ZeroIndex is an AI-native software consultancy. Production applications, APIs, and data platforms — accelerated by Claude — plus AI adoption that gets teams shipping faster. Reviewable code, real observability, true CI/CD. Not pilot decks.
A 2–3 week, fixed-fee assessment of where Claude and adjacent AI tools fit your stack — and where they don’t. You leave with a prioritized roadmap and an opinionated build-or-buy call — not a sales deck.
Production-grade applications, APIs, websites, and data platforms — 21 years of engineering, Claude as the velocity multiplier. Senior judgment, reviewable code, real observability. From MVP to multi-quarter engagement.
Hands-on enablement for teams and businesses adopting AI to accelerate the work that matters. SDLC, workflow automation, internal tools, MCP integrations — measurable velocity, not pilot decks.
Four steps from first email to clean hand-off. No surprises, no lock-in.
A 30-minute call. You describe the problem and constraints. I tell you whether ZeroIndex is the right fit — and if not, where to look instead.
A fixed-fee SOW with milestones, deliverables, IP terms, and clear exit conditions — written before any code is.
Continuous delivery. Every merged PR ships to production. Evals catch regressions. You see progress as it happens — not at the end.
Documentation, runbooks, an on-call playbook, and a working session with your team. Code that outlasts the engagement stays with someone who can change it.
The kinds of problems Claude and adjacent models solve well — and where ZeroIndex tends to operate.
Embedding Claude and adjacent LLMs into user-facing products — production-grade integration, not chat widgets glued on top.
Building data platforms that move at scale — pipelines, warehouses, lakes — with LLM-powered insights, natural-language interfaces, and semantic retrieval on top.
Monitoring, evals, and tracing for production AI — so you know what the model did, why, and what to do when it drifts.
Establishing AI-first SDLC at the org level — code generation, automated PR creation, AI-augmented test and release workflows. Track record of absorbing major workload growth without proportional headcount increases.
Classification, triage, summarization, and routing — the rules-based work that LLMs do better.
Extract structured data from contracts, invoices, forms, and other unstructured documents.
Every project here is public and built the way client work is — tested, typed, CI on every commit, dogfooded before it ships. The first user is always me.
Point it at any public GitHub repo and it runs a multi-phase AI investigation — exploring the code, forming findings, and citing every claim back to specific files and lines, streamed to you live.
Pulls structured fields out of contracts, invoices, and forms — every value cited back to the source page of the original document.
Detects and redacts PHI from clinical documents and free-text notes, with a reviewable audit trail for every redaction.
A published npm toolkit for writing and running LLM evals — because “it worked on my prompt” isn’t a test.
Tracing for LLM applications — every call, prompt, and outcome is inspectable, so you catch drift before your users do.
Four published Model Context Protocol servers (Porkbun, Mercury, GitHub, Turso), plus a recipe for shipping a new one in a day.
Retrieval-augmented Q&A grounded in source content, with citations. It’s the widget powering the Ask section on this site.
A durable, crash-safe project-intake pipeline on Vercel Workflow — resumable steps, retries, and a typed admin view.
Career-to-date metrics from prior engineering leadership roles.
Production stack from 21 years of shipping. Claude-first on AI — deliberate concentration, expanding with each engagement.
Senior engineer and engineering leader with 21 years of experience building APIs, applications, websites, and enterprise systems — currently pioneering AI-first SDLC adoption at organization scale.
ZeroIndex applies that delivery discipline — reviewable code, real observability, honest tradeoffs — to every engagement. The senior engineer your contract names is the one writing the code, and the one on-call when it breaks.
Twenty-one years in, and I’m still curious about what comes next.
Model output is an input, not a product. Code that ships is read, reviewed, and tested — like any team that takes itself seriously.
Continuous delivery, real observability, true CI/CD — not a slide deck and a Loom video. The work isn’t done until on-call knows what to do at 3am.
Including when it’s not the right tool. Selling an LLM to solve a deterministic problem is the fastest way to lose a client’s trust.
Answers are grounded in this site’s content, with sources cited.
Tell me about the problem and the constraints. If it’s a fit, I’ll scope the work — if not, I’ll point you elsewhere.