Understand your Enterprise AI Architecture—then improve it in under two minutes.
Start with requirements, an architecture diagram, a repository, or enterprise AI architecture assets. VAIP adapts to your input and produces focused architecture guidance.
1 Upload→2 Analyze→3 Review Results→4 Download PDF
Architecture intelligence that adapts to your input
One focused experience, with different guidance for different starting points.
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Fast Architecture Intelligence
Understand architecture structure, dependencies, risks, and readiness without navigating a complex tool.
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Context-Aware Guidance
VAIP changes its architecture response based on what you provide.
Review the findings first, then create a concise PDF only when it is useful.
Run Demo
See how VAIP changes its findings for four different architecture inputs before uploading your own files.
Each demo uses the same six assessment areas, but its coverage checklist changes for the artifact type. Coverage means the selected input provides evidence for concerns expected from that type of artifact.
Assessment areas: Architecture, Security & Trust, Governance & Compliance, Engineering Fitness, Operations Readiness, and AI Readiness.
GitHub Repository
Claims Service Platform
A Java/Spring service repository with APIs, database access, deployment configuration, and CI/CD evidence.
An AI Agent, MCP, RAG, vector database, AI Gateway, guardrail, and human-approval architecture.
Agent DesignAI SecurityAI GovernanceEvaluationAI OperationsEnterprise AI Readiness
Analyze Enterprise AI Architecture
Upload one input set and run one focused architecture assessment.
What would you like to analyze?
💻 Repository Intelligence
.zip only · maximum 50 MB. Upload a GitHub or project repository archive.
🏗 Architecture Intelligence
.drawio, .vsdx, .png, .svg, .pdf · maximum 15 MB per file.
📋 Requirements Intelligence
.pdf, .docx, .md, .txt · maximum 20 MB per file.
🤖 Enterprise AI Intelligence
.json, .yaml, .yml, .zip, .pdf · maximum 50 MB per file.
Choose the scenario that matches your artifact. VAIP validates file type, file size, integrity, and likely scenario before analysis.
Assessment status
After upload, VAIP starts the architecture assessment automatically and opens Results when it is complete.
Loading assessment state...
Preparing analysis…
Architecture Assessment Results
Scenario-specific findings across six architecture areas.
No completed assessment yet
Upload an architecture input and run the assessment from Analyze.
Review the assessment, then download the PDF when ready.
Architecture Assessment
Architecture Assessment Report
Current assessment
Architecture results are ready for review.
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Architecture coverage
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Coverage across concerns relevant to this artifact type.
VAIP measures whether the uploaded artifact provides evidence for the concerns expected for that artifact type. “Not evidenced” does not always mean the capability is absent; it means the uploaded material did not clearly demonstrate it.
Architecture maturity
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A practical readiness level based on available evidence.
Recommended next diagrams
Recommendations will appear after analysis.
Architecture Gaps
Run the assessment to identify missing architecture concerns.
Top Recommendations
Run the assessment to see recommendations.
Architecture Guidance
Run the assessment to see guidance.
Executive Summary
Run the assessment to prepare the executive summary.
Download
Generate and download one assessment PDF.
SUPPORT, DEMO & ENTERPRISE ENGAGEMENT
How can we help?
Choose the reason for contacting Venara Labs. VAIP sends your request securely to the Request Center and gives you a reference number.
About VAIP
Enterprise AI Architecture Intelligence from Venara.
What VAIP does
VAIP turns architecture-related inputs into architecture assessment, patterns, recommendations, and executive guidance.
Clear product boundaries
Prompt intelligence belongs to PIP. Runtime logs and future OpenTelemetry analysis belong to VRI. VAIP stays focused on Enterprise AI Architecture.
How coverage scores work
VAIP uses a different checklist for repositories, design diagrams, requirements, and Enterprise AI projects. A concern is marked Evidenced when the uploaded material clearly supports it, Partially evidenced when support is incomplete, and Not evidenced when the artifact does not demonstrate it. These indicators guide review; they are not compliance certification.
Common terms
System boundary: what is inside and outside the solution. Trust boundary: where identity or security assumptions change. Resilience: how the system handles failure. Observability: how teams understand system behavior through logs, metrics, traces, and audit evidence.
