Real-estate market intelligence
Public housing data turned into a ranked target list, scored and running live on a schedule. Delivered, then kept running on my own infrastructure.
Track record · Upwork & beyond
A perfect client rating across every engagement. A paid security bounty from Anthropic. Named credit in a published architecture reference. A fix merged into the container runtime behind Podman and CRI-O. Everything here is independently verifiable, none of it is a claim you take on faith.
In writing · one contract, start to finish · 72 seconds
For more than ten years I've worked inside private companies on tightly-scoped problems, some involving government data, under confidentiality that outlasts the contract. That work stays private, and always will, so the engagements below are described by their shape, not their client names.
Discretion with sensitive data is part of what you hire, not a footnote to it.
01 Client reviews
Every engagement · 5.0 · verified on Upwork
Real-estate market intelligence
Public housing data turned into a ranked target list, scored and running live on a schedule. Delivered, then kept running on my own infrastructure.
Legal research data collection
Two years of public forum discussion, 3,221 threads and 58,686 comments, delivered with a completeness report the client reconciled against the raw file himself.
Data cleansing at scale
A configuration-driven cleansing pipeline for a large product dataset. Same rules, any catalog, no hand-editing.
Healthcare data extraction
7,010 physician records pulled clean from a bot-protected registry, structured and de-duplicated for direct use.
Pricing extraction
Live pricing pulled across multiple print vendors and normalized into one comparable structure.
Insurance form automation
A fillable Medicaid claim form (eMedNY), field-mapped and validated so it fills correctly every time.
02 Validation
External · verifiable · by name
I disclosed a real security flaw through Anthropic's own program. They validated it and paid the bounty. It sits inside a broader track record of coordinated vulnerability disclosures across multiple programs, none dismissed.
Invited as a technical reviewer on a decision-centered reference architecture for trustworthy agentic commerce, now published on arXiv. The paper credits me by name for sharpening how AI-generated claims carry their own limits: the propagation of inherited refusal through derived claims, and a cleaner separation of the axes each surface projects onto.
Read the paper on arXiv ↗crun's passwd parser tested for a digit with a signed comparison that had no lower bound, so 186 of the 256 possible byte values kept the loop running, the null terminator among them. A line with an empty uid field walked the parser past the end of the buffer. The correct version came from musl in June 2020 and lost that lower bound 43 minutes later, in a commit that removed one character to silence a warning on the Alpine build, which is where the affected path compiles. Traced back to that commit and fixed. Reviewed and merged by the project maintainer.
Read the merged pull request ↗Receipts. Redacted where a coordinated disclosure is still in progress.

Reported by me, coordinated disclosure in progress. Mechanism redacted until it ships.

Credited collaborator on the advisory. Mechanism redacted until it ships.
03 Selected work
Open source · clean-room builds · public on GitHub
04 Beyond the platform
Products shipped & authored
A production SaaS in daily use by more than 1,000 businesses. Built and maintained end to end.
A live app on the Apple App Store, taken from web stack to store through a hybrid build.
A trust-first local-services marketplace for Brazil’s countryside towns. Full KYC before anyone is listed: document, liveness selfies, face match and three criminal-record registries, automated at under R$1 per verified worker.
See it ↗A free 84-page field manual on applied AI: RAG, agents, evaluation, and three end-to-end capstones.
Read it ↗