AiThority Interview with Lokesh Jindal, Head of Products at Axtria

How is GenAI impacting workflows for the life sciences industry? Lokesh Jindal, Head of Products at Axtria weighs in with some observations in this AiThority interview:

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Hi Lokesh, welcome to our AiThority Interview series. Can you walk us through your journey, from leading large enterprises to driving growth at Axtria?

Thank you! It’s been quite the ride. Managing the complexity of large enterprises taught me a powerful lesson: that impact at scale is hard, but once you crack the formula, the ripple effect is exponential. One of the most insightful things a CXO once told me was, “We often underestimate how much impact one person can make.” That stayed with me.

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At Axtria, I’ve had the opportunity to bring this mindset to a dynamic, high-growth environment. Over the past five years, we’ve scaled our product business 3X. What excites me most is that we’re not tied down by legacy systems; we’re free to innovate and disrupt. From navigating large companies to building one, my journey has been about scaling impact through disruptive innovation.

Axtria emphasizes the “Data-to-Insights-to-Action” journey. How do its products bring this vision to life?

In today’s world, data isn’t an afterthought; it’s the starting line. While traditional applications were process-driven, modern systems must be data-driven. That’s where our product suite begins—with Axtria DataMAx, our trusted data cloud platform that sets the foundation for all insights.

From there, Axtria InsightsMAx.ai powers intelligent decision-making by embedding analytics within workflows. And because insight without action is just noise, our applications across Marketing Analytics (Axtria MarketingIQ), Customer Engagement (Axtria CustomerIQ), and Sales Performance Management (Axtria SalesIQ) ensure these insights translate into measurable business outcomes. We don’t just connect data points. We connect data to performance.

What’s your take on the role of generative AI in sales and marketing effectiveness?

We’re only scratching the surface of what GenAI can do for life sciences. At its core, GenAI is a content engine, and great marketing starts with great content. In a highly regulated industry, creating compliant content faster is a massive win.

Next comes transforming the pharma rep into a “Super Rep” by providing them with pre-call planning, during-call insights, post-call summaries, and personalized training—all powered by GenAI. As we move toward Agentic AI, we’re even envisioning virtual “Shadow Reps.” These will maintain healthcare provider relationships in areas not covered by human reps and bring context-aware engagement to life, just like a human would.

From content creation to cognitive copilots, GenAI is redefining sales and marketing from the ground up.

How does Axtria ensure data integrity, compliance, and scalability in its cloud products for global pharma clients?

We’ve always believed that data is a product, not just a byproduct, and we treat it with that level of respect. We are very particular about data integrity, compliance, and scalability, as the future of all products is to be data-centric instead of process-centric.

Our safeguard strategy rests on two powerful pillars:

• Fortress‑grade SaaS security. A leading global audit firm recently told us that Axtria’s security surpasses that of many large global enterprises. We run active, predictive controls that shut threats down before they blossom, layered with passive monitoring and a 24/7, finely‑tuned SOC that knows our infrastructure inside out.
• Data governance at hyperscale. Built on our Axtria DataMAx platform, every product inherits enterprise‑class integrity, lineage, and elasticity. Today, some of the world’s largest life‑sciences companies rely on this foundation to process global commercial data every single day. Native GDPR safeguards and the architectural flexibility to meet any regional regulation ensure compliance isn’t an afterthought; it’s baked into the blueprint.

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Can you highlight a recent product innovation at Axtria that significantly improved client outcomes?

One recent innovation that delivered an outsized impact is our IC Inquiries GenAI Agent. Incentive Compensation reports typically generate a flood of inquiries from reps; almost 20% of reports result in questions. Our GenAI agent now handles most of these queries autonomously, reducing the load on headquarters teams and dramatically improving rep satisfaction. Simple solution, big win. Innovation isn’t always flashy. Sometimes, it’s just solving the right problem at scale.

Before we wrap up, please share your approach to integrating AI and analytics in product roadmaps.

For AI to be truly effective, it must be embedded at the point of decision. When it sits on the side, adoption suffers. We ensure AI flows naturally within workflows so that it feels like a part of the process, not an add-on.

Another critical factor is the varying need for accuracy depending on the user. For example, pharma sales reps need very high accuracy since they don’t have the time to question or interpret AI-generated results, and errors can lead to immediate negative outcomes such as loss of trust. In contrast, HQ users may be okay with lower accuracy as they have more resources to validate and adjust outputs, or are already used to working with uncertain data for long-term strategic planning.

Finally, it’s important to trust that LLMs will continue to evolve and will improve rapidly. This means that even if accuracy is not perfect today, organizations should still plan to incorporate LLMs, because by the time the solution is deployed, the models will likely have matured to deliver the needed precision. It also means designing systems that can leverage the latest and most advanced LLMs, and just as importantly, considering when domain-trained private models make more sense for specific use cases.

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