ARCHAI ENTERPRISE™ BY ARCHAI WORLD™

ARCHAI Enterprise Architecture MCP™

The Governed Context Layer for the Agentic Enterprise.

Let AI understand your enterprise before it advises it.

AI can generate sophisticated recommendations. Without organizational context, however, it cannot reliably understand what the enterprise owns, how its capabilities operate, which systems depend on one another, what risks exist, or who is accountable.

ARCHAI Enterprise Architecture MCP™ connects authorized AI applications with the architecture, evidence, and decision context required to generate more relevant, traceable, and governable outcomes.

Launch the Interactive WorkspaceRequest an Enterprise Pilot

Permission-controlled access. Evidence-linked responses. Human accountability.

A governed connection, not an open pipe.

Enterprise Sources

Architecture RepositoryCMDBProcess RepositoryApplication PortfolioGovernance LibraryDecision RecordsRisk RegisterProject Portfolio

ARCHAI MCP Layer

Enterprise MetamodelIdentity and PermissionsEvidence and ProvenanceArchitecture ToolsGoverned Workflows

Authorized AI Experiences

Executive AssistantArchitecture CopilotGovernance AgentTransformation AgentDecision WorkspaceApproved AI Client
BEFORE YOU CONTINUE

Four questions worth answering before your next AI initiative.

  • If an AI system recommended a decision today, could you trace exactly which architecture records, risks, and owners it relied on?
  • If a critical application failed tomorrow, do you know every capability, process, and integration that would be affected, resulting in a validated impact assessment rather than a guess?
  • Does your current AI governance process distinguish confirmed evidence from an unverified assumption before it reaches an executive?
  • If your Architecture Review Board asked "who is accountable for this," would every system in scope have a confirmed answer on record?

If any answer was uncertain, the gap is not a lack of AI. It is the absence of a governed context layer connecting AI to the actual structure of your enterprise. That is what the Founding Pilot below is built to demonstrate against your own architecture.

FOUNDING PILOT — LIMITED CAPACITY

Connect this same engine to your real architecture, under controlled scope.

The workspace above runs entirely on a fictional dataset. The Founding Pilot takes the identical graph-traversal engine, evidence classification, and governance workflow and configures it against a defined slice of your actual enterprise architecture, resulting in a working, evidence-linked answer to a real question your organization is facing right now.

ARCHAI Enterprise Architecture MCP™

Founding Pilot

US$25,000

Submitting an application does not create a payment obligation. Selected organizations will receive a scope agreement, contract, and private payment instructions after qualification.

6-week controlled enterprise engagement

Limited to 3 founding organizations

One business domain. Three approved sources. Three high-value architecture use cases. One governed and evidence-linked decision environment.

Apply for the Founding PilotReview What Is Included

Investment

US$25,000

Duration

6 weeks

Capacity

3 organizations

Deployment

Private and read-only

A fixed-scope, US$25,000, 6-week, read-only engagement: we configure the metamodel, ingest an agreed set of your architecture sources, and deliver governed answers to three of your own high-value architecture questions, resulting in a decision-ready brief your Architecture Review Board can act on.

Founding Pilot scope

  • 1 organization
  • 1 priority business domain
  • Up to 3 approved information sources
  • Up to 250 architecture elements
  • 3 configured use cases
  • 1 private, read-only pilot environment
  • 1 Architecture Review Board brief
  • 1 executive findings presentation
  • 1 prioritized 90-day roadmap

Application flow

  1. 1Application submitted.
  2. 2Internal fit, scope, data, and security review.
  3. 3Executive qualification conversation.
  4. 4Scope and contract approval.
  5. 5Private invoice or payment link issued.
  6. 6Initial payment confirmed.
  7. 7Pilot onboarding begins.

Payment terms

Total investment:

US$25,000

Recommended payment schedule:

  • US$12,500 upon signing.
  • US$12,500 before the final executive deliverable.

Alternative enterprise payment terms may be considered for organizations requiring an approved purchase order or procurement process.

Application Portfolio Intelligence

Point the engine at a real capability or business unit, resulting in a dependency map, lifecycle exposure list, and ownership-gap report generated from your own CMDB and application portfolio records.

