Hey San Diego — I get it, you're probably clicking through a bunch of city-specific pages right now, trying to find someone who actually understands what you need. Most of those pages are just keyword-stuffed, right? Well, I’m A.I. Consulting LLC, and I'm a solo operator based in Florida. I specialize in helping businesses, including those right here in San Diego, California, figure out and implement machine learning and data science solutions that actually make a difference.
I’m not gonna hit you with a bunch of jargon about 'disrupting industries' or 'leveraging synergies.' That’s just not my style. What I do is much simpler: I help small to medium-sized businesses use their data better, build smart systems, and automate the boring stuff. Think of me as your neighborhood shop for AI – someone who's seen a few things, knows what works, and isn't afraid to tell you if something's a bad idea.
## What I actually do for San Diego clients
Okay so, when a San Diego business comes to me, they usually have a problem that feels kinda fuzzy. Maybe they’ve got a mountain of customer support tickets and think 'AI could help here,' but they don't know where to start. Or they're drowning in spreadsheets, and someone mentioned 'predictive analytics.' My job is to translate those vague ideas into concrete projects, then build them.
Typical projects I handle involve things like building a custom machine learning model to predict customer churn, automating data entry or report generation from messy sources, or setting up a small pilot program to see if a particular AI approach is even worth pursuing. I've helped clients in manufacturing identify defects faster, and in e-commerce, I've built recommendation engines. It's all about finding that one specific bottleneck or opportunity where data and a little bit of smart tech can make a tangible difference.
## How a San Diego engagement usually goes
I like to keep things straightforward. Here’s how a typical project unfolds when you work with me:
1. **Initial Chat & Discovery (1-2 weeks):** We start with a 20-minute call, then if it feels like a good fit, I'll do a deeper dive. This involves understanding your business, your data, and what you're trying to achieve. I'll ask a lot of questions. I might even ask to see some anonymized data if it helps me understand the scope. 2. **Project Definition & Proposal (1 week):** After discovery, I'll come back with a clear, fixed-scope proposal. This outlines the problem I'm solving, the specific deliverables (e.g., 'a deployed model,' 'a data pipeline'), the timeline, and the cost. No surprises. This is also where I'll tell you if I don't think I can help, or if your expectations are outta whack. I'm not gonna take your money if I don't think I can deliver value. 3. **Development & Iteration (4-12 weeks, project dependent):** This is where I build the solution. I work iteratively, meaning I'll show you progress often and gather your feedback. For a typical machine learning model, this involves data cleaning, model training, validation, and preparing it for deployment. Communication is key here; I'll be in regular contact. 4. **Deployment & Handover (1-2 weeks):** Once the solution is built and tested, I help you get it into production. This could mean integrating it with your existing systems, providing documentation, and training your team on how to use and maintain it. My goal is for you to be self-sufficient, not reliant on me forever.
## What it costs, roughly
I know budget is always a concern. I don't do hourly billing for projects because I think it rewards inefficiency. Instead, I work on a fixed-fee basis, tied to a clear set of deliverables. For most initial pilot projects or focused data automations, you're usually looking at a few thousand dollars on the low end, up to mid-five figures for more complex model development and deployment. It really depends on the complexity and scope, but I'll always be transparent about the number upfront in my proposal. I'm not the cheapest option, but I aim to be the most straightforward and effective for what I do.
## Who I'm usually NOT a fit for
Look, I'm just one guy, A.I. Consulting LLC, and I can't be everything to everyone. I'm usually not a good fit for:
* **Companies looking for 'AI for AI's sake':** If you just want to say you're 'doing AI' without a clear business problem, I'm probably not your guy. I need a real problem to solve. * **Organizations with no data at all:** Machine learning and data science kinda need data to, you know, _do_ anything. If you're starting from absolute zero, we might need to talk about data collection first. * **Massive enterprise-level projects with a cast of thousands:** I'm built for agility and direct communication. If you need a huge team and a long, drawn-out procurement process, I'm probably too small for what you need. * **Those expecting overnight miracles:** Building effective data solutions takes time and iteration. It's not magic, it's careful engineering.
## Getting in touch
If you're a San Diego business owner or manager, and what I've said here resonates with you, I'd genuinely love to hear about what you're trying to achieve. The best way to start is to book a 20-min call with me. We can chat about your situation, see if there's a potential fit, and if not, maybe I can point you in the right direction. No pressure, just a candid conversation. You can find the link on my website.
FAQs — San Diego
How do I know if Machine Learning or Data Science is worth it for my San Diego business?
The best way to tell is if you have a clear business problem that involves large amounts of data, or repetitive, data-driven tasks. If you're spending a lot of time manually sifting through information or making educated guesses, there's likely an opportunity for automation or intelligent prediction.
Do you work with companies outside San Diego, California?
Yes, I work remotely with clients across the United States. While this page is for San Diego specifically, my operations are set up to handle projects virtually, so location isn't a barrier to working together.
What does the first 2 weeks of a project usually look like?
After an initial call, the first couple of weeks are dedicated to deep discovery. I'll spend time understanding your business processes, existing data, and what success looks like for you. This helps me scope the project accurately and ensure I'm building something truly useful.
I have some data, but it's really messy. Can you still help?
Absolutely. 'Messy data' is the norm, not the exception, in the real world. A significant part of any data science project involves cleaning, organizing, and preparing data. I'm well-versed in handling imperfect datasets.
What kind of commitment is required from my team during a project?
Your team's commitment primarily involves providing access to relevant data and subject matter expertise. I'll need some of their time for initial discovery and regular check-ins to review progress and provide feedback. The more engaged you are, the better the outcome.