Hey Richmond — I know you've probably clicked through a bunch of 'AI consulting' pages already, and yeah, they all kinda start to sound the same, don't they? 'Revolutionary solutions,' 'paradigm shifts,' all that jazz. If you're looking for someone to just tell you what you wanna hear or pitch you a giant, abstract project, I'm probably not your guy. But if you're a business owner in Richmond, Virginia, and you're curious about how machine learning or data science could actually help you make more money or save some time, then you're in the right place. I’m a solo operator, A.I. Consulting LLC, and I work directly with businesses like yours to figure out what’s real and what’s just hype. I focus on practical applications, not just theory, so you get something that actually works. Most of my clients are looking for a clear path forward, not a year-long engagement. I don't have a huge team, so you're always working with me directly. This means you get straight answers and real talk about what's possible, and what's probably not, for your Richmond business.
## What I actually do for Richmond clients
Okay so, when a Richmond business comes to me asking about machine learning or data science, it's usually because they have a specific problem. Maybe they're drowning in data and can't make sense of it, or they're repeating a task manually that feels like it could be automated. I help them scope out a small, manageable pilot project. Think things like building a predictive model to forecast sales more accurately based on historical data, or setting up a system to automatically categorize customer feedback, saving someone hours of reading every week. It's about finding that one high-impact thing that moves the needle.
I also do a lot of data cleanup and analysis. Sometimes, before you can even think about machine learning, you just need to get your data in order. I can help with that, turning messy spreadsheets or databases into something usable, then showing you how to extract actual insights. It's not always glamorous, but it’s often the most important first step, and it sets the stage for any future AI work. My goal is to get you a working solution that you can understand and maintain, whether it’s a simple script or a more complex model, all tailored to your specific needs in Richmond.
## How a Richmond engagement usually goes
1. **Initial Chat (1-2 days):** You book a quick 20-min call. We talk about what you're trying to do, what your business looks like, and if I think I can genuinely help. If it seems like a good fit, I'll ask for some more info and maybe schedule a deeper dive.
2. **Discovery & Proposal (1-2 weeks):** We'll have a more detailed call or two, where I dig into your current processes and data. I'll ask a lot of questions. Then, I'll put together a fixed-fee proposal for a specific project, outlining exactly what I'll deliver, the timeline, and the cost. No hourly billing surprises here.
3. **Project Work (3-8 weeks, typically):** Once we agree, I get to work. This involves data collection (if needed), cleaning, model building, testing, and then integrating the solution. I'll check in with you regularly, usually weekly, to show progress and get your feedback. My aim is to be transparent throughout the whole process.
4. **Delivery & Handoff (1 week):** I deliver the working solution, whether it's a report, a data pipeline, or a deployed model. I'll walk you through how it works, provide documentation, and make sure you or your team can use it effectively. I'm available for a little bit of post-delivery support, too, just to make sure everything settles in okay.
## What it costs, roughly
Look, I don't give hourly rates because I hate watching the clock and I bet you do too. I work on a fixed-fee basis for defined projects. This means you know the exact cost upfront. For typical small to medium-sized projects – things like a focused data analysis, a specific predictive model pilot, or an automation script – you're usually looking at a range somewhere from a few thousand dollars up to mid-five figures. It really depends on the complexity and scope. Bigger, more involved projects would obviously be more. I'm always transparent about the cost in my proposal, and I won't start work until you're clear on it.
## Who I'm usually NOT a fit for
I'm pretty upfront about who I can help and who I can't. If you're a huge corporation looking for a large team of consultants to conduct a year-long 'AI strategy' engagement with dozens of stakeholders, I'm definitely not the right choice. I also don't do 'magic bullet' solutions – if you expect me to wave a wand and solve all your business problems without any data or effort on your end, we won't get along. And if your data is totally non-existent or completely inaccessible, it's gonna be tough for me to do much with machine learning. My sweet spot is working with Richmond businesses that have some data, a clear problem, and a willingness to engage in the process.
## Getting in touch
If any of this sounds like what you've been looking for, and you're ready to explore how machine learning or data science could practically benefit your business here in Richmond, I'd love to chat. It costs nothing to find out if there's a good fit. Just head over to my contact page and book a 20-min call.
FAQs — Richmond
How do I know if AI is worth it for my Richmond business?
The best way is to identify a specific, repeatable task that takes a lot of time, or an area where better predictions could lead to clear financial gains. If you have data related to that, then it's often worth exploring. I can help you figure this out in our first chat.
Do you work with companies outside Richmond, Virginia?
While I focus on serving local businesses, I do work with clients remotely across the US. However, I prioritize understanding the unique needs of the Richmond business community.
What does the first 2 weeks of an engagement look like?
The first 2 weeks are mostly about discovery. We'd have detailed conversations about your data and processes, and I'd be working on a clear, fixed-fee proposal outlining the project scope, deliverables, and timeline for your review.
What kind of data do I need to have for machine learning?
You'll generally need historical data that's relevant to the problem you're trying to solve. For example, if you want to predict sales, you'd need past sales figures. The cleaner and more organized your data is, the faster we can get to work, but I can help with messy data too.
Do I need to hire a full-time data scientist after working with you?
Not necessarily. My goal is often to deliver a working solution that can be integrated into your existing operations or used by your current staff. For ongoing maintenance or new projects, you might consider it, but I aim for self-sufficiency where possible.