Architecture Impact Analysis

Ask what would be affected if a specific application, vendor, or technology were replaced, resulting in a multi-level, evidence-classified impact path instead of a workshop full of opinions.

AI Solution Governance Review

Run a real AI system or agent proposal through the same governance dimensions used in the demonstration, resulting in a conditional-approval brief with named gaps, owners, and required validations.

Deliverables

  • A private, read-only pilot instance configured with your enterprise metamodel
  • Ingestion of an agreed set of architecture, CMDB, or risk-register sources (CSV, Excel, JSON, or ArchiMate exchange files)
  • Identity-aware access scoped to your pilot team
  • Governed answers to three of your own architecture questions
  • Evidence, inference, assumption, and gap classification on every finding
  • A dependency and impact map for the selected scope
  • A decision-ready Architecture Review Board brief
  • A written summary of information gaps and required validations discovered during the pilot
  • A findings review session with your architecture and governance stakeholders

Out of scope

  • No production deployment or write access to any source system
  • No integration with systems outside the agreed pilot scope
  • No automated or unsupervised AI agent actions on your architecture
  • No migration of the pilot instance to production without a separate enterprise deployment agreement

Good fit

  • You maintain (or want to maintain) an architecture repository, CMDB, or application portfolio, even if it is fragmented across tools
  • You have at least one AI initiative currently under governance review or planning
  • You have an identifiable Architecture Review Board, governance committee, or equivalent decision-making body
  • You can name a real, current architecture question worth answering

Not a fit if

  • You are looking for a fully automated, unsupervised AI agent with production write access
  • You have no architecture, risk, or ownership records in any form, structured or unstructured
  • You need a multi-year enterprise integration before any first result, with no interest in a scoped pilot

Why now

The Founding Pilot cohort directly shapes the connector priorities, metamodel defaults, and governance workflow that ship in the general enterprise release. Founding participants influence the product and lock in pilot pricing before general availability.

Capacity

Limited to 3 founding organizations per cohort to preserve direct architect involvement in every pilot.

Apply for the Founding Pilot

The workspace above runs entirely on a fictional dataset. The Founding Pilot takes the identical graph-traversal engine, evidence classification, and governance workflow and configures it against a defined slice of your actual enterprise architecture, resulting in a working, evidence-linked answer to a real question your organization is facing right now.

Return to the Workspace

Apply for the Founding Pilot

Sixteen fields. No confidential files required.

I understand that this is a fixed-scope, six-week Founding Pilot with an investment of US$25,000. It is subject to fit, scope, data, and security review and does not include production deployment or write access to organizational systems.

THE ENTERPRISE CONTEXT GAP

AI can access information. That does not mean it understands the enterprise.

Fragmented Architecture

Capabilities, processes, applications, data, technology, owners, risks, and decisions remain distributed across repositories and documents.

Generic Recommendations

AI generates plausible answers without understanding organizational dependencies, constraints, standards, or transformation history.

Invisible Assumptions

Recommendations frequently mix verified facts, interpretations, and missing information without distinguishing among them.

Uncontrolled Agent Access

Agents may retrieve excessive information or act without sufficient permissions, approval gates, ownership, or auditability.

The enterprise does not need another isolated assistant.

It needs a governed context layer connecting AI with the actual structure of the organization.

A STANDARD CONNECTION. AN ENTERPRISE CONTROL LAYER.

Connect compatible AI with authorized enterprise architecture context.

The Model Context Protocol provides a standardized method for compatible AI applications to access external resources and controlled tools.

ARCHAI Enterprise Architecture MCP™ applies that method to enterprise architecture and surrounds it with organizational permissions, evidence, provenance, policies, approval requirements, and human accountability.

MCP provides the standardized connection mechanism. ARCHAI provides the enterprise architecture and governance surrounding that connection.

Resources

Enterprise information the authorized AI can inspect.

  • Business capabilities
  • Value streams
  • Processes
  • Applications
  • Data domains
  • Technology lifecycle
  • Architecture principles
  • Risks and controls
  • Roadmaps
  • Decisions

Tools

Controlled functions the AI can request.

