Agentic AI and the Future of Customer Experience: In Conversation with Vishal Sharma, CTO, SearchUnify
At a time when enterprises are racing to balance automation with authenticity, agentic AI has emerged as a transformative force in customer experience. More than a buzzword, it represents a shift toward intelligent systems that can act with autonomy, learn adaptively, and collaborate with humans to deliver hyper-personalized and trustworthy experiences.
At the forefront of this transformation is Vishal Sharma, Chief Technology Officer at SearchUnify, an enterprise agentic platform by Grazitti Interactive. Built on a powerful machine learning and insights engine, SearchUnify includes a suite of AI-powered products such as Cognitive Search, SUVA—the world’s first Federated, Information Retrieval Augmented Chatbot—Agent Helper, Knowler, Escalation Predictor, and Community Helper. Together, these tools empower organizations to revolutionize information discovery and elevate support outcomes across global enterprises.
In this exclusive CXQuest interview, Vishal shares how SearchUnify is leading the charge in deploying agentic AI to create seamless, transparent, and culturally adaptive customer experiences.
Interview with Vishal Sharma, CTO, SearchUnify
1. How are you leveraging agentic AI to create seamless, personalized experiences while building trust with customers? What challenges have you faced in implementation?
At SearchUnify, we use agentic AI to move beyond scripted, rule-based interactions and deliver experiences that are genuinely adaptive. Our systems interpret user intent, understand context, and dynamically adjust responses in real time. This allows support experiences to feel relevant, intuitive, and less mechanical, while still operating at scale.
Equally important is our human-in-the-loop approach. As agentic systems take on greater autonomy, trust becomes non-negotiable. Customers want clear assurance that critical decisions are guided by human judgment. By embedding human oversight at defined decision points, we ensure outcomes are not only efficient, but also fair, auditable, and responsibly governed—addressing both trust and liability considerations.
The primary challenges have been practical rather than conceptual. Agentic AI is only as effective as the data, knowledge sources, and workflows that support it. Inconsistent data or poorly integrated systems can undermine outcomes. Much of our effort has therefore focused on building strong foundational guardrails, ensuring autonomy is introduced in a deliberate, controlled, and reliable manner.
Growing Demand for Transparency in AI-driven Decisions
2. How are you addressing the growing demand for transparency in AI-driven decisions, and what strategies are proving effective in building customer trust?
As AI becomes increasingly customer-facing, transparency is essential to sustaining trust—both in the outputs and in the data and logic behind them. At SearchUnify, we address this by designing AI systems with clear operational guardrails that define how decisions are made and escalated.
The most effective transparency is experiential rather than theoretical. When accountability, traceability, and explainability are embedded directly into everyday workflows, users gain confidence naturally—without being burdened by complex policy language or technical explanations. Our focus is on providing users with clarity and visibility into how decisions are guided, rather than exposing every algorithmic detail. This balance helps reinforce trust while keeping the experience intuitive and usable.
Balancing Global Scalability and Customer Experience
3. How are you balancing global scalability with localized, culturally relevant customer experiences to stay competitive in 2026?
Global scale often pushes organizations toward standardization, which can dilute local relevance. AI presents an opportunity to break that trade-off—provided flexibility is built into the system from the outset.
Our approach is to maintain a strong common foundation while enabling localized adaptation. A shared software and data layer ensures consistency, governance, and operational efficiency. On top of that, localized knowledge—covering language nuances, cultural expectations, and regulatory context—shapes how experiences are delivered in different regions. Agentic AI is particularly well suited to this model, as it can dynamically adapt behavior without requiring separate deployments or fragmented systems.
Looking ahead to 2026, the companies that will lead are those that treat global scale and local relevance as complementary, not competing, priorities. Customer expectations around tone, responsiveness, and escalation vary significantly by region. Capturing these nuances requires close collaboration between AI systems, technical teams, and local stakeholders—and that is where agentic AI can deliver a meaningful competitive advantage.
CX Takeaway: Building Trust in the Era of Agentic AI
| Key Principle | SearchUnify Strategy | Business Impact |
|---|---|---|
| Human-in-the-Loop | Oversight at critical decision points | Fairness + Reduced liability |
| Experiential Transparency | Workflow-embedded explainability | Intuitive trust without complexity |
| Global + Local | Shared foundation + regional adaptation | Scalable relevance across markets |
Agentic AI succeeds when autonomy meets accountability—delivering personalized experiences at global scale.
Agentic AI in Customer Experience: Closing Thoughts
As Vishal Sharma highlights, the future of customer experience lies in building systems that think, learn, and adapt—while staying grounded in human judgment and ethical governance. SearchUnify’s commitment to combining intelligent autonomy with transparency and localized relevance positions it as a global leader in redefining how AI interacts with customers.
Agentic AI is not just reinventing workflows—it’s reimagining trust, empathy, and engagement at scale.
Connect & Explore:
SearchUnify Website | Vishal Sharma on LinkedIn
Published on CXQuest.com | January 2026
