Clearwater CEO Sandeep Sahai is leading a transformation in how institutional investors harness data to strengthen decision-making and operational resilience.
The role of enterprise software is evolving. Efficiency alone is no longer sufficient; organizations require intelligence at scale. Automated investment management, performance measurement and risk analytics are becoming critical components of modern investment infrastructure. These capabilities enable firms to manage complexity, improve transparency and respond to market dynamics with confidence.
Alternative investments raise the stakes
The growth of alternative asset classes is accelerating this shift. While equities data is relatively standardized and accessible, private credit and other alternatives remain opaque and fragmented. “It takes roughly seven times the processing and human power to tackle $1bn of alternative assets versus $1bn of equities,” says Sahai. If companies want to conserve headcount but achieve more transparency in alternatives, they must look at technology instead.
“Generative AI allows you to sift through vast quantities of data and provides analysis for you – it can’t replace the analyst but can make them twenty times more efficient.”
“Generative AI allows you to sift through vast quantities of data and provides analysis for you – it can’t replace the analyst but can make them twenty times more efficient.”
Sandeep Sahai, CEO, Clearwater Analytics
Prioritizing propriety data and developing it incrementally gives businesses a competitive edge. Investors expect immediate access to actionable insights, yet many organizations are not designing for that reality. Clearwater is.
AI is becoming the first line of defense in data verification. Clearwater’s’ C1 GenAI allows investors to query a report and get an instant assessment – rather than go through the usual manual inquiry process. This level of speed and responsiveness helps investors to understand risk, manage exposure, and report more effectively.
The direction of travel looks optimistic – reducing the necessity for human input. “If AI can address 10% of queries today, it may address 50% tomorrow and 85% the day after.”
But Sahai cautions that companies waiting for generative AI to be perfect will be left behind: “Even if 40% of the time you’re right, clients are much happier.”
To sustain momentum, companies should pursue short-term projects rather than chase technology for technology’s sake. “Building consensus and aiming for a clear-cut return in a meaningful time horizon is crucial to sustaining a generative AI program.”
Building a front-to-back platform
Clearwater’s recent acquisitions reflect its ambition to deliver a complete investment lifecycle solution. The purchase of Enfusion added front-office capabilities to Clearwater’s established middle- and back-office strengths. Combined with the acquisition of Beacon, which brought advanced risk analytics and developer infrastructure, Clearwater is now positioned to offer the first cloud-native front-to-back platform for the investment management industry. These strategic moves aim to eliminate fragmented workflows and enable faster, data-driven decision-making across the entire investment lifecycle.
Anticipating market needs
While the next two years will not hinge on acquisitions, Sahai is clear that M&A will remain part of Clearwater’s longer-term strategy. “We think about M&A when it is strategically thought out. Financial returns matter, but they never drive our decisions. The bedrock of any M&A decision is thinking ahead about what the market will want.”
That forward view is particularly important in Europe, where clients typically purchase full systems rather than point solutions. “Our proposition is very strong in North America, but if Clearwater only had part of the answer, it would hurt growth in the medium to long term,” Sahai says.
Reading the deal environment
Sahai sees a clear divide in the current market for SaaS businesses. “Someone said to me today, what’s the difference between medium-sized SaaS companies and restaurants? It struck me how undifferentiated the coloring is right now,” he notes.
Companies with strong revenue growth, solid unit economics, cash flow generation and competitive moats should be valued highly, while those lacking proprietary data or defensible positions face real risk of disruption.
He draws a parallel between generative AI and the early days of the internet. “The internet was massive, as big as generative AI. But the companies that prospered were those that harnessed it to build new products – Netflix, Salesforce, Workday – not those focused on infrastructure like Netscape or AOL,” Sahai says. “In Clearwater’s case, we’ve had massive gross margin expansion because we are using generative AI to help our business become better, fast. We are completely changing how clients do reporting through agentic technology we’ve built around it.”
“We’ve had massive gross margin expansion because we are using generative AI to help our business become better, fast.”
Sandeep Sahai, CEO, Clearwater Analytics
Leadership built on intense passion and thoughtful innovation
Carefully guiding teams and clients through market cycles is key to Sahai’s success as a leader. He puts it down to having a strong goal, genuine motivation and the right tools.
“It’s the job of the leadership team to start with a powerful enough vision, build infectious passion, and then empower your talent. At Clearwater we have a reward system which clearly identifies what’s being measured – and crucially, tracking it. For five years we’ve guided and executed to precisely what we have said, and better.”
“It’s the job of the leadership team to start with a powerful enough vision, build infectious passion, and then empower your talent.”
Sandeep Sahai, CEO, Clearwater Analytics
Navigating the genAI transformation
Looking ahead, Sahai highlights the potential risks of generative AI at personal, community and global levels and urges a thoughtful approach.
While transformative, the internet continues to create massive echo chambers that feed content based on individualized data, making certain positions rigid, even binary. Generative AI will likely reinforce this trend.
“As those echo chambers become louder, you become wedded to that single point of view. So, technology can limit originality, thinking, and diversion of views. The lessons of the internet have not been learned – generative AI is the most transformative technology by far, but needs to be handled thoughtfully and with care,” he concludes.
