According to CTO and yoga teacher Kishore Subramanian, the physical practice of yoga (asana) is merely preparation. Its true purpose is to train the body to sit still with an erect spine, which is the foundation for effective meditation. This practice, in turn, unlocks creativity and sustained energy for knowledge workers.
To demystify the complex world of Product Lifecycle Management (PLM) for hardware, CTO Kishore Subramanian uses a simple, powerful analogy. He positions Propel as the equivalent of Atlassian, which provides tools like Jira and Confluence for the software development lifecycle. This makes the value proposition instantly understandable.
A practical framework for developing agentic AI is to first map the human workflow. Break down the task into discrete steps, identify which ones can be automated, ensure the necessary data is available, and then build the underlying tools and code blocks. Don't start with the technology; start with the human process.
Instead of building a rigid, one-size-fits-all solution, Propel built its product lifecycle management tool on Salesforce. This provides inherent flexibility in data models, processes, and UI, allowing it to adapt to the unique needs of med-tech, high-tech, and consumer goods clients without creating a bloated product.
AI agents review "engineering change orders"—the hardware equivalent of software pull requests—to flag risks and compliance gaps early. This "shift left" approach prevents costly downstream errors in physical products, where fixes are exponentially more expensive than a software patch and can involve factory recalls.
Propel chose Salesforce's AgentForce 360 to build its AI agents, citing the platform's built-in security, governance, and reasoning engine. This de-risked the project and allowed them to focus on their domain expertise, shipping a product to customers in just six months—a speed unachievable with nascent open-source tools.