ArtJeck is a one-engineer software and AI studio. I design, build, and test custom web, mobile, and AI products — done right, and you own the code outright.
I matched a carrier's official tax filing to the penny.
An AI filing pipeline I designed and built, backed by 429 automated tests and running in production for a real client.
429
automated tests
Exact
filing match
Live
in production
Six things, done to one standard — and on every one, you work directly with the engineer building it.
AI that holds up in production, not just the demo.
Custom agents and assistants that answer from your own documents and take real work off your team's plate. Built with evaluations and guardrails, so accuracy holds when real customers are the ones asking.
Fast, custom sites and web apps you actually own.
Websites and web apps built clean, quick, and exactly to your brand — no templates, no monthly fees holding your site hostage. The code is yours from day one, built to grow with you.
Mobile apps from first idea to the App Store.
Native iOS apps in SwiftUI and cross-platform builds that feel at home on every device. I take you from a focused MVP to a tested production release — your app, your code, your roadmap.
Catch the bugs before your customers do.
Independent functional, regression, and edge-case testing on software you or another team built. You get a clear written report of what breaks and why — a senior second set of eyes before you put your name on it.
Your business data in one place, finally connected.
Databases set up, migrated, and connected — spreadsheets turned into real systems, your tools talking to each other through their APIs, and messy documents like PDFs and invoices extracted into clean, structured data.
Starting at
$1,500fixed scope · $90/hr after
Get found on Google — and know what's working.
Technical SEO that makes Google actually understand your site: structured data, local pages, speed, and clean indexing. Plus analytics done right — GA4, Search Console, and a dashboard that shows where customers really come from.
Starting at
$1,000audit + fixes · $90/hr after
Each one is live, tested, and open to inspect — the actual deliverables, not mockups. I lead with the outcome, then show how it was built.
Trucking carriers spend hours every quarter reconciling fuel and mileage data, hand-typing per-state lines into the gov portal, and second-guessing whether the math matches what the state will recompute.
An end-to-end pipeline that ingests raw mileage and fuel files, computes a state-portal-ready return with exact CDTFA math, and runs an AI agent over it to flag missing surcharges, MPG anomalies, and audit-bait patterns before filing.
Python, pandas, openpyxl, pdfplumber, Anthropic Claude, multi-tenant client registry, per-truck Excel deliverables
429 automated tests, including a real-data backtest that matches a Kentucky carrier's official CDTFA filing to the penny.
A real client (DM Express, KY) files quarterly through the pipeline, with an AI review note and concrete next steps before each filing.
A resale business sells the same inventory across many marketplaces at once. Listing each item by hand on every platform — and keeping prices and 'is it still listed?' in sync — is slow, repetitive, and error-prone.
A cross-posting engine that describes an item once in a normalized model and publishes it to every marketplace through one uniform adapter interface — with bounded retries, fast-fail on rejections, and idempotency so a scheduled re-run never double-posts.
Python, adapter-pattern marketplace clients, deterministic listing generation, SQLite listing ledger, retry/backoff orchestration; the production system spans six marketplaces behind private adapters
The public clean-room showcase ships 14 tests over the retry state machine, permanent-vs-transient handling, idempotent skips, partial-failure reporting, and the deterministic listing rules.
In progress for a live, revenue-generating client (anonymized). A sanitized showcase of the architecture is public and runs end-to-end on synthetic data; the production code and integrations stay private.
A jewelry brand needed a real online store — catalog, reviews, promotions, and self-service management — without a monthly platform fee or a dashboard to learn.
A full Next.js storefront with a product catalog, image galleries, reviews, stock, a Buy-Now flow, and token-based personal offer links — plus a secured admin where the owner manages everything themselves.
Next.js, React, TypeScript, Prisma + libSQL (Turso), Vercel Blob uploads, Tailwind CSS, TOTP two-factor admin
Admin gated behind two-factor auth, validated image uploads, and cached queries for fast product pages; storefront and admin flows tested end to end.
A live store the owner runs themselves — add products, publish reviews, send personal offers — with no recurring platform cost.
A small trucking company needed a credible, fast, phone-friendly site to help recruit drivers.
A one-page React/Vite site with light and dark themes, animated sections, and a structured driver application flow.
React, TypeScript, Vite, Vitest, mailto application flow, Vercel
29 tests using equivalence partitioning, boundary value analysis, decision tables, and state transition testing.
A real client site tuned for iPhone, accessibility, and a sub-500KB first load — now their front door for recruiting drivers.
Cloud AI assistants send your notes, docs, and client files to someone else's servers, and answer without showing where the answer came from — a non-starter for sensitive or auditable work.
A local-first RAG assistant that ingests your own notes, docs, and code and answers only from them, with every claim cited to its source. Free local models by default; one flag routes the answer to Claude.
