Hey Irving — I know you're probably looking at a bunch of city pages right now, trying to figure out if some AI consultant out there can actually help your business. It's a bit of a wild west, I get it. I'm not gonna lie to you and say I'm some huge firm with a massive team. It's just me, A.I. Consulting LLC, based out of Florida, but working with folks just like you in Irving, Texas, to make sense of all this 'data science' and 'machine learning' stuff. My goal here isn't to dazzle you with buzzwords, but to give you a straightforward idea of what I do, how I do it, and if it might be a good fit for your company right here in Irving.
Okay so, you’re probably thinking, “What’s different here?” Well, for starters, it’s just me. That means when you talk to me, you're talking to the person who will actually do the work. No sales team, no handoffs, no 'account managers' who don't know a neural network from a fishing net. I'm kinda like that neighborhood shop owner who knows his stuff, doesn't upsell you on things you don't need, and is around for the long haul. I've been doing this for a while, and I've seen enough to know what usually works and what's probably just a waste of your time and money.
## What I actually do for Irving clients
Mostly, I help businesses in Irving take their messy data and turn it into something useful. This could mean predicting when a piece of equipment is gonna fail, or figuring out which customers are most likely to buy your new product. It's about finding patterns and making educated guesses, automatically. Think of it as giving your data a brain, so it can start working for you instead of just sitting there in a spreadsheet.
Typical projects often start small: maybe a proof-of-concept pilot to see if a machine learning model can actually improve your sales forecast by, say, 15%. Or I might help automate a repetitive data analysis task that eats up hours of your team’s time every week. The aim is always to deliver something tangible that moves the needle for your Irving business, not just a fancy report no one understands.
## How a Irving engagement usually goes
1. **Discovery (1-2 weeks):** This is where I listen. We'll talk about your business, your data, and what problems keep you up at night. I'll ask a lot of questions, look at your existing processes, and try to get a clear picture of what's possible. No big commitment, just understanding. 2. **Feasibility & Proposal (1 week):** After our initial chats, I'll tell you honestly if I think machine learning can help. If it can, I'll put together a clear, fixed-price proposal for a specific pilot project. This proposal will outline what I'll build, what success looks like, and exactly what it'll cost. If it can't, I'll tell you that too. 3. **Pilot Project (4-8 weeks):** This is the doing part. I’ll build out the agreed-upon machine learning model or data science solution. We'll have regular check-ins to make sure we're on track, and you'll see the progress firsthand. The goal is to deliver a working system that solves a defined problem. 4. **Handoff & Support (Ongoing):** Once the pilot is complete and you're happy, I'll make sure you understand how to use and maintain the solution. I can also provide ongoing support or help transition it to your internal team, if you have one. It’s all about making sure what I build actually sticks and provides value.
## What it costs, roughly
I prefer fixed-fee pricing for projects. That way, you know exactly what you’re paying upfront, and there are no surprises. For a typical pilot project, you're generally looking at costs in the low-to-mid five figures. If we're talking about something more involved, like building a complex predictive model from scratch and integrating it into your systems, it could go higher. But we'll always agree on the price before any major work starts.
## Who I'm usually NOT a fit for
I'm not usually a good fit for huge corporations with layers of bureaucracy and a dozen stakeholders who all need to sign off on every tiny decision. My sweet spot is working with small to medium-sized businesses in Irving who are nimble, have fairly accessible data, and are ready to actually implement solutions. If you're just looking for someone to write a 100-page 'strategy document' that sits on a shelf, I'm probably not your guy. I'm here to build things that work.
## Getting in touch
Anyways, if this sounds like what you're looking for, and you're curious about how machine learning or data science could help your Irving business, I'd love to chat. It's a no-pressure conversation, just a chance for us to figure out if there's a good fit. Go ahead and book a 20-min call.
FAQs — Irving
How do I know if Machine Learning is worth it for my Irving business?
The best way to know is to start with a specific problem you're trying to solve, like reducing customer churn or optimizing inventory. If you have data related to that problem, there's a good chance machine learning could provide some valuable insights.
Do you only work with businesses directly in Irving, Texas?
While I enjoy working with businesses in Irving and the DFW area, I'm set up to work remotely with clients across the United States. Location isn't a barrier to getting good work done.
What kind of data do I need to have for a Machine Learning project?
You'll ideally need structured historical data that's relevant to the problem you want to solve. This could be sales records, customer demographics, operational logs, or sensor data. Don't worry if it's not perfectly clean, that's part of what I help with.
What does the first 2 weeks of an engagement look like?
The first couple of weeks are all about discovery. We'll have several conversations to understand your business goals, current processes, and available data. I'll be asking a lot of questions to get a clear picture before any solution design begins.
Can I start with a small pilot project to test the waters?
Absolutely. I almost always recommend starting with a small, focused pilot project. This allows us to prove the value and viability of a machine learning solution with minimal risk before committing to a larger initiative.