Priya Vijayarajendran, ASAPP Inc. CEO: “We’re focused on expanding what AI agents can safely and reliably own within enterprise operations. There is significant momentum ahead, and we’re just getting started.”

ASAPP Inc. was founded to close a gap most enterprises had learned to live with: the distance between customers seeking help and the organizations built to serve them. Contact centers sit at the heart of that relationship, yet for years innovation in the space amounted to surface-level upgrades. New dashboards. Faster routing. Slightly smarter scripts. The underlying system, fragmented and reactive, remained intact.

ASAPP took a different path. The goal was never to ship a marginally better chatbot. It was to design an enterprise-grade AI stack capable of resolving complex customer interactions end to end, without sacrificing trust, safety, or human judgment. That meant rethinking the architecture from the ground up. Instead of layering automation on top of legacy processes, ASAPP built a system where intelligence, context, and action work together inside production environments. At the center of that vision is the Customer Experience Platform, or CXP. Built specifically for high-volume, high-complexity contact centers, CXP integrates deeply into existing enterprise systems, from CRM and CCaaS platforms to billing, identity, and workflow engines. There is no rip-and-replace disruption. The platform connects to what enterprises already use and orchestrates it in real time. Above that foundation sits a reasoning and orchestration layer designed to understand intent, retrieve structured context, invoke tools, and execute actions across systems seamlessly. Every interaction becomes structured intelligence. Over time, that intelligence sharpens prediction, improves personalization, and strengthens operational insight. Human oversight is not bolted on at the end. Governance, auditability, and control are embedded throughout the stack.

Under the leadership of Priya Vijayarajendran, ASAPP continues to advance this systems-level approach. What this really means is simple: better conversations are only the starting point. The real outcome is measurable business performance delivered through governed, production-grade AI built for the realities of enterprise scale.

In conversation with Priya Vijayarajendran, CEO of ASAPP Inc.

ASAPP describes its approach as "agentic" and "AI-native," moving beyond chatbots to dedicated AI agents. What is the fundamental technological and philosophical difference between an "agent" that acts and an "assistant" that answers, and why does this represent the future of customer experience?

Most enterprises try a lot of AI projects but don't mainstream because models are probabilistic. It is great for experimentation and discovery but not enterprise robust enough to be rolled out in production.

Agentic refers to notion of understanding intent of the conversation , passing the right  context which typically comes from contact center domain expertise of understanding interactions in voice or digital, knowing which data is relevant in which turn of conversations, orchestrating prompts to tasks and keeping simple tasks simple enough and invoking reasoning when its needed,  successfully containing the interaction by answering , invoking tool calling , actioning through API or through integration . A platform built with all of the above in a most low friction and low code way is AI Native.

Abstracting all of this being the personalized agent at all times, understanding, answering and solving and pulling in human oversight or escalation is the future of customer experience.

Your Customer Experience Platform (CXP) is built to unite systems, data, and workflows without a "rip and replace" approach. For complex enterprises, why is this integrated, connective capability the true innovation, more so than the AI models themselves?

Handling a customer flow for years has been learnt, configured as deterministic rules, and Agents have being coached with best practices. It takes any AI native platform to earn trust and enable Agents to evolve solving complex problems and delegate what AI Agents can do best. This integrative approach ensures no business disruption and in the most guided way enables transformation of CX.

You report dramatic results like a 54% containment increase in 90 days for an insurer. What specific innovations within your platform such as real-time reasoning or integration depth enable such rapid and significant performance leaps that pure automation tools cannot achieve?

Three things - reasoning, integration depth, and control.

First, our agents reason in real time, allowing them to adapt to nuanced, multi-turn conversations rather than following static scripts. Second, they are deeply integrated into enterprise systems, which means they can actually complete tasks (policy changes, account updates, claims actions) rather than deflecting customers.

Finally, performance is continuously governed through real-time monitoring and human oversight. This combination allows enterprises to scale automation rapidly while maintaining accuracy and trust, which is why results materialize in weeks, not years.

The Human-in-the-Loop (HILA™) workflow is central to your model. How does this designed collaboration between AI and human agents optimize outcomes, and what does it reveal about your brand's core belief in "elevating human performance" rather than replacing it?

HILA™ is designed for collaboration, not a fallback in our model. It ensures that humans remain in control of complex, sensitive, or novel scenarios while AI handles high-volume, repeatable work. Over time, insights from human interventions improve the system, raising overall performance.

This reflects a core belief at ASAPP that the goal is never to remove humans from the equation, but to apply human judgment where it matters most. The result is better outcomes for customers, agents, and the business.

Forrester named ASAPP the "undisputed leader in AI-led innovation." Looking at the competitive landscape, what core innovation do you believe has created this market leadership, and how does it set the standard for what an innovative brand in enterprise AI should deliver?

Our leadership comes from execution. We focused early on building production-grade systems for the most demanding enterprises - those with scale, regulatory complexity, and zero tolerance for failure. That required solving for integration, safety, and governance alongside AI capabilities. The result is a platform that works in the real world, at scale. That’s what enterprise customers ultimately value.

What does the future hold for your company and its customers? Are exciting things on the way?

We’re focused on expanding what AI agents can safely and reliably own within enterprise operations. There is significant momentum ahead, and we’re just getting started.

For customers, that means higher automation ceilings, faster resolution, and better customer experiences without increasing operational risk. For ASAPP, it means continuing to raise the standard for what enterprise AI should deliver: measurable impact, accountability, and trust.

Meet the leader behind the success of ASAPP Inc.

Priya Vijayarajendran is the Chief Executive Officer of ASAPP, where she leads the company’s efforts to advance enterprise AI automation in contact centers. ASAPP is a leading provider of AI-native solutions designed for large, complex customer operations.

With over three decades of experience in enterprise software, Priya has held senior leadership roles across multiple technology companies such as Microsoft, IBM, SAP, specializing in building cloud-native, scalable platforms that solve real business problems. She is a deeply data-driven leader known for translating advanced technology into measurable outcomes.

Priya is a trusted advisor to customers and boards, a recognized voice in enterprise AI, and an active mentor and advocate for the next generation of technology leaders, particularly women in tech.

“Our leadership comes from execution. We focused early on building production-grade systems for the most demanding enterprises - those with scale, regulatory complexity, and zero tolerance for failure.”