Python, OpenAI-compatible LLM API, Qdrant / Chroma vectors, LangGraph workflow, MCP server (stdio + token-gated HTTP)
An eval harness over a synthetic regression corpus — retrieval hit-rate, grounded-answer checks, and abstention cases — plus a pytest suite.
Open source and in daily use; exposed over MCP so Claude Desktop and Claude Code can query and teach it directly.
Operating a multi-machine AI lab from anywhere usually means SSH and a raw shell — powerful, but reckless to hand to an autonomous agent.
An MCP server that gives any agent safe “hands” on the lab: health checks, model management, free local inference, and a deliberately gated remote shell — allowlist only, no shell metacharacters, hard timeouts.
Python, MCP (stdio + token-gated HTTP), httpx, subprocess argv (no shell=True), launchd, Tailscale
A pytest suite covering the command-gating safety logic, runnable offline.
Open source and running around the clock; an agent can operate the lab from an iPad while the dangerous operations stay locked behind validated tools.
Daily inbox review was noisy and manual, with important messages mixed into low-priority mail.
A local agent that pulls mail over IMAP, uses a local model to triage and summarize, then sends a Telegram digest.
TypeScript, Node, imapflow, mailparser, Ollama, SQLite, Telegram Bot API, launchd
Test-connection and dry-run paths, SQLite dedupe for idempotency, and cost reporting per run.
A self-hosted morning digest that runs on schedule, entirely on local models at $0 API cost.
Bills of lading are still often reviewed and keyed by hand, which slows operations and creates avoidable data-entry risk.
An in-progress extractor that turns BOL documents into structured shipment data with validation and review-ready output.
OCR / document parsing, LLM structured extraction, JSON schema validation, field checks, export workflow
Planned around sample BOL fixtures, required-field checks, edge-case documents, and regression tests for extraction quality.
In progress: designed to cut manual BOL entry and make shipment data easier to review, reuse, and automate.
Premium pricing buys senior hands, real testing, and code you own outright — so you pay once and keep what you get.
The person who scopes your project is the one who builds it. No account managers in the middle, no junior developers learning on your budget.
Scope and price are agreed before work starts. You know what you're paying and what you're getting — no surprise invoices halfway through.
Testing isn't an afterthought bolted on at the end. It's how I work, so bugs surface in my hands and not in front of your customers.
All the code, all the accounts, all yours. No lock-in, no licensing traps, no monthly fee to keep your own product running.
Six steps from the first call to long after launch — so you always know what's happening, what it costs, and what comes next.
I learn your business, your users, and what success looks like before writing a line of code.
I design the system and we agree on scope and a fixed price, so there are no surprises later.
I build in clean, documented code that's yours to keep, and keep you in the loop the whole way.
I test against the edge cases and write up exactly what I found and fixed — before your customers see it.
I ship it live, hand over every key and credential, and make sure it holds up under real use.
I stay close after launch to refine, extend, and grow what we built together.
I treat design, build, and testing as one job, not three handoffs — because the seams between them are where most software quietly breaks. I'm the same hands from sketch to ship, so the details line up.
Testing discipline is my edge. On one AI project — an IFTA tax-filing automation — I wrote 429 automated tests and ran a real-data backtest that matched a Kentucky carrier's official filing to the penny. I'd rather find the problem in a test than have you find it in production.
Working with me is direct. You talk to the person doing the work, you get honest answers about what's hard and what's worth it, and you leave owning software you understand.
Senior hands on your project, start to finish
Built to be maintained, not just launched
Tested against real-world edge cases
Plain answers and a clean handoff
Your AI can run on a private, self-hosted stack I build and operate — free local models by default, paid cloud only when it earns its place. For you that means lower running costs, real data privacy, and no surprise bills.
Every AI call runs through one gateway with automatic failover and a hard spend cap — so an automation can't quietly run up a bill against you.
Always-on machines run free local AI for chat, code, and search, with a vector index and database holding your project's knowledge — no per-token meter ticking.
Everything sits on a private network — nothing public — and the services stay up around the clock, so what you depend on is there when you need it.
Private by default — nothing is exposed to the public internet.
Three disciplines, one engineer, no handoffs between them.
AI that answers from your own documents and runs your workflows — on private infrastructure with local models, automatic failover, and hard spend caps, so it stays accurate, private, and predictable.
Fast, custom websites, web apps, and mobile apps in modern, maintainable code that's entirely yours to keep.
I test the way your customers will, then harder — functional, regression, and edge-case coverage with clear written reports.
Service areas
ArtJeck is based in Sacramento and works with businesses across Northern California: AI automation services in Sacramento, AI automation for San Francisco startups, AI automation across the Bay Area, and computer repair in Sacramento and six nearby cities. See the full AI automation services overview.
Tell me what you're building and where it's stuck. I'll tell you straight whether I'm the right engineer for it — and what it would take to do it right.
Work with me if you