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Blueprint scope selection

Blueprint scope selection

Blueprint Scope Selection

Purpose

The SuperAI SuperBlueprint aims to define open, interoperable, and production-ready reference architectures for AI systems. This document establishes the criteria and process for selecting initiatives, technologies, and workstreams to be included in the Blueprint.

Selection Principles

A Blueprint candidate should satisfy one or more of the following objectives:

Strategic Importance

  • Addresses a significant industry challenge.

  • Supports enterprise, sovereign, telecom, edge, or cloud AI adoption.

  • Enables ecosystem collaboration.

Community Demand

  • Requested by multiple community members.

  • Demonstrates active contributor interest.

  • Has clear adoption potential.

Technical Innovation

  • Introduces new capabilities.

  • Advances open AI infrastructure.

  • Improves interoperability between platforms.

Reusability

  • Applicable across multiple industries.

  • Can serve as a reusable reference architecture.

  • Encourages standardization and best practices.

Scope Categories

Category A: AI Infrastructure

Examples:

  • GPU Infrastructure

  • AI Factories

  • Cloud AI Platforms

  • Sovereign AI Infrastructure

  • Edge AI Infrastructure

  • AI Networking

  • AI Storage

Selection Criteria

  • Production deployment potential

  • Multi-vendor interoperability

  • Scalability

Category B: Agentic AI

Examples:

  • Multi-Agent Systems

  • Agent Orchestration

  • MCP Integration

  • Agent Marketplace

  • Autonomous Workflows

Selection Criteria

  • Open interfaces

  • Tool interoperability

  • Governance and security considerations

Category C: Data, Memory & Knowledge

Examples:

  • Vector Databases

  • AI Memory Systems

  • RAG Architectures

  • Knowledge Graphs

  • Data Governance

Selection Criteria

  • Data portability

  • Privacy and compliance

  • Performance and scalability

Category D: Industry Solutions

Examples:

  • Telecom AI

  • Manufacturing AI

  • Financial Services AI

  • Healthcare AI

  • Public Sector AI

  • Retail AI

Selection Criteria

  • Industry relevance

  • Reusable architecture patterns

  • Business value

Category E: Physical AI

Examples:

  • Robotics

  • Autonomous Systems

  • Digital Twins

  • Industrial Automation

  • Edge-to-Cloud AI

Selection Criteria

  • Real-world deployment

  • Safety requirements

  • Edge integration

Evaluation Matrix

Criterion

Weight

Criterion

Weight

Strategic Impact

25%

Community Interest

20%

Technical Feasibility

20%

Ecosystem Value

20%

Resource Availability

15%

Minimum score for Blueprint inclusion: 75/100

Selection Process

Step 1 – Proposal Submission

Project sponsor submits:

  • Problem statement

  • Scope definition

  • Expected outcomes

  • Resource requirements

Step 2 – Initial Review

Conducted by:

  • Blueprint Working Group

  • Technical Steering Committee representatives

Step 3 – Scoring

Evaluate against the selection matrix.

Step 4 – Recommendation

Working Group recommends:

  • Approve

  • Approve with modifications

  • Defer

  • Reject

Step 5 – TSC Approval

Final approval by the Technical Steering Committee.

Current Candidate Workstreams

  1. AI Infrastructure Blueprint

  2. Sovereign AI Blueprint

  3. Agentic AI Blueprint

  4. AI Memory Blueprint

  5. Edge AI Blueprint

  6. Telecom AI Blueprint

  7. Physical AI Blueprint

  8. AI Benchmark & Validation Blueprint

  9. AI Governance & Security Blueprint

  10. Open agent Marketplace Blueprint

  11. AI Operations Blueprint

Success Metrics

  • Number of approved blueprints

  • Number of participating organizations

  • Number of reference implementations

  • Production deployments

  • Community adoption

  • Contributor growth