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Bogdan0708/README.md

Vasile Bogdan Godja — Applied AI developer

I build TypeScript/Next.js applications, Node.js services and n8n workflows for funding, hospitality and municipal administration. My background in operations leadership and EU-funded delivery helps me turn domain requirements into deterministic rules, controlled AI workflows and useful tests.

I began independent AI work in early 2025 alongside my Mitch from Transylvania food stall. After closing the stall in September 2025, I joined Wilde as a full-time Restaurant Manager; I continue AI development in my spare time, a few hours a day.

Portfolio and CV · London, UK · godjabogdan@gmail.com

Selected projects

Project Engineering evidence Status
EuFund public exhibit Phase transitions, bounded tools, write gates, citation checks and provider failover; 57 tests in the dated September 13 verification. Runnable extract with synthetic fixtures and injected providers. Main platform private and offline.
MitchAI case study Hospitality backend with 193 passing tests, none skipped, in the September 13 verification. Eight n8n workflows exercised through ten synthetic HTTP scenarios. Offline. Model endpoints and database persistence were substituted. Source made private on September 14; credential revocation and history cleanup remain pending.
PrimărIA Next.js/PostgreSQL municipal workflows: forced RLS across 34 tenant tables, deterministic tax modules and XML exporter fixtures. 318 offline tests plus 9 real-PostgreSQL isolation tests, both run in CI. Offline portfolio implementation. Database tests run under a restricted role. No municipal adoption or compliance certification claimed. PrimatIA is the repository slug for PrimărIA.

Supporting work

  • Grant Scout: cited funding retrieval and deterministic eligibility over a dated 30-record snapshot; 48 offline tests. The recorded provider evaluation and tool-compliance result are separate from unit-test CI. Deployment pending.
  • Review Responder: approval tied to the reviewed reply version, publication fencing and uncertain-outcome reconciliation. Offline demo.
  • AI Gateway: provider routing, spend controls and failure handling. Offline implementation; no hosted demo offered.
  • Local AI Gateway and Local LLM MCP: local retrieval, model tools, queueing and telemetry; scope and reproduction instructions in each repository.
  • Veloce fare engine: deterministic pricing and DST handling extracted from a private transfer-operator project.

Dated tests and synthetic execution demonstrate specific engineering behaviour. They do not establish production operation, client adoption or measured business outcomes. Source, scope and reproduction notes accompany each project.

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