Okay so, you're on a city page, and you're probably wondering what's different here. Most of these pages are just, well, pages. Filled with fluff. I'm not gonna do that to you. I'm just a guy who’s been doing this a long time, and I've seen what works and what doesn't. My goal is simple: help you cut through the noise and get to what matters. If you're running a business in Indianapolis and you think there might be a better way to do something with your data, or if you're curious about what machine learning could actually *do* for you, you're in the right place.
I don't have a huge team, no fancy offices, just me and my brain. That means you get direct access to someone who actually does the work, not a project manager who just passes messages around. I'm pretty good at explaining complex stuff without making you feel dumb, which I think is kinda important when we're talking about machine learning and data science.
## What I actually do for Indianapolis clients When an Indianapolis company comes to me, it's usually because they've got a specific problem, or maybe they just have a lot of data and don't know what to do with it. Typical projects involve things like building a predictive model to forecast sales more accurately, or maybe automating a tedious data analysis task that’s eating up too much time. I've helped businesses here in Indianapolis identify patterns in customer behavior they never saw before, leading to smarter marketing spend.
Sometimes, it's just a pilot project, a proof-of-concept to see if a machine learning approach even makes sense before you invest a ton of resources. I’ll help you define what success looks like, gather the right data, build out a prototype model, and then actually measure if it delivered on the promise. I focus on practical applications that actually move the needle for your business, not just cool tech demos.
## How a Indianapolis engagement usually goes
1. **Initial Chat (1-2 days):** We hop on a quick 20-minute call. You tell me what's on your mind, what problem you're trying to solve. I ask some clarifying questions. No pressure, just a chat to see if there's even a potential fit. If it seems like I can genuinely help, we move to step two.
2. **Deep Dive & Proposal (1-2 weeks):** This is where I really dig in. I might ask for access to some of your anonymized data, or just more detailed discussions with your team. I’ll put together a clear, fixed-price proposal outlining the project scope, deliverables, timeline, and what you can expect in terms of results. This isn't a vague 'time and materials' estimate; it's a solid plan.
3. **Project Execution (4-12 weeks):** Once the proposal is approved, I get to work. This typically involves data cleaning and preparation (which is often 80% of the battle, let's be honest), model development, testing, and then getting it ready for deployment. I keep you updated regularly, explaining progress in plain English, not technical jargon. My goal is to deliver a usable solution that fits into your existing operations.
4. **Handover & Support (Ongoing):** When the project is complete, I don't just disappear. I'll provide documentation, training for your team if needed, and make sure you're comfortable with how to use and maintain the solution. I'm always available for follow-up questions or adjustments, because let's face it, business needs evolve.
## What it costs, roughly Look, I'm not gonna give you some vague 'it depends' answer. For most practical machine learning or data science projects – things like a specific prediction model, an automation script, or a focused data analysis project – you're typically looking at a fixed-fee engagement somewhere in the low to mid-five figures. Smaller, proof-of-concept engagements can sometimes start a bit lower. The exact price depends entirely on the complexity and scope, but I'm upfront about it. I don't do hourly billing for projects; I quote a fixed price so you know exactly what you're paying for the outcome.
## Who I'm usually NOT a fit for I'm not a good fit if you're looking for a giant consulting firm with a huge bench of engineers. I can't build you a custom AI platform from scratch or manage a team of 50 data scientists. If you need someone to just 'do AI' without a clear problem or goal in mind, I'm probably not your guy either. And if you're expecting something for free, or a 'percentage of savings' deal, that's not how I operate. I work with businesses in Indianapolis that have a specific, measurable problem they believe data or machine learning can help with, and who are ready to invest in a clear, defined solution.
## Getting in touch Ready to skip the buzzwords and just talk about what's possible for your business in Indianapolis? The easiest way to get started is to book a 20-min call directly on my calendar. We can chat about your challenges and see if I can help you out. No sales pitch, just a conversation.
FAQs — Indianapolis
How do I know if AI is worth it for my Indianapolis business?
It's worth exploring if you have repetitive tasks, large datasets, or areas where you're making decisions based on intuition rather than hard data. If a specific business problem keeps you up at night, AI or machine learning might offer a solution.
Do you work with companies outside Indianapolis?
Yes, absolutely. While I focus on helping local businesses in Indianapolis, I also work remotely with clients across the United States. Location isn't a barrier to getting good data science help.
What does the first 2 weeks look like?
The first 2 weeks typically involve an initial discovery call, followed by a deeper dive into your specific problem and data. I'll then prepare a tailored, fixed-price proposal outlining the project scope and expected outcomes for your review.
What kind of data do you usually work with?
I work with all sorts of structured and unstructured data, from sales figures and customer demographics to operational logs and text data. The key is having enough relevant data to train a useful model or extract meaningful insights.
What if I don't have a data science team?
That's perfectly fine! Many of my Indianapolis clients don't have an internal data science team. I can act as your outsourced data expert, handling everything from data preparation to model deployment and explanation.