I enjoy turning curious ideas into things that actually work.
I'm a developer and Artificial Intelligence student who likes building the whole thing — the logic, the data, the interface, and all the details in between. At tezway, I build its AI features and backend integrations using .NET 10 — from lead scoring to the Zayro assistant.
BS Artificial Intelligence, Superior University · tezway since June 2026
DRAG TO EXPLORE ↔Conversational CRM insights, grounded in real operational questions.
AI features I've built for tezway using .NET 10, alongside model experiments and API integrations. Select a project to explore the interface and the thinking behind it.
Building .NET 10-powered lead scoring workflows across different CRM formats, including realtime evaluation and controlled batch rescoring. The aim is to make AI scores consistent, explainable, and meaningful for sales decisions.
Adapted from an actual product screenshot; helper copy has been removed for clarity.
01 / 03A learning path rooted in computer science, with practical product work now shaping how I approach problems.
Developing tezway's AI features and backend APIs using .NET 10, including lead scoring, Zayro's CRM analytics and conversational reporting, AI service integrations, and Ollama-based local LLM experiments. My focus is connecting AI capabilities to working business software, not just demos.
Developing foundations in machine learning, NLP, software development, data structures, databases and system design, with hands-on academic projects that move ideas into working applications.
A selection from my CV, spanning more than AI: databases, data visualisation, software engineering and network design. Click a project for the details.
Hover over or select a field to see the tools I use and where I've applied them. Skills connect back to actual projects, not just a long stack of logos.
Building applications with Python and JavaScript, with Flask for API routes and web services, and HTML/CSS for the user-facing layer.
I'm interested in what happens after the prototype — when the interface is being used, the data isn't perfect, and the software still needs to make sense.
Whether it's a career recommendation app, a CRM assistant, or a local model serving workflow, I enjoy understanding the entire problem before choosing the technology.
I'm open to interesting conversations about software, product work, AI development and technical collaboration.