Case Studies — Neuron HQ | Four shipped AI products Skip to main content
Case Studies

Four products. All shipped.

These are the real apps Neuron HQ has designed, built, and put into people's hands — not concepts, not mockups. Each one started as someone's idea and ended as working software, with every line reviewed by a senior engineer. Below: the problem each one solves, what we built, and the capability it delivers. We describe what's real and skip the inflated numbers.

Fixed price · You own the code · First version in ~2 weeks · Powered by our Neuron engine
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4 products shipped
Real, working software in real domains — learning, spa operations, construction finance, and the job hunt.
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Powered by Neuron
The same in-house engine — AI drafting, real tutors, automation — runs across every build, so each new product starts ahead.
Senior-reviewed — every line
Veracode's 2025 GenAI Code Security Report found 45% of AI-generated code contains security flaws. A senior engineer reviews ours before it ships.
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Case study · 01 · Live

Neuron Academy

An AI learning platform built so the knowledge actually sticks — and the flagship demonstration of what the Neuron engine can do.

150
Lessons
12
Tracks
SM-2
Spaced repetition
$0
Free tier · Pro $19/mo
The problem

Most online courses get abandoned, and most AI courses are stale within months because the field moves faster than the curriculum. People watch lessons, then forget the bulk of what they learned within a week. The hard part isn't access to content — it's retention and staying current.

What we built

A mobile-first learning app with 150 lessons across 12 tracks, wired to a real Claude tutor that knows your progress, studio-quality voice narration on every concept, and an Anki-style spaced-repetition scheduler that resurfaces lessons at expanding intervals. Track capstones are AI-graded against a rubric.

The outcome

A live product with a free tier and Pro at $19/month. It issues cryptographically signed (ECDSA P-256), publicly verifiable certificates, runs offline as an installable PWA, and updates as new models ship. It's the proof case for the Neuron engine the rest of our work is built on.

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Case study · 02 · Shipped

Spa Owner HQ

An operating system for spa and med-spa owners — booking, operations, and marketing in one AI-native app instead of a stack of disconnected tools.

The problem

Spa and med-spa owners run their business across a patchwork of apps — one for booking, another for client follow-up, a third for social posts and promotions. Nothing talks to each other, the owner becomes the integration layer, and the day disappears into copy-pasting between tabs instead of serving clients.

What we built

A single AI-native app that consolidates the core jobs of running a spa: appointment booking and scheduling, day-to-day operations, and marketing automation. The AI layer drafts client communications and marketing content in the owner's voice, so routine outreach stops being a manual chore.

The outcome

A shipped product that replaces several point tools with one system built specifically for spa and med-spa owners — the booking, ops, and marketing work that used to be scattered now lives in one place, automated where it can be.

Want something like this for your business? We build custom →
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Case study · 03 · Shipped

Top Builder AI

Eight self-learning AI agents that install on the ServiceTitan a contractor already runs, and out-agent ServiceTitan's own. They run the back office ServiceTitan never automated: money, materials, people, and paperwork.

The problem

ServiceTitan runs a contractor's field operations, but the back office it never automated (money, materials, people, and paperwork) still gets stitched together by hand across QuickBooks and spreadsheets. Usually too late to act on, and rarely with the clarity a full-time operator would bring.

What we built

An AI back office of eight self-learning agents that install on ServiceTitan (plus QuickBooks and nine other field-service platforms), out-agent ServiceTitan's native booking and dispatch, and run advisory by default: they propose, the operator approves, with full undo and audit. Every dollar figure is deterministic, tested code the learning layer cannot touch.

The outcome

A shipped product that gives contractors a board-ready back office on top of the ServiceTitan they already run: agents that get sharper every week from what the operator approves and edits, with every number locked to tested code.

Want something like this for your business? We build custom →
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Case study · 04 · Shipped

JobScout

An AI job-search copilot that does the tedious, repetitive parts of applying — resume tailoring, cover letters, and compensation research — so a job seeker can apply faster and smarter.

The problem

A serious job search means tailoring your resume to every posting, writing a fresh cover letter each time, and trying to figure out what a role actually pays. Done well, it's hours of repetitive work per application — so most people either cut corners or burn out before they find the right fit.

What we built

An AI copilot for the job hunt that tailors a resume to each specific posting, drafts a matching cover letter, and surfaces compensation intelligence so applicants know the market rate going in. The grunt work of applying is automated; the human stays in control of every submission.

The outcome

A shipped product that compresses the per-application busywork into a guided, AI-assisted flow — letting job seekers send stronger, better-targeted applications without spending hours rewriting the same documents for every role.

Want something like this for your business? We build custom →
Proven in the field

What these systems actually deliver.