  • Trace dependencies
  • Assess technology obsolescence
  • Evaluate solution compliance
  • Detect architecture gaps
  • Compare current and target states
  • Generate impact analysis
  • Prepare an architecture review
  • Draft a decision record

Governed Workflows

Structured architecture missions.

  • Architecture Review Board preparation
  • Application portfolio rationalization
  • Technology risk assessment
  • AI solution governance
  • Transformation impact analysis
  • Target architecture development
  • Modernization roadmap preparation

Resources provide context. Tools perform controlled analysis. Workflows convert analysis into governed architectural action.

Every response passes through enterprise context and control.

  1. 01

    Understand the Request

    Identify the user, role, objective, organizational scope, and requested action.

  2. 02

    Validate Permission

    Confirm which repositories, domains, records, and tools may be accessed.

  3. 03

    Resolve Enterprise Context

    Map the request across capabilities, processes, applications, data, technology, owners, risks, controls, and decisions.

  4. 04

    Retrieve Evidence

    Access authorized source records while preserving source, date, ownership, and provenance.

  5. 05

    Apply Architecture Intelligence

    Use approved rules, frameworks, metamodel relationships, and controlled analytical tools.

  6. 06

    Present a Governed Result

    Return findings with evidence, uncertainty, risks, affected stakeholders, recommendations, and required approvals.

AI may analyze and recommend. Authorized humans remain accountable.

THE METAMODEL IS THE EXPERIENCE

The answer becomes useful when the relationships become visible.

METAMODEL OBJECTS

Strategic ObjectiveBusiness OutcomeBusiness CapabilityValue StreamProcessOrganizational UnitRole and OwnerApplicationData DomainTechnology ComponentVendorAI SystemAI AgentRiskControlPolicyInitiativeInvestmentDecisionEvidence

SELECTING AN OBJECT REVEALS

  • What it supports
  • What depends on it
  • Who owns it
  • What risks affect it
  • What controls apply
  • What decisions changed it
  • What initiatives are transforming it
  • What evidence supports the record

The user does not need to know where every record is stored. The MCP resolves the relevant context while preserving source traceability and access boundaries.

EXPLAINABLE BY DESIGN

Every important statement must reveal what it is based on.

Evidence

A statement supported directly by an authorized source.

  • Source
  • Record
  • Date
  • Owner
  • Last verified
  • Confidence

Inference

A conclusion derived from multiple pieces of evidence.

  • Supporting evidence
  • Reasoning summary
  • Confidence
  • Required review

Assumption

A proposition that has not yet been verified.

  • Assumption owner
  • Potential impact
  • Required validation
  • Target date

Gap

Information needed for a reliable decision but unavailable, incomplete, contradictory, or inaccessible.

  • Missing information
  • Affected conclusion
  • Responsible owner
  • Recommended action

Classification is never communicated through color alone — every record also carries a text label.

FOUNDING EDITION

Begin with three high-value architecture missions.

Application Portfolio Intelligence

Identify redundancy, lifecycle exposure, critical dependencies, missing ownership, and modernization priorities.

  • Application health analysis
  • Dependency map
  • Technology lifecycle exposure
  • Ownership gaps
  • Modernization candidates
  • Executive portfolio brief

Architecture Impact Analysis

Understand what changes when an application, process, technology, vendor, policy, or AI system is introduced, modified, or retired.

  • Affected capabilities
  • Process and application dependencies
  • Data and integration impact
  • Risk and control implications
  • Affected initiatives
  • Required decisions and approvals

AI Solution Governance

Evaluate whether an AI system or agent fits the enterprise architecture, governance model, risk appetite, accountability structure, and applicable controls.

  • Architecture fit
  • Governance gaps
  • Accountable ownership
  • Human oversight requirements
  • Control and evidence gaps
  • Conditional review recommendations
Launch the Demonstration
CONNECT THE CONTEXT YOU ALREADY HAVE

Works above your repositories, not instead of them.

