controls, including Azure OpenAI usage.

  3. 3

    Design the MCP architecture

    Define how agents discover and call tools and data through MCP servers, including hosting, authentication and governance.

  4. 4

    Review security and identity

    Assess agent identities, delegated and application permissions, least privilege, secrets handling and logging.

  5. 5

    Define the data strategy

    Recommend grounding sources, retrieval patterns and data quality and permission controls for agents.

Deliverables

What you receive

  • Agent architecture assessment

    An assessment of your current and planned agents against enterprise architecture practice, with gaps and risks identified.

  • Azure AI Foundry review

    A review of your Foundry and Azure AI environment, covering models, agents, evaluation, monitoring and cost.

  • MCP architecture design

    A design for exposing tools and data to agents through MCP, with hosting, authentication and governance defined.

  • Security and identity review

    Findings and recommendations for how agents authenticate, what they can access and how their actions are audited.

  • Data strategy recommendations

    Recommendations for the data that grounds your agents, and how it is kept accurate, permissioned and governed.

Outcomes

What you walk away with

An architecture your teams can build to, and a plan for getting there.

  • Reference architecture

    A reusable enterprise pattern for building, securing and running AI agents on Microsoft technology.

  • Implementation roadmap

    A sequenced plan covering the platform, integration, security and data work needed to put the architecture in place.

Business value

  • Reduce implementation effort

    Every new agent starts from a proven pattern instead of from scratch, so teams spend their time on business logic.

  • Reduce risk

    Identity, tool access and data grounding are designed in from the start rather than retrofitted after agents are live.

  • Build on Azure AI with confidence

    A clear path to running production agents on Microsoft Foundry and Azure OpenAI, with evaluation, monitoring and cost decisions made up front.

Get in touch

Discuss this engagement

Tell us about your environment and what you want to achieve. We'll come back to you by email to talk through scope.

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