The same building blocks we ship — an answer-on-the-first-ring front desk, instant lead follow-up, and automatic appointment reminders — have a long, documented track record of recovering revenue for local service businesses. Below are real, third-party results from the category: a missed call answered, a lead reached in minutes instead of hours, a no-show that never happened.

In plain terms: these are documented results from the category — peer-reviewed studies and named industry research — not Neuron HQ's own client outcomes. We're a new AI-agent practice and don't yet have client numbers to show. What we can show is that the model works, with a source you can open behind every figure.

Documented result · Speed-to-lead

Why does answering a lead in 5 minutes matter so much?

Because the window closes fast. The MIT / InsideSales.com Lead Response Management study — three years of data across 15,000 leads and 100,000 call attempts — found that contacting a new web lead within 5 minutes instead of 30 makes you 21 times more likely to qualify it. Harvard Business Review's audit of 2,241 U.S. companies reached the same conclusion: firms that responded within an hour were nearly 7 times more likely to qualify a lead than those who waited even one hour longer. An AI agent answers in seconds — every time, day or night.

21×  more likely to qualify (5 min vs 30 min) Source: Oldroyd, McElheran & Elkington, “The Short Life of Online Sales Leads,” Harvard Business Review (2011) · MIT / InsideSales.com Lead Response Management Study (2007)
Documented result · Never miss a call

How many calls is a local business actually missing?

More than owners think. Invoca's platform data shows 27% of calls to home-services businesses go unanswered — roughly one in four new-customer conversations dropped before it starts. And the ones you put on hold don't wait: Invoca's Buyer Experience report found 75% of consumers hang up rather than stay on hold, with only 6% willing to hold for 30 minutes. An AI receptionist picks up on the first ring, books the appointment, and never sends a paying caller to voicemail.

Documented result · No-show reduction

Do automated reminders really cut no-shows?

They do, and the effect is large. In a randomized controlled trial published in the International Journal of Pediatrics, automated text reminders cut the no-show rate from 38.1% to 23.5% — a 14.6-percentage-point drop (p = 0.04). A 2020 systematic review of 20 studies backs it up: patient reminders produced an average 41% reduction in missed appointments, with 95% of studies showing a positive effect. Every recovered slot is revenue that would otherwise have walked out the door.

Documented result · The buyer still wants to call

Is the phone still where high-value bookings happen?

Yes — especially for the bookings worth the most. Invoca's Buyer Experience research found 68% of consumers prefer calling a business over any other channel for the human connection, and 30% say they call specifically because they're most comfortable making a high-stakes purchase by phone. A new patient or homeowner is far more likely to book by voice than fill out a form — which is exactly why a front desk that always answers, in a natural voice, protects your highest-value revenue.

68%  prefer to call a business Source: Invoca Buyer Experience Benchmark Report (500 U.S. consumers, high-stakes purchases)
Documented industry results for AI front-desk, speed-to-lead, and no-show automation
What the system does Documented result Source & type
Instant lead follow-up (speed-to-lead) 21× more likely to qualify a lead (5 min vs 30 min) HBR (2011) · MIT/InsideSales study (15,000 leads)
Answer every call (AI receptionist) 27% of home-services calls otherwise unanswered Invoca platform data
Automatic appointment reminders 38.1% → 23.5% no-show rate (−14.6 pts) Int. Journal of Pediatrics (2016) · RCT
Reminders at scale (across studies) ~41% average reduction in missed appointments PAMJ-One Health (2020) · review of 20 studies
Always-on natural-voice front desk 68% of consumers prefer to call a business Invoca Buyer Experience Report · 500 consumers

The takeaway: across independent studies, the wins come from the same three habits — answer fast, answer every time, and remind every patient. Those are exactly the jobs an AI agent does perfectly, around the clock. These are category results, not Neuron HQ's own client numbers — but they're the proof the model works before we build it for you.

Want this for your front desk?

Tell us where calls, leads, and appointments slip through today. We'll map exactly which AI agents to build first — and what they'd recover — for your business.

The through-line

Different industries. Same way of building.

Learning, spa operations, construction finance, the job hunt — on the surface these have nothing in common. Underneath, they were built the same way: an idea scoped into a real app, the AI work done on our Neuron engine, and every line of code reviewed by a senior engineer before it shipped. That's the method behind Built with Neuron, and it's available for your idea too.

Fast, not rushed
AI speed gets a working first version up in about two weeks — then a human makes sure it's right.
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One engine, every build
Each product reuses proven pieces from the Neuron engine, so new work starts ahead instead of from zero.
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You own the result
Every build ships with the full code and repo in your hands — no lock-in, no black box.
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Your idea, shipped
as real software.

These four started exactly where you are — as a description of something that didn't exist yet. Tell us what to build. Fixed price, every line reviewed by a senior engineer, first version in about two weeks, and you own the code.

Questions first? Read the FAQ or see how we work.