I specialize in AI cloud consulting for compliance-regulated industries, helping businesses integrate advanced automation, voice AI, and data-driven solutions with a strong focus on privacy and operational efficiency. My work spans several sectors, including finance, physical therapy, dentistry, and e-commerce, where I deliver systems that not only meet technical standards but also align with client workflows and industry regulations.

I value long-term relationships and have ongoing consulting arrangements with several clients and their dev teams. A rockstar client, to me, is one who’s collaborative, values the work, and sees the bigger picture. I’m not afraid to walk away from projects that undervalue the effort or come with unrealistic expectations, and I’ve done so when necessary.

Currently, I’m consulting for a finance company, meeting biweekly with their development team to guide strategy and implementation. In healthcare, I’ve designed a voice AI appointment setter and outbound reminder system for a physical therapy network with over 20 locations. Each solution is tailored, often priced according to the real-world workload it replaces, such as calculating savings based on the number of employees currently performing those tasks.

I lean heavily on n8n for automation, leveraging its flexibility to create streamlined workflows like an AI image scanning pipeline I built for a dental office. For data and storage, I prefer Airtable or AWS-based services, depending on the scope and scalability needs. On the AI model side, I work with Claude, Gemini, OpenGPT, Grok, and local deployments of Ollama. Interfaces vary by project; I use chatbots, Streamlit, or Laravel depending on whether I’m building the front end or collaborating with developers. For audio and visual generation, I utilize tools like Leonardo.ai, Heygen, ElevenLabs, and ChatGPT.

One key lesson I emphasize in my consulting practice is that AI needs direction. Without the right fine-tuning and knowledge base, even powerful models can produce misleading or irrelevant results. That’s why I always insist on training models using client-specific data, ensuring output is aligned with business goals and facts.