In today’s AI-powered enterprise world, copilots draft emails, optimize code and even help make hiring decisions. That means security has moved far beyond firewalls and compliance checklists. As generative systems process sensitive data and deliver critical outputs, trust has become the new benchmark, not just for adoption, but for survival.

Few understand this paradigm shift more intimately than Achal Singi, Vice President at WestBridge Capital, and a Forbes Financial Council member. Having evaluated hundreds of platforms across AI infrastructure, developer tools, and enterprise SaaS, Singi has emerged as a vocal proponent of one principle: scalable AI is secure AI.

“We are not just investing in performance anymore, we are investing in predictability. Trust is not the end goal. It is the product.”

From Model Risk to Intelligent Containment

Generative AI introduces a new kind of attack surface, one that is probabilistic, non-deterministic, and often opaque. Traditional security models, designed for deterministic systems, fall short when asked to guard against hallucinations, prompt injections, or data leakage from large language models. The risks are no longer just technical, they are reputational, operational, and existential.

That is why Singi backed Nightfall, an AI-native data loss prevention (DLP) platform. Designed specifically for LLM contexts, Nightfall automatically detects and redacts sensitive information, enabling developers to build secure-by-default AI products. “The way we think about AI safety has to change,” Singi notes. “This is not about perimeter defense, it is about continuous, intelligent containment.”

Singi shared this exact perspective with enterprise security leaders grappling with AI adoption as a featured speaker at the 2023 CISO Dinner. It is not just about tools, it is about architecture that supports trust at scale.

“If your infrastructure cannot explain itself, it cannot protect itself,” Singi explains. “We fund companies that make systems self-aware and self-defensive.”

Systems that Learn, Respond, and Secure

Security today is as much about workflows as it is about walls. As AI systems influence customer service, DevOps, and legal pipelines, the challenge is not just detection, it is action. The ability to flag, route, and escalate risk is becoming a differentiator.

Take SupportLogic, one of WestBridge’s investments that uses AI to predict customer escalations before they happen. It exemplifies a deeper philosophy: security is a contextual signal. When embedded into systems with real-time stakes, it becomes proactive, not reactive.

Singi’s role as a judge for the 2025 Stevie Awards for Technology Excellence further underscores his commitment to redefining what innovation looks like. “Intelligence without judgment creates noise,” he explains. “Great systems know when to act, and when to escalate.”

What made WestBridge’s follow-on $55M investment in Innovaccer so significant was the strategic clarity behind it. Singi led a deep-dive evaluation, partnering with physicians, payers, and technologists to map how AI agents could drive measurable improvements across fragmented health systems. The conviction was not abstract: it was built from user feedback, regulatory assessments, and go-to-market readiness. A secure and intelligent health system is one the most fundamental needs of today.

Investing in Risk Surfaces, Not Just Revenue Lines

For most investors, risk is a downside. For Singi, it is a roadmap. The next decade of enterprise AI will not be won by flashy features but by systems that measure and mitigate risk at scale.

This perspective shaped WestBridge’s strategic involvement with DuploCloud, a DevOps automation platform that empowers engineering teams to deploy secure, compliant infrastructure in minutes—not months. By transforming cloud compliance and provisioning into a unified control plane rather than a patchwork of scripts and dashboards, DuploCloud reflects a broader thesis: that operational intelligence starts with seamless visibility and ends with automated secure action.

Singi’s approach to investing, across platforms like Postman, Lucidity, Tessell, DuploCloud, and Nightfall, centers on one shared attribute: resilience by design. Whether it is embedded compliance, policy-as-code, or intelligent redaction, these technologies share an underlying principle. They do not wait for the breach. They anticipate it, model it, and prepare for recovery.

Trust, as Strategy

As security becomes the organizing principle of AI design, investors like Achal Singi are shifting their lens. It is no longer about market size, it is about risk surfaces, explainability, and intelligent recovery.

“The future of enterprise intelligence is not who can move fastest, but who can move securely at scale. That is the real edge.”

And investors who understand that, who recognize trust not as a checkbox, but as a continuous system state, will define the next generation of AI market winners.