Building AoA Agent with Lovable and n8n
Learn how to build an AoA (Agent of Agents) using Lovable for the UI and n8n for workflow automation
Read more →Building beyond the boundaries of imagination
15+ years building scalable data platforms and AI solutions across media, healthcare, and AdTech industries. Expert in real-time analytics systems processing petabytes of data.
Developed HIPAA-compliant IT systems that reduced clinical documentation time by 62% and integrated multiple healthcare data standards (FHIR, HL7, CCDA) to process millions of patient records daily.
Consistently delivered 50-85% performance improvements through cloud architecture optimization, ML pipeline efficiencies, and distributed systems engineering across AWS and Azure environments.
Learn how to build an AoA (Agent of Agents) using Lovable for the UI and n8n for workflow automation
Read more →Design patterns and best practices for building modular AI agent systems
Read more →Physician co-pilot that saves clinicians time so they can focus on practicing medicine.
Read case studyThe Healthcare Knowledge Graph RAG with Neo4j, LangChain, and Llama 3 for enhanced clinical decision support.
Read case studyCollecting data from various EHR vendors and building a data warehouse following the Medallion Architecture.
Read case studySince I began programming in 2007, I've always wanted to create something that makes a lasting difference in the lives of billions. For me, healthcare technology is the ideal field where my impact can be exponentially greater.
Remember when you were cooking dinner, chopping away, and then - suddenly - the knife slipped? So does my wife, a talented violinist who almost lost her index finger in a kitchen accident. It's one of those incidents we see coming only in slow-motion, right before everything speeds up.
You can probably imagine the panic as we dashed to the local urgent care at around 7 p.m. To our surprise, there were no other patients there. You'd think we'd be seen immediately, but instead, the receptionist said the same old line, "You'll be called when the provider is ready." As I held my anxious wife within my arm's fold, I whispered comforting words into her ear, a meager attempt to stifle her fear of never returning to the stage.
However, the ticking hands of the clock engrossed us in a torturous waiting game. Would she ever play the violin again? Could we have gone to the emergency room? Probably, but who knows how much longer that would've taken? So we sat for an agonizing 45 minutes. Something about that didn't feel right.
Finally, a bright spot amidst the chaos — the attending provider was exceptional, reassuring us that the fresh cut, finely sliced by a new, sharp knife, was perfectly stitched back. On the drive home, the idea for Arcs Health took root in me. Rather than allowing our personal story to fade, I wanted to use it as a catalyst for change.
Luckily for my wife, she recovered in a few short weeks. Before we knew it, she was back on stage. But the whole incident left us wrestling with a bunch of scary "what ifs": What if we hadn't been lucky enough to have the right provider? What if we'd waited 30 minutes longer? What if she was told her arrival was too late, affecting the optimal healing of her finger and potentially causing a long-term impact?
I envisioned a future where waiting times would be nonexistent in our clinics. I saw our providers spending more time with patients, free from the usual tedious 'busy-work' that has become the norm in our healthcare systems. Picture providers finally say goodbye to 'Pajama Time' notes, freeing themselves from the headaches of prior authorizations and eliminating the pressures to squeeze more patient appointments into the day.
Jon has a solid background in the tech industry, recognized for his strong work ethic and leadership in fast-paced startups. He's very involved with LLM, Data, and Cloud. Before joining Arcs Health, he sharpened his technical skills as a Senior Solution Architect at The Trade Desk and a Senior Software Engineer at IBM's Thomas J. Watson Research Center.
Jon is versatile across the entire tech stack in data engineering and machine learning. He can take on roles such as product manager, software engineer, solution architect and client facing account manager. With over a decade of experience in designing and managing data-intensive applications using Spark, AWS, and Databricks, he has a proven history of handling massive datasets up to 2.6 PB and real-time streaming data.
In addition to his strong data engineering skills, Jon is also a hands-on AI engineer with a solid grasp of LLM pre-training, fine-tuning, and advanced RAG techniques.
Jon also holds an M.S. in Computer Science from New York University.