Hey Houston – I get it. You've probably clicked on a dozen city pages, all promising the moon with AI. This isn't that. I'm A.I. Consulting LLC, and I help businesses like yours make sense of machine learning and data science, right here in Houston. I'm a solo operator, not some faceless corporation. My goal is simple: help you figure out if these tools can actually make a difference for your business, and then help you build it. I'm not gonna sell you on 'bleeding-edge neural networks' if what you really need is a smarter spreadsheet. I focus on practical applications and clear, measurable outcomes. If you're tired of hearing buzzwords and want to talk about how a machine learning model could actually help your business operate smoother, or make a better decision, then you're in the right place.
## What I actually do for Houston clients Okay so, when a Houston business comes to me, they usually have a problem that feels like it *could* be solved by some smarter data. Maybe they're drowning in customer feedback and can't see the patterns, or they're trying to predict demand for a product and their current methods are just not cutting it. I step in to design and build custom machine learning models or data science workflows to tackle those specific problems.
Think of it as building a really smart tool for a very specific job. I've helped clients analyze historical sales data to forecast future trends, or categorize inbound customer service requests to route them more efficiently. It's about taking your existing data and making it work harder for you, identifying insights or automating decisions that would be impossible or too slow for a human to do consistently. I won't just hand you a report; I aim to get a working model into your hands that makes a tangible impact.
## How a Houston engagement usually goes 1. **The Initial Chat (Week 1):** We'll hop on a quick call, maybe 20 minutes. You tell me what's on your mind, what problem you're wrestling with. I'll ask some questions about your data, your current process, and what success would look like. No sales pitch, just a real conversation to see if there's even a potential fit. If it sounds promising, I'll send over a simple proposal outlining the scope and what I think I can deliver. 2. **Deep Dive & Data Prep (Weeks 2-4):** If you decide to move forward, I'll spend some time really getting to know your business and your data. This often involves securely accessing your data, cleaning it up (this is almost always a bigger job than anyone thinks!), and exploring it to understand its quirks and potential. I'll keep you updated frequently, usually with a quick check-in call once or twice a week to show progress and get your feedback. 3. **Model Building & Testing (Weeks 5-8):** This is where the machine learning magic happens, or data science modeling. I'll design, build, and train the model or system, testing it rigorously to make sure it's accurate and reliable for your specific needs. We'll iterate on this together; your feedback is crucial here to make sure it's solving *your* problem effectively. This stage kinda depends on the complexity. 4. **Deployment & Hand-off (Weeks 9-10+):** Once the model is performing well, I'll help you integrate it into your existing systems. This could be as simple as an automated daily report or as involved as an API endpoint your software can call. I'll make sure you understand how it works and what to expect. My goal is for you to be able to use and maintain it, with me available for any ongoing support if needed.
## What it costs, roughly Look, I'm not gonna pretend this stuff is cheap. Building custom machine learning solutions takes time and expertise. Most projects usually fall into a range, not a fixed price, because every business's needs are different. For a pilot project or a well-defined problem, you're usually looking at something in the **mid-five figures**. Larger, more complex engagements can certainly go higher. I prefer fixed-fee arrangements so there are no surprises, but sometimes an hourly rate makes more sense for exploratory work. We'll discuss all this upfront, transparently, before any work begins. I want you to feel good about the investment.
## Who I'm usually NOT a fit for I'm pretty upfront about this. If you're a huge corporation with a massive in-house data science team, I'm probably not the right fit. You likely need a different kind of partner with a different kind of overhead. Also, if you're looking for 'AI' just for the sake of it, without a clear business problem you're trying to solve, I'll probably tell you to save your money. I also don't do 'black box' solutions where you don't understand how it works. My clients in Houston value transparency and a hands-on approach.
## Getting in touch Ready to talk about what machine learning or data science could actually do for your Houston business, without all the fluff? The easiest way to get started is to book a 20-min call. No pressure, just a chance to see if I can help you out.
FAQs — Houston
How do I know if machine learning is worth it for my Houston business?
The best way to know is if you have a recurring business problem that involves a lot of data, and you suspect there are patterns or decisions that could be automated or improved. If you're spending a lot of manual effort on tasks like forecasting, categorizing, or predicting, then it's worth a conversation.
Do you only work with companies physically located in Houston, Texas?
While I love working with local Houston businesses, I can certainly work with companies outside of Houston too. Most of my work is done remotely, so geographical location isn't a barrier. However, I do enjoy the occasional in-person meeting if you're in town.
What does the first 2 weeks of an engagement typically look like?
The first two weeks are usually focused on discovery and data preparation. After our initial chat, if we decide to work together, I'll spend that time diving deep into your business processes and, crucially, getting your data ready for analysis. This often involves data cleaning and initial exploration to understand its structure and quality.
What kind of data do I need to have for machine learning to be useful?
You typically need historical data related to the problem you're trying to solve. For example, if you want to predict sales, you'd need past sales data. The more data you have, and the better quality it is, the more accurate and useful the machine learning model can be. Don't worry if it's not perfect; part of my job is to help you with that.
Will I own the machine learning models and code you develop for my Houston business?
Absolutely. Once the project is complete and paid for, you will own all the intellectual property, including the models and code developed specifically for your business. My goal is to deliver a solution that you can integrate and benefit from long-term, without any ongoing licensing fees from my end.