Built and delivered by the founder
I’m Kelvan Ince, a software engineer with over a decade of experience building production systems, including platforms used by the New York Stock Exchange. I now work directly with local San Diego businesses to apply AI in practical ways: reducing admin, improving operations, and supporting day-to-day decision-making. This work is founder led, hands on, and intentionally small scale, so projects move quickly and stay grounded in real business needs.
- - 10+ years building production software
- - Experience across finance, retail, healthcare, and services
- - San Diego based, founder led delivery
Helping San Diego businesses operate with less friction
We work directly with local teams to introduce practical AI that reduces admin load, speeds up responses, and improves day-to-day decision making without changing how you already run your business.
Small pilots first, clear outcomes, and a focus on what saves time and increases revenue.
User stories
Slide through a few grounded examples. One shows at a time.
Hairdresser
The problem: The hairdresser relied on phone calls and text messages to manage appointments. Last-minute cancellations were common. Sometimes several at once, leading to lost time, lost income, and constant schedule juggling.
What we did: Implemented an AI scheduling agent to handle appointment changes automatically. When a client couldn’t make their slot, they could notify the agent, which reviewed availability, suggested alternatives, and notified other clients when an earlier opening became available.
The outcome: Cancellations were handled in the background without interrupting the workday. Fewer empty slots went unused, clients were better accommodated, and the hairdresser spent less time on admin and more time with clients.
Types of inputs used: Booking history · Cancellations · Availability
Restaurant
The problem: A local restaurant struggled to order the right amount of fresh ingredients. Demand fluctuated with weather, tourism, and seasonal menu items. San Diego has a particular problem here with avocados, seafood, and cocktail ingredients. To avoid running out, the owner over-ordered, leading to spoilage and inconsistent margins.
What we did: We ran a trial using historical sales and ordering data plus seasonal and local demand signals. Provided simple ingredient level demand forecasts ahead of each ordering cycle so the owner could order confidently without changing suppliers or kitchen workflows.
The outcome: Reduced food waste, improved ordering confidence, and stabilized margins during busy periods. The owner had clearer guidance on when demand was likely to spike and when it wasn’t.
Types of inputs used: Sales history · Ordering cycles · Seasonal patterns
Plumbing company
The problem: A local plumbing company spent too much time on non-billable admin. Missed calls, voicemails, texts, photos, and follow-up questions piled up while technicians were on jobs leading to delayed responses, lost opportunities, and evenings lost to paperwork.
What we did: Implemented an AI intake and admin agent to handle customer inquiries asynchronously. It collected job details, photos, and availability, categorized requests by urgency, and prepared clear summaries for the owner and technicians without interrupting active jobs.
The outcome: The company responded to more inquiries without adding headcount. Urgent issues were identified faster, follow-ups were handled automatically, and the owner spent less time on admin and more time on jobs and customers.
Types of inputs used: Calls · Texts · Photos · Job details
What we typically build for local businesses
AI intake & scheduling assistants
Handle inquiries, rescheduling, and follow ups automatically without changing your existing tools.
Operational forecasting
Improve ordering, staffing, and day-to-day decisions using your existing sales, demand, or workflow data.
Admin & workflow automation
Reduce manual admin with automated summaries, reports, and follow-ups.
Built as small pilots first. No lock-in. No unnecessary tooling.
A simple, low-commitment process
Most local pilots run 1–2 weeks, require minimal setup, and don’t lock you into anything.
Short conversation
A 20–30 minute call to closely understand your workflow, current tools, and what success looks like for you.
Small pilot or analysis
A focused test using data and/or processes. Lightweight, contained, and designed to answer a specific question.
Clear recommendation
A straightforward call on whether this is worth building. If yes, you’ll get a clear scope, risks, and timeline. If not, you still get the findings.
Optional expansion
If the pilot works, we can continue into a tailored solution and its support. If it doesn’t, there’s no obligation to continue.
Book a 20-minute conversation
No demos. No sales funnel. We’ll tell you honestly if this makes sense.
We typically respond within 1 business day.