I build custom AI tools
for SMB sales, marketing,
and ops teams.
Off-the-shelf AI is built for everyone, which usually means it doesn’t quite fit anyone. I sit with your team, scope the build, and ship working software in 2–4 weeks. You own the code and can edit it yourself.
6
AI tools built across sales, marketing, ops, and data
2-4 wks
typical kickoff-to-shipped window
1:1
I build it personally, not a junior
build + run
fixed-price build, plus an optional $4-5k/mo managed tier
You get me on the call, in the build,
and on the other side of it.
ron · builder
I’m Ron. I didn’t set out to be an AI consultant. I started building AI tools for my own companies because I had work I didn’t want to do anymore. The slow, repetitive stuff that eats half a week and never feels finished.
The first few builds were just for me. Then a teammate started using one. Then another team asked if I could do something similar for their workflow. The tools were saving hours every week and making annoying processes feel almost fun, and that’s the part I got hooked on. Watching something I built move the day.
That’s the work I want to do for other teams now. If your reps, marketers, or ops folks are stuck doing things AI should be handling, that’s exactly the kind of problem I like getting on a call about.
The person you talk to is the person who builds it. Discovery, prompts, configuration, code. Same head the whole way through.
Don’t trust me.
Look at what I’ve shipped.
Six production AI tools across sales, fintech ops, e-commerce, healthcare, and events. Click any card to see the full interactive demo.
Each of these went from idea to deployed in 2-4 weeks.
book a discovery call →Most AI builds break
for the same five reasons.
None of them are about the model. They’re about the work that should happen before and around the model. Here’s what to watch for, and how a build avoids each one.
01 · business
Pick the right problem.
Most AI builds solve the loudest problem, not the most expensive one. Some of the busywork on your team is costing you real revenue or hours. Some of it just feels urgent in standup. Those are not the same thing.
We start by sizing the pain in dollars or hours before scoping anything.
02 · marketing & ops
Match how the team works.
A tool that ignores the actual workflow gets abandoned in week two. Reps already have a way they sell. Marketers already have a stack. Ops already has a system of record. The build has to live inside that, not next to it.
I sit with your team first so the tool fits the muscle memory they already have.
03 · product
Cut the right things.
The biggest reason builds drag on is scope. Every ‘wouldn’t it be cool if’ adds a week and dilutes the thing that mattered in the first place. The hard part of building isn’t adding features. It’s knowing what to leave out.
You get a one-page scope so you can see exactly what’s in, what’s out, and why.
04 · ai
Avoid the AI failure modes.
AI tools tend to fail in predictable ways: bad context, wrong model for the job, no evals, no fallback when the model whiffs. They look great in a demo and fall over the first week your team uses them on live data.
I pick the model, write the prompts, and build the eval loop so it holds up once your team is on it daily.
05 · build
Ship it without handoffs.
When strategy, design, and engineering live in different rooms, things get lost in translation. The spec a strategist writes is rarely the spec a dev would have written, and the gap is where builds die.
Same person scopes it and writes the code, so nothing gets lost between the call and the commit.
If your last AI rollout stalled, it almost certainly tripped on one of these five. The discovery call is mostly about figuring out which one is in your way right now.
02 — discovery before code
I learn how you work. Then I build.
Most AI tools ship before they meet you. I sit in on your meetings, read your playbook, talk to two or three of your people, and map the busywork eating their day. Only then do I touch a line of code.
// discovery.week_one
One-page scope
what · cost · timeline · sent in 48h
03 — wired into your stack
Built around the stack you already use.
Whatever I build plugs into how your team already works. Your CRM, your analytics, your marketing stack, your docs. The AI runs on your data, not someone else's templates.
// your.stack
Your custom build
6
tools wired
0
data leaves
100%
yours
04 — fast and visible
Daily progress. Working software.
