Businesses are transcending the limitations of basic AI tools and embracing more sophisticated, domain-specific systems. These advanced solutions are designed to integrate deeply with industry knowledge, allowing organizations to enhance efficiency, drive innovation, and make more informed decisions tailored to their specific fields. In this podcast, Priya Dialani speaks with Ranga Kanapathy, Global CTO at Altimetrik, about why specialized AI models are becoming essential and how businesses can adopt them effectively.
A: Ranga Kanapathy explains that Altimetrik, founded in 2012, focuses on digital and data-driven solutions across industries like banking, fintech, pharma, and manufacturing. With over 150 global clients and 11,000 engineers, the company emphasizes long-term customer value. His 30-year journey across PayPal and Visa helped shape strong expertise in data and global platforms.
A: He highlights that general AI lacks a deep understanding of complex industries. Areas like payments or pharma require precise handling of compliance, risk, and regulations. Domain-specific models reduce errors and improve trust, making them essential for real business outcomes.
A: He outlines four levels: prompt engineering, RAG, fine-tuning, and building custom models. Most companies stay in early stages, while advanced levels need strong expertise and investment.
A: Domain Forge acts as an orchestration platform. It allows businesses to start small, test use cases, and scale gradually without disrupting operations, making AI adoption more practical.
A: He explains that infrastructure costs are the biggest hurdle. Instead of building from scratch, most organizations fine-tune existing models and adopt step-by-step strategies based on their current systems.
This conversation highlights that enterprise AI success depends on focused execution, domain knowledge, and gradual scaling rather than one-size-fits-all solutions.