Architecture sources

  • ArchiMate exchange files
  • Sparx Enterprise Architect
  • LeanIX
  • Ardoq
  • Bizzdesign
  • Architecture decision records
  • Architecture standards

Operational sources

  • ServiceNow CMDB
  • Asset inventories
  • Incident records
  • Change records
  • Service portfolios
  • Technology lifecycle records

Knowledge and delivery

  • SharePoint
  • Confluence
  • Jira
  • Project portfolios
  • Business cases
  • Policies
  • Process repositories

Governance and risk

  • Risk registers
  • Control libraries
  • AI inventories
  • Policy repositories
  • Audit evidence
  • Regulatory obligation records

Founding MVP ingestion

CSVExcelJSONArchiMate exchange filesPDFWordApproved API connections
Supported in Founding MVPPlanned ConnectorAvailable Through Approved APIRequires Enterprise Configuration

Third-party product names describe potential interoperability only. No affiliation or endorsement is implied.

ENTERPRISE CONTEXT REQUIRES ENTERPRISE CONTROL

Access is governed before intelligence is generated.

Identity-Aware Access
Least-Privilege Authorization
Read-Controlled by Default
Human Approval Gates
Source-Level Traceability
Organization Isolation
Audit Records
Data Protection
  • OAuth 2.1 for protected remote deployments where supported and appropriate
  • Role-based and attribute-based access controls
  • Configurable scopes
  • Encrypted transport
  • Secrets management
  • Retention controls
  • Customer-configurable boundaries
  • Private deployment options
  • Customer-approved model and hosting architecture

MCP alone does not guarantee enterprise security. ARCHAI adds the policies, authorization, isolation, evidence, approval, and accountability architecture around the connection.

Three ways to begin, matched to your risk tolerance.

Available

Controlled Pilot

A limited-scope, read-only deployment using fictional, approved sample, or selected enterprise data.

Configurable

Private Enterprise MCP

A protected server configured for the organization’s identity, repositories, permissions, policies, and metamodel.

Planned

Enterprise Intelligence Integration

Integration with ARCHAI Executive Intelligence OS™, architecture workflows, governance, enterprise memory, decision records, and authorized agents.

Make architecture usable when consequential decisions are made.

Faster Impact Analysis

Better Architecture Decisions

Visible Technology Risk

Operational AI Governance

Reusable Enterprise Memory

Consistent AI Context

Start with one architecture question. Scale toward an enterprise context layer.

  1. 01

    Context Discovery

  2. 02

    Founding Pilot

  3. 03

    Private Enterprise Deployment

  4. 04

    Continuous Intelligence

Built inside a complete transformation ecosystem.

ARCHAI WORLD Studio

Builds and operates the product and workspace.

ARCHAI Enterprise and ARCHAITECTS

Provide discovery, integration, governance, private deployment, and enterprise transformation.

ARCHAI WORLD University

Develops enterprise architecture, AI governance, and future MCP professional capability.

ARCHAI Marketplace

May distribute approved connectors, agents, extensions, and specialist services.

ARCHAI WORLD creates the ecosystem.

ARCHAI WORLD Studio builds the tools.

ARCHAI Enterprise implements them inside organizations.

Technology changes the connection. Architects govern what the connection means.

ARCHAI MCP Enterprise Architect™

Planned certification pathway
MCP foundationsEnterprise metamodel designResource definitionControlled toolsWorkflow governanceIdentity and authorizationEvidence and provenanceSecurity architectureHuman approvalEnterprise deploymentArchitecture Review Board integrationOperating model and accountability
Explore Enterprise Architecture Education
FOUNDER AND CHIEF ARCHITECT

Three decades of enterprise architecture. A new context layer for the Agentic Age.

ARCHAI Enterprise Architecture MCP™ is conceived by Leonardo Ramírez, Senior Enterprise Architect, AI Strategist, AI Governance Specialist, Executive Advisor, and founder of ARCHAI WORLD.

AI should not advise an enterprise without understanding the architecture, evidence, constraints, and people behind the decision.

Meet Leonardo Ramírez

Bring one consequential architecture decision.

In six weeks, the Founding Pilot configures a private, read-only architecture context environment for one approved business domain.

US$25,000 · 6 weeks · 3 founding organizations

Apply for the Founding PilotRequest an Enterprise Pilot