Services

Services

I do four things. I do them well.

Every project I take on falls into one of these areas. Each one is backed by production experience, not just theoretical knowledge. Here’s what I build, how I build it, and what you can expect.

Service 01

AI & Automation

I build tools that eliminate the repetitive work your team does every day. LLM-powered assistants that answer questions from your data. Workflow automations that move information between systems without human intervention. Chatbots that actually understand your business context.

This isn’t “AI strategy.” It’s working software that does a specific job.

Tech Stack
OpenAI API LangChain RAG pgvector n8n Twilio MCP Protocol Webhooks
Who it’s for

Businesses drowning in manual data entry, copy-paste workflows, or answering the same questions over and over. If your team spends hours doing something a script could do in minutes, we should talk.

What a typical project looks like

2–6 weeks. You get a deployed, working system with documentation. Examples: a RAG chatbot querying your internal docs, an n8n workflow automating lead nurturing across Mailchimp and HubSpot, or an AI assistant that processes incoming forms and routes them automatically.

Real example

Built a semantic knowledge infrastructure with 9,890 indexed records using PostgreSQL + pgvector and a custom MCP server with 4 tools, enabling natural language search across multiple data sources.

Service 02

Data Pipelines & Analytics

Your data is scattered across spreadsheets, databases, and SaaS tools. I build the plumbing that connects it all, transforms it, and surfaces it in dashboards your team can actually use to make decisions.

No more exporting CSVs and pasting into Excel. No more waiting a week for a report.

Tech Stack
Python PostgreSQL BigQuery Power BI Tableau Prefect pandas Streamlit
Who it’s for

Businesses making decisions on gut feel because their data is locked in silos. Teams spending hours on manual reporting. Companies that have data but can’t see the patterns.

What a typical project looks like

2–8 weeks depending on complexity. Deliverables include automated pipelines, database schemas, and interactive dashboards. I use Prefect for orchestration, Python for transformation, and Power BI or Tableau for visualization.

Real example

Engineered automated ETL processes that eliminated manual data entry across agricultural operations. Built data pipelines with Prefect orchestration and fuzzy-logic matching systems that replaced hours of daily manual work.

Service 03

Custom Software

Sometimes you need an application that doesn’t exist yet. An internal tool, a customer-facing portal, an API that connects two systems, or a CI/CD pipeline that makes deployment reliable instead of terrifying.

I build it, deploy it, and set up the infrastructure so it keeps running.

Tech Stack
Flask Django FastAPI Node.js Docker GitHub Actions Azure DigitalOcean REST APIs
Who it’s for

Businesses that have outgrown their spreadsheets and off-the-shelf tools. Teams that need a custom internal application but don’t have a developer on staff. Companies that need two systems to talk to each other.

What a typical project looks like

4–8 weeks for a full application. 1–2 weeks for an API integration or CI/CD pipeline. You get source code, deployment infrastructure, and documentation for your team.

Real example

Built a custom ERP system from scratch for a coworking space: financial management, member lifecycle tracking, access control, room reservations, and real-time analytics. Integrated with Square, Calendly, Nexudus, and HubSpot via REST APIs.

Service 04

ML & Data Science

When you need to go beyond dashboards and actually predict what’s going to happen, I build machine learning models that answer real business questions. Not academic exercises. Models that run in production and inform real decisions.

I handle the full pipeline: data preparation, model selection, training, evaluation, and deployment.

Tech Stack
scikit-learn pandas Streamlit Azure ML MLOps NLP matplotlib Statistical Analysis
Who it’s for

Businesses sitting on data that could predict churn, forecast demand, classify documents, or optimize operations. Teams that want to move from reactive reporting to proactive decision-making.

What a typical project looks like

3–8 weeks. Starts with data exploration, moves through model development and validation, ends with a deployed model and monitoring setup. I document everything so your team understands what the model does and when to retrain it.

Real example

Built a production-ready RAG chatbot for operational analytics with hyperparameter-tuned ML models (SVC achieving 94.8% accuracy) enabling natural language querying across 5 business domains.

Not sure which service you need?

That’s fine. Most projects cross boundaries. Tell me what problem you’re trying to solve, and I’ll tell you what it would take to fix it.