๐Ÿง  Signal Stack

System Signal Logo

โ€œA portfolio of systems โ€” real, independent, and enterprise-grade โ€” where architecture meets execution.โ€

The Signal Stack is my deep lab: a space for enterprise case studies, independent platforms, and fictional prototypes.
Here, I document lifecycles, architectural frameworks, and governance models โ€” blending TOGAF, LeanIX, and product strategy into practice.


๐Ÿš€ Enterprise Case Studies

๐Ÿ“‘ EU VAT Compliance Engine

A blockchain-powered VAT compliance system ensuring proof of delivery across EU borders.


๐Ÿ“ก Telecom Reconciliation Platform

Settlement engine for roaming operators, processing billions of CDRs.

TOGAF Lifecycle

  1. Conceive
    • Problem: Months-long roaming settlement with high OPEX + disputes.
    • Vision: Automate reconciliation via blockchain auditability + AI anomaly detection.
  2. Plan
    • Stakeholders: Telcos, regulators, roaming teams
    • LeanIX: Application portfolio โ€” legacy mediation vs. reconciliation modules
    • ArchiMate: Technology + Data flow diagrams
  3. Develop
    • Stack: Hedera Hashgraph ยท Hyperledger Fabric ยท Python anomaly engine ยท Postgres
    • Architecture: AI detects mismatches โ†’ blockchain logs receipts โ†’ smart contracts calculate settlements.
  4. Qualify
    • KPIs: OPEX reduction %, dispute resolution time, % reconciled automatically
    • OKR Example: โ€œReduce dispute resolution time from 60 days โ†’ <15 days by Q2.โ€
  5. Launch
    • Piloted in multi-operator roaming environment
    • Integrated via OSS/BSS APIs
  6. Maximize
    • Added compliance dashboards for regulators
    • LeanIX risk dashboards for blockchain upgrades + AI drift
  7. Retire
    • Archive reconciliation history in distributed storage
    • Regulator-facing lineage proofs

Value


๐Ÿ’ฑ Stablecoin Payment Platform

Cross-border settlement rails using stablecoins.


๐ŸŒ Renewable Energy Infrastructure (REI)

Traceability for renewable energy certificates.


๐ŸŒฑ Independent Platforms

These projects represent my personal exploration of system design, governance, and scale.

๐Ÿ” Neuralic โ€“ AI Governance & Explainability

TOGAF Lifecycle

  1. Conceive
    • Problem: AI adoption lacks audit trails + explainability
    • Vision: Governance stack that makes AI traceable, explainable, regulator-ready
  2. Plan
    • Stakeholders: CIOs, compliance officers, AI leads
    • LeanIX: Map AI services across portfolios
    • ArchiMate: Business โ†’ Application โ†’ Data flows
  3. Develop
    • Stack: Modular services (Neuralic.Core, Neuralic.Trace, Neuralic.Engine)
    • Architecture: Policy store, lineage tracker, explainability layer
    • Security: RBAC, encrypted audit logs, zero-trust APIs
  4. Qualify
    • KPIs: % of decisions logged, % explainable models, compliance coverage
    • OKR Example: โ€œAchieve 100% AI lineage tracking across enterprise ML pipelines by Q4.โ€
  5. Launch
    • MVP open-sourced under SignalBuilds
    • Policy templates + governance docs published
  6. Maximize
    • Cloud integrations (Azure OpenAI, AWS Sagemaker)
    • LeanIX dashboards for model drift + risk mapping
  7. Retire
    • Archive explainability logs
    • Generate governance playbooks for successor AI systems

Value


๐Ÿ“Š Ideas of Scale โ€“ Frameworks for Growth

Essays, models, and frameworks translating TOGAF ADM phases + LeanIX governance into actionable scaling strategies.


๐Ÿ›  Operary โ€“ Industrial Coordination Engine

An API-first engine for industrial teams.

๐Ÿ—๏ธ Concept Experiments


๐Ÿ”ฎ Fictional Blueprints

โ†’ Explore Blueprints in Detail


๐Ÿ“š Signal Frameworks

Frameworks applied across projects:


โ€œThe Signal Stack is where I demonstrate not just what Iโ€™ve built, but how I think โ€” with clarity, governance, and scale.โ€