Few professionals in technology manage to balance corporate pragmatism with scientific precision the way Karishma Mandal does. As a Senior AI Product Manager at Cisco and lead infrastructure strategist at AIDNI, she has built systems that support tens of thousands of engineers and automate hundreds of millions of dollars in operational value.
Her fingerprints are on some of the largest enterprise systems of the decade. At Salesforce, she directs product strategy for over 55,000 MuleSoft API engineers, advancing adoption through structural efficiency and deep product insight. At CVS Health, she developed an automated rebate forecasting system that saved over $200 million, utilizing predictive clustering models and natural language pattern analysis. This achievement has garnered quiet admiration across the healthcare technology field.
With her new endeavour at AIDNI, Karishma aims to revolutionize the AI infrastructure for on-prem companies. The new hyperconverged architecture, as described by her, enables large enterprises to bring cloud capabilities to their in-house data warehouse. The overall potential for transforming on-premises architecture is projected to reach $137 billion by 2028.
Mandal’s work is neither theoretical nor confined to whiteboards. Her frameworks sit inside enterprise software used daily by thousands, determining how data moves, scales, and delivers insights. “Every decision has a chain reaction in enterprise systems,” she explains. “My job is to build that chain so efficiently that people forget it exists.”
Her journey began in Mumbai, where she earned a Bachelor’s degree in Computer Engineering before moving to Northwestern University for a Master’s in Engineering Management. The duality of those experiences, where mathematical rigor meets executive logic, became the foundation of her professional style.
BNP Paribas spotted her early promise, awarding her third place in its annual innovation awards for an employee productivity framework that was later integrated across several departments. It was an early validation of her capacity to turn abstraction into measurable output. From there, she moved through SCI Pvt. Ltd. and SAP America, where she learned to compress delivery cycles for large-scale products into weeks rather than quarters.
At CVS Health, her team developed a forecasting platform that converted disjointed pharmaceutical data into actionable predictions. Using DBSCAN clustering and language models, her system parsed complex rebate structures into a single, automated pipeline. The outcome of hundreds of millions saved wasn’t a lucky strike; it was a direct result of her habit of testing theoretical models in live environments.
Her influence expanded further at Salesforce. Managing large-scale integration for the Anypoint platform, she oversaw usability studies and gateway architecture that increased adoption by seven percent across internal product lines. That may sound modest, yet at Salesforce’s scale, seven percent translates into tens of thousands of developers working faster, with fewer dependencies and lower latency.
Mandal’s leadership style differs from the textbook image of product management. She prefers precision to persuasion. She is often described as the calm within chaos, a manager who reads API metrics like others read music. Her method centers on alignment between design logic and human behavior.
Her colleagues at Salesforce call her an “architect of flow,” a reference to how she reduces friction between engineers, data, and systems. She sees product management not as a discipline of features but of connections. “Good infrastructure doesn’t scream for attention,” she says with a half-smile. “It just works quietly, consistently, and at scale.”
At AIDNI, Mandal extends this philosophy into large-scale infrastructure strategy. She leads the development of AI-driven data systems for enterprise clients that demand reliability amid market volatility. Her focus remains on turning complex technical requirements into clear, maintainable products that withstand real-world pressures. It is the kind of engineering that seldom draws headlines yet supports billion-dollar operations behind the scenes.
Her frameworks now circulate internationally. Within Salesforce, her methodologies are referenced across the developer network and cited in internal documentation used by engineering teams worldwide. She built a forecasting tool for CVS Health, using a technique called DBSCAN which got noticed by people working with health data who want to update how drug prices are set. As a result, her work, albeit understated, has a real influence on significant organizations worldwide.
Mandal decides what the rest of the industry will focus on. She pitched her thoughts in front of crowds of people at top-level conferences like the Salesforce Developer Conference (2024), and also spoke to over 200 product managers during SAP America Product Strategy Sessions (2022-2023), as well as at the CVS Health Healthcare Innovation Summit (2023).
She didn’t follow the expected path; instead, her career blossomed into something unexpected. Where others see product management as coordination, she treats it as translation, bridging the language of systems, executives, and engineers. She avoids the glamour of marketing launches and focuses instead on engineering truth: stable systems, measurable savings, replicable models.
Colleagues describe her as someone who “makes complexity readable.” It’s a fitting description for a technologist whose fingerprints are evident in enterprise frameworks for both infrastructure and management tools.
Her name has been featured across various news outlets, including Business Insider, Financial Express, and Hindustan Times, often in connection with her work in automating processes at Salesforce and CVS Health. She seemed known for her LinkedIn tips, yet she held deeper skills. Those initial impressions barely touched on what she truly did - designing systems that brought in huge revenue, a fact overlooked until now
Karishma Mandal’s story isn’t about luck or visibility. It’s about precision as a form of leadership, systems thinking as strategy, and the quiet assertion that true engineering excellence doesn’t announce itself; it sustains everything around it.