Sebastien Henry@sebastien_henry7
3
Events attended
2
Submissions made
United States
2+ years of experience
About me
Senior data & AI engineer based in Austin, TX, with deep roots in the modern data stack — Snowflake, dbt, Python, and AWS — and a growing obsession with agentic AI systems built on LangChain and LangGraph. By day I architect data platforms and analytics pipelines. On the side, I'm building AI-powered applications, exploring multi-agent workflows, and looking for hackathons where I can ship something real with people who care about what they're building. My sweet spot is the intersection of structured data and generative AI — think RAG pipelines over warehouse data, AI agents that actually do something useful, and automation workflows that replace hours of manual work. Always up to team with engineers, product thinkers, and builders who move fast and build things worth showing. Stack: Python · Snowflake · dbt · LangGraph · n8n · AWS · Tableau
🤓 Latest Submissions
HireGuard — AI Hiring Compliance Auditor
HireGuard is a multi-agent compliance auditor built on Band. A single command feeds a hiring packet — job posting, comp band, and interview scorecard — into a Band room where four specialized agents hand off work through @mentions. @Intake (LangGraph) extracts structured facts from the raw artifact and writes them to facts.md. @PolicyAgent (LangGraph) cross-references every fact against a 10-rule EEOC and pay-transparency ruleset, appends cited findings, then hands off to @RiskScorer. @RiskScorer (CrewAI) calls the AI/ML API for each finding to score legal exposure on a 0–100 scale, weighing severity, litigation likelihood, and jurisdiction attachment, then writes risk.md. @Counsel (CrewAI) adversarially validates Critical findings, bounces thin cases back to @PolicyAgent for a visible re-loop, and writes the final audit.md — a defensible memo with statute citations and a human sign-off gate. The AI/ML API is load-bearing: no finding gets a risk score until that call returns. Agents coordinate through Band @mentions; content lives in shared workspace files, keeping chat lightweight and auditable. The ruleset covers Federal EEOC law (ADEA, Title VII, ADA, disparate-impact doctrine) and state pay-transparency statutes in California (SB 1162), New York (LL 194-b), and Colorado (EPEWA). The demo packet ships with pre-planted violations — age-proxy language, a salary-history question, a missing CA pay range — producing a HIGH verdict with six cited findings on first run. EEOC charges cost U.S. employers $440M+ in 2023 and pay-transparency penalties are accelerating. HireGuard makes compliance audits fast, repeatable, and traceable.
19 Jun 2026
DealPulse Scout — AI Agent for Live Car Deals
Finding a genuine car deal is a manual, frustrating process. Buyers spend hours cross-referencing listings across five platforms, guessing whether a price is actually below market — and by the time they act, the deal is gone. DealPulse Scout solves this with a LangGraph multi-agent pipeline powered entirely by Bright Data's live web infrastructure. A single natural-language query ("Find me a used 2022 Tesla Model 3 under $28k in Austin TX") triggers a coordinated scraping run across CarGurus, AutoTrader, and Craigslist using Bright Data's Scraping Browser and Web Unlocker to bypass bot detection and JavaScript rendering. A parallel SERP API call pulls real-time market pricing data for that exact make, model, trim, and mileage range. A scoring agent then computes a 0–100 deal score by comparing each listing's price against the live market average, factoring in listing freshness and mileage deviation. Claude claude-sonnet-4-20250514 generates a one-line plain-English reason for every top result. The entire flow streams live in the UI — judges and users see each agent node activate in real time. A demo mode backed by SQLite cache ensures the experience is reliable under any network condition. Built solo in under 24 hours. The same infrastructure directly powers DealPulse, a live car-deals business — this is not a toy demo, it is the production intelligence layer.
31 May 2026