Most builds ship in a few weeks. You get a Loom or a Slack message every day showing what changed and what's next. Your team pokes at it as it grows, so by the time it's live, they already know how to use it.
// build.timeline
a few weeks from idea to shipped
How the work
actually gets done.
From a first call to software your team is using day to day. The same shape every time, so you know what you’re signing up for before you sign up.
Discovery call
free · 30 min
We get on a call.
Tell me what your team is dealing with. What's slow, what's broken, what you've already tried. I ask the questions a builder would ask instead of running a sales script.
Understand your needs
the first few days
I sit with your team.
I ride along on meetings, read whatever docs you have, look at your tools, and talk to two or three of the people who'll be using the build day to day. The goal is to see how the work gets done before I write a line of code.
Scope the build
before any code
Written proposal. Fixed price.
You get a one-page scope covering what I'm building, what it'll do, what it costs, and roughly when it ships. Everything you'll need to say yes or push back is on a single page.
Implement + test
a few weeks
I build. You watch.
I send updates in Slack or Loom as I go. Working software lives somewhere you can click around in every day. Your team gets eyes on it as it grows, so by launch they already know how to use it.
Track results
after launch
We measure what changed.
Pipeline created, hours saved, response rate, whatever metric matters to you. We agree on it before I start so when it works there's nothing to argue about.
Stay available
ongoing
I'm a text message away.
Most clients keep me around for tweaks, new builds, or to bounce ideas off someone who ships software for a living. No retainer. You only pay when there's something to do.
Step one is always a real conversation. Everything else flows from there.
book a discovery call →Buying off-the-shelf AI
vs. building your own.
Off-the-shelf AI products are built for everyone, which means they’re built for nobody in particular. Sometimes that’s fine. When the work is specific to how your team runs, a build that fits your workflow tends to hold up better than a tool you have to bend your team around.
what you get
Scoped to your team's workflow
Wired into your existing stack
Runs on your data, not someone else's templates
You own the code and can edit it
Built and shipped in a few weeks
Same product shipped to every customer
Seat-based pricing forever
Roadmap controlled by someone else
One build.
Two ways to run it.
Pay once and run it yourself, or pay monthly and I handle the whole thing. Same build either way.
Build only
I build it. You run it.
Mid 4 to low 5 figures
one-time, fixed in writing before any code
best for
Teams with a developer who can own the tool day to day.
what’s included
- Discovery week with your team
- One-page scope, fixed price
- Full build in 2 to 4 weeks
- Code transferred to your GitHub
- Prompts and evals documented
- Two weeks of post-launch tweaks
you handle
- Your own API keys (OpenAI, Anthropic, etc)
- Hosting on Vercel, Supabase, or your stack
- Day-to-day monitoring and edits
Build + Managed
I build it. I run it.
Build cost + $4–5k / month
managed fee starts at launch, cancel anytime
best for
Teams that want a working tool without owning the infrastructure.
what’s included
- Everything in Build only
- Hosting, database, API keys on me
- Model selection and evals tuned monthly
- Prompt updates and small tweaks included
- Monitoring, alerts, uptime
- Direct Slack channel with me
- New small builds bundled in
you handle
- Telling me what you want changed
- That’s it
Not sure which tier fits? We figure it out on the discovery call. The right answer depends on your team, your stack, and how much of this you want to think about after launch.
Things you’re probably
wondering about.
Two options. Default is you bring your own keys: the build sits on your OpenAI, Anthropic, or other API accounts and the bill goes to you. No markup, no middle layer. Most builds run somewhere between $50 and $500 a month in API costs depending on volume, and I pick the cheapest model that holds quality so the bill stays sane. The other option is the managed tier (see below) where I handle all of it.
Got a question that’s not here? Ask it on the discovery call. I’d rather answer it once for you than guess at it on a marketing site.
08 — let’s talk
Want something built
for your team?
Book a 30-min discovery call. Tell me what’s slow,
and I’ll tell you if I can fix it.