As the founder of Rutherford Labs, I lead a forward-thinking R&D company specializing in next-generation AI, multi-agent systems, and intelligent automation solutions. I also provide C-level operational leadership on a fractional basis, partnering with CEOs and investors to install scalable operating systems, drive efficiency, and accelerate profitable growth. My work focuses on the critical intersection of people, process, technology, and commercial strategy. Key Engagements & Products: Fractional COO Engagement: Global AI/ML Delivery Partner Architecting and leading the global AI/ML consulting and staffing practice for enterprise clients. Responsible for developing the operational framework, delivery methodologies, and team structures to provide elite AI/ML talent solutions in highly regulated industries (Healthcare, Finance, Insurance). ► Product Development: VocalBrain Led the incubation and development of VocalBrain, an AI-powered platform designed to enhance learning experiences. Guided the product from concept to profitability. • Engineered the product's entire operational and technical infrastructure, including a full-stack AI-driven platform (GCP, Vertex AI, LLMs) and a cross-functional delivery team. • Secured initial funding through incubator and accelerator programs by articulating a clear vision, a lean operational plan, and a compelling market opportunity. ► Product Development: OMNAgent Spearheading the design and development of OMNAgent, a multi-agent framework that redefines enterprise automation. OMNAgent treats platforms like CRM and ERP as dynamic environments where autonomous agents, powered by LLMs, reason, plan, and execute complex tasks. • The framework utilizes a dynamic knowledge graph as a collective "brain," enabling intelligent collaboration between agents to solve complex problems in areas like sales forecasting, customer retention, and even drug discovery.

Architected enterprise-scale data and AI/ML strategies for major healthcare clients operating within complex HIPAA-compliant environments. Functioned as a de facto operational leader, bridging the gap between client business needs and technical delivery teams to ensure project success and commercial value. ► Led full-cycle implementations of large-scale systems on Azure and GCP, designing data-driven AI solutions for risk assessment models and health chatbots that directly impacted client revenue cycle management. ► Established and led a Center of Excellence (CoE) to standardize best practices for AI/ML development, improving delivery consistency and efficiency across multiple client engagements.

Directed a data mining and analytics team focused on identifying fraud and ensuring claims integrity for major healthcare payers. Championed data-driven decision-making to support critical business functions like underwriting and risk assessment. • Managed the full development lifecycle for a portfolio of six enterprise applications, leading a technical team of 10+ developers, data analysts, and QA engineers.1 ► Identified and mitigated significant instances of fraud, optimizing reimbursement accuracy and directly protecting the company's bottom line through the strategic application of data mining and AI/ML tools. ► Critically observed how rigid organizational structures, such as a strict "contributor vs. manager" policy, created operational bottlenecks and stifled cross-functional collaboration—insights that now inform my approach to building flexible, high-performance teams.