SAP LeanIX now offers AI-generated custom reports directly in the solution. Ruslan Shogenov takes us through the value of this new capability.
Enterprise architecture is about translating complex technology landscapes into actionable insights for stakeholders. Understanding vast amounts of data across an organization's IT landscape is challenging, but communicating that understanding to the decision-makers who need it is equally demanding.
Every stakeholder views enterprise architecture through a different lens:
What answers a CIO's strategic question about portfolio optimization may not address a business unit leader's operational concerns about technology enablement
What satisfies an audit team's compliance requirements differs from what a transformation office needs to track migration progress
The ability to deliver insights through visualizations tailored to each stakeholder's specific context and decision framework is what makes enterprise architecture strategically relevant to the organization. To find out more about SAP LeanIX' new custom reporting capabilities, book a demo:
Reports transform architecture data into decisions. They provide the visibility that enables leaders to understand where the organization stands, what risks exist, and what actions to prioritize.
This translation from data to insight to action is what makes enterprise architecture strategically relevant to the organization. Standard reports address common scenarios that apply across organizations, but transformation initiatives are unique to each enterprise.
Each organization has its own strategic priorities, risk tolerance, regulatory context, and operational constraints. Visualizations that support transformation decisions must reflect these unique factors, combining data in ways that align with how that specific organization makes choices.
This is where custom reporting becomes essential.
Architecture teams understand what visualizations their stakeholders need and they know which data relationships matter for specific decisions. The challenge is where those reports live and how they integrate with architecture workflows.
Organizations can export data to external tools like Power BI or Tableau to create custom visualizations, but this approach fragments architecture data away from the platform where it is managed. The reports exist separately from the fact sheets, relationships, and assessments that architects work with daily.
Updates require manual data exports. The rich relational context gets flattened into disconnected data extracts.
Building custom reports directly within enterprise architecture platforms requires coding expertise that most architecture teams lack. This creates a choice: accept the fragmentation of external tools, or queue requests in developer backlogs where they compete with other technical priorities.
Architecture teams understand what visualizations their stakeholders need and they know which data relationships matter for specific decisions. The barrier has traditionally been technical implementation:
Building custom reports requires specialized coding expertise that most architecture teams do not possess. This creates dependency on scarce developer resources:
Development timelines stretch into weeks
Architecture teams face a backlog of unfulfilled visualization requests
Stakeholders either wait for reports that may never arrive, or they export data to external tools where the rich relational context of enterprise architecture gets lost
When reports do not arrive in the timeline that decisions require, business leaders rebuild data manually in presentations. This introduces errors, loses the authoritative source of truth, and diminishes the strategic value that enterprise architecture should deliver to the organization.
When the people who understand stakeholder questions can build the visualizations that answer those questions, the strategic relevance of enterprise architecture increases. The timeline from question to deployed answer compresses from weeks to hours. The backlog of unfulfilled requests diminishes.
Accessible custom reporting shifts the bottleneck from technical implementation to business understanding. Architecture teams can respond to stakeholder needs directly, without waiting for developer capacity.
Organizations maintain their architecture data as the authoritative source rather than fragmenting it across external tools where context gets lost. This democratization of report creation means insights flow to decision-makers in the timeline those decisions actually require.
SAP LeanIX now provides Custom Reports via MCP Server, enabling enterprise architects to build tailored visualizations by describing what they need in natural language. By connecting AI assistants to your SAP LeanIX workspace, report creation becomes accessible to anyone who understands what stakeholders need, not just those with coding expertise.
The Model Context Protocol (MCP) acts as a bridge that gives AI assistants like GitHub Copilot, Claude Code, and Cline direct access to your enterprise architecture data. When connected, your AI assistant understands your workspace structure, data relationships, and organizational terminology, allowing it to generate reports that reflect how your organization actually works.
This transforms the custom reporting experience. Instead of writing code or explaining requirements to developers, architects describe what they need in plain language.
The AI assistant creates the report automatically and development timelines compress from weeks to minutes. The technical barrier that has historically limited custom reporting to specialists dissolves.
Architecture teams can now respond to stakeholder reporting needs directly, without developer dependency. Enterprise architecture data becomes accessible through custom views that answer specific business questions, delivered in the timeline transformation decisions actually require.
The workflow is straightforward. You connect your AI assistant to SAP LeanIX through the MCP Server.
When you need a custom report, you describe what you want to visualize in natural language. Your AI assistant generates code based on your workspace data and organizational structure.
You review the generated report, request refinements through further conversation, and publish the report to your workspace. The reports integrate with SAP LeanIX's existing access controls, so stakeholders see only the data they have permission to view.
By providing AI assistants with direct access to workspace data through the Model Context Protocol, SAP LeanIX enables architects to work with their architecture data in new ways. The same connection that enables custom report generation creates possibilities for other scenarios where architects understand what they need but lack coding expertise to build it themselves.
When AI assistants can understand enterprise architecture context, they can generate solutions that reflect how specific organizations work. The barrier between understanding what should be built and having the technical skill to build it diminishes.
As AI assistants become standard tools in enterprise architecture practice, connecting them to authoritative data sources transforms how architects translate insights into artifacts that drive decisions.
Custom Reports via MCP Server represents a shift in how enterprise architecture teams deliver insights to stakeholders. When the people closest to the data can create the visualizations that communicate its value, the timeline from question to answer compresses and the strategic relevance of enterprise architecture increases.
This capability reflects our commitment to making enterprise architecture more accessible. As AI assistants become standard tools in knowledge work, connecting those assistants to your architecture data creates new possibilities for turning insights into decisions.
To find out more about customer reports in SAP LeanIX, book a demo: