I founded Chesin with two bets one automates data pipelines with AI, the other reinvents urban mobility with intelligent electric fleets. No demos. Real systems. |
currently = {
"shipping" : "DataSM v1 — Decision Layer",
"target" : "≥ 85% code acceptance rate",
"reading" : "Designing ML Systems",
"open_to" : [
"data engineering roles",
"AI/ML engineering",
"founding team"
],
} |
Built on a dual-brain architecture: LangGraph orchestrates the full pipeline while Claude acts as an adversarial Reviewer, catching hallucinations and enforcing schema correctness before anything touches production. A Decision Layer (replacing the broken weighted-blend merge) arbitrates between agent outputs. dbt + BigQuery as the initial wedge. North star metric: ≥ 85% code acceptance rate. |
Real-time telemetry ingestion, route optimization, and predictive maintenance at scale. Built for the operational complexity of emerging markets where data is sparse and downtime is expensive.
|
↳ more projects
| Project | Description | Stack |
|---|---|---|
| Language Quest | Gamified language learning — progression system, adaptive quizzes, real-time feedback | React, TypeScript |
| Java Forum App | Full MVC application — auth, threads, points system, end-to-end tests | Java, Spring, PostgreSQL, DBUnit, Selenium |
| DataSM Code Review | Automated code review dashboard — dual-agent pipeline (Reviewer + Critic), 5-stage WebSocket flow | React, Python, WebSocket |
| nlp-regras-basico | Study notes: BoW, TF-IDF, Word2Vec, GloVe, RNN, LSTM, GRU + NLPortugues/USP labs | Python, PyTorch |
Real-time multi-agent threat chain detection with LGPD compliance enforcement and cryptographically-signed audit trails. Policy engine with regulatory basis, DPO settings, RoPA (Art. 37), health checks, and a SOC-grade dark UI built for long analyst sessions. Threat severity classification with audit blockchain verification. |
Automated code review system powered by adversarial AI. Dual-agent pipeline (Reviewer + Critic) in 5 stages with real-time feedback via WebSocket. Issues classified by severity critical, major, minor, suggestion — with per-file stats and tree visualization. AMD ROCm dark mode UI. |
↳ full breakdown
| Layer | Technologies |
|---|---|
| AI / LLM | LangChain, LangGraph, RAG, LSTM/GRU, LLM Fine-tuning, Codestral, Claude API |
| Data Engineering | Apache Spark, dbt, BigQuery, PostgreSQL, SQL, ETL/ELT |
| Languages | Python, Scala, Java, Rust, TypeScript, COBOL |
| Backend | FastAPI, Spring Boot, Node.js, REST, MVC |
| Frontend | Javascript, React, TypeScript, HTML/CSS |
| BI | Power BI |
| CLOUD | AWS, GCP, AZURE |
| Infra | Docker, Git, Maven, Tomcat, DBUnit, Selenium, Terraform |