I build typed, observable, auditable AI systems for regulated workflows.
Rust · Axum · Tokio · Postgres · OpenTelemetry · RAG · Agents · KYC/KYB/AML
AI prepares. Humans validate. Audit trails prove.
typed workflows > prompt spaghetti domain models > loose JSON blobs audit events > vague logs evaluation > vibes human validation > blind automation observability > guessing permissions > agent free-for-all boring reliability > demo theatre
| Backend | Rust · Axum · Tokio · Postgres · SQL · Background Workers |
| AI Systems | RAG · Structured Outputs · Agents · LLM Orchestration · Evaluation |
| Ops | OpenTelemetry · Tracing · CI/CD · Docker · Cost / Latency Control |
| Domains | Fintech · KYC · KYB · AML · LCB-FT · Regulated Automation |
- Remolab — venture studio infrastructure for AI, fintech, and deep-tech products.
- Welcome Place — fintech and onboarding infrastructure for migrants and newcomers in Europe.
- CaseReady / RavenKYC — supervised AI for blocked KYC/KYB/AML/LCB-FT cases.
- AI Reading Club — foundational LLM papers, discussed from research to production.
- Rust AI Systems — ML, transformers, backend systems, and AI architecture in Rust.
AI systems become useful in serious workflows only when they are: typed observable permissioned evaluated auditable boring enough to trust
I run the AI Reading Club : transformers, attention, BERT, generation, interpretability, scaling, fine-tuning, and alignment.




