Khuze Siam is a founder of tech-first companies and the visionary behind ProdWrks, a product thinking community and publication. With a deep commitment to user-centric product strategy, Khuze has collaborated closely with early-stage and growth-stage startup founders, helping them scale from 0 to $10 million+ in annual recurring revenue (ARR).

He built Hisabing to bring technology to India's grassroots small and medium businesses. He also helped co-found Startups Club, a premier destination for early-stage startups. 

INDIAai interviewed Khuze Siam to get his perspective on AI.

AI plays a crucial role in helping startups scale. What practical ways have you integrated AI to help startups achieve significant growth, such as from 0 to $10M+ ARR?

We’ve seen first-hand how AI can be a startup game-changer when scaling quickly and efficiently. For instance, we’re partnering with a health tech startup in the Ayurvedic treatment space, where patients typically have many questions before committing to therapy. Previously, they relied heavily on their call centre to handle inquiries, but now, with an AI-powered chatbot, we’ve transformed the entire lead conversion process. This chatbot answers patients' questions about their conditions and guides them to the right treatments, schedules doctor appointments, and reduces the need for human intervention. The result? Faster conversions, better patient experience, and a significant reduction in operational costs.

Similarly, we’re building a solution in the agetech space, focusing on a segment often overlooked in the digital revolution: seniors. While younger generations have embraced technology, many seniors face digital access barriers. That’s where we come in. We’re developing a highly personalized companion bot that answers their health-related questions and motivates them, assists with tasks like booking cabs or ordering food, and helps them navigate the digital world through conversational AI. Essentially, we’re bridging the digital divide for seniors by delivering technology that feels intuitive and natural, enhancing their quality of life.

These AI solutions don’t just solve problems—they create opportunities for startups to scale faster, serve customers more effectively, and, ultimately, grow their ARR dramatically.

Large Language Models (LLMs) and gamification are transforming product design. How do you leverage these tools in your projects, and what opportunities do they present for early-stage founders?

LLMs bring a transformative ability to personalize user experiences through generative technologies, turning interactions into meaningful and engaging moments. For instance, we’ve leveraged LLMs to elevate the online shopping experience by allowing users to virtually try on products, generating hyper-realistic images that reflect their unique features. Beyond that, we integrated social sharing capabilities, letting users share these images with friends and family to gather feedback on potential purchases. It doesn’t just create a personalized shopping journey—it fosters a community-driven experience that drives user engagement and boosts conversion rates.

On the gamification side, we’ve used elements like aspirational goal-setting to design wellness paths for a fitness app. By employing generative AI, we create vivid, aspirational images of what users could look like as they hit their fitness milestones. It motivates users and builds anticipation and excitement, turning fitness tracking into an engaging journey rather than a tedious task.

The opportunities are enormous for early-stage founders. By combining LLMs and gamification, they can design products that connect deeply with individual users and keep them coming back through engaging personalized experiences. The ability to blend AI-powered personalization with game-like motivation mechanics opens up a new world of possibilities for startups looking to build sticky, scalable products.

How can AI accelerate digital transformation for traditional businesses transitioning into tech-first models? Can you share any examples from your work?

While software has revolutionised industries for years, AI is set to take this transformation to the next level. I often say, "Software is eating the world, but AI is going to eat software." What makes AI so powerful is its ability to democratize access to technology. We’re on the cusp of a future where even individuals without coding expertise can build digital solutions to solve niche problems. Imagine businesses of all sizes, from local retailers to global enterprises, empowered to create AI-driven tools that solve unique challenges without needing a team of developers.

It happens because AI reduces the complexity barrier, taking us from writing code to simply using ordinary language to create software. When combined with low-code and no-code platforms, AI allows traditional businesses to build custom software solutions that were once out of reach. In our work, we’ve seen this in action. For example, a client in the retail space with no prior tech experience leveraged AI to build a recommendation engine for their customers. What once required significant resources and technical know-how was made possible through accessible AI tools, transforming their digital capabilities and enhancing customer engagement.

Building teams for AI-driven product development requires unique skills. How do you approach team building, and what skills do you consider critical for AI-powered projects?

At Siam Computing, we’ve made it a priority for every team member to be well-versed in AI regardless of their role. From prompt engineering to Retrieval-Augmented Generation (RAG) and fine-tuning models, our team is equipped with the knowledge to leverage AI tools effectively. This approach has resulted in a 40% optimization in our development and engineering processes. By embracing AI, we’ve unlocked efficiencies and empowered our team to build smarter and faster.

The true game-changer isn’t just technical skills—it’s mindset. The most critical skill for any AI-driven project is being open-minded, adaptable, and eager to learn. In an era where AI is evolving rapidly, clinging to old methods is a sure way to get left behind.

The ability to unlearn outdated approaches and relearn new techniques is key. We encourage our team to be proactive, constantly learning and adapting to new AI tools and trends. If we behave like ostriches with our heads buried in the sand, ignoring the changes around us, we’ll miss out on AI's incredible opportunities. In short, fostering a culture of curiosity and continuous learning is how we build teams that are ready for the future of AI-driven product development.

Given your expertise in HealthTech, what role do you see AI playing in the future of these sectors, and how do you envision the next significant AI-driven innovations?

AI is already reshaping HealthTech profoundly, and the future is even more exciting. One of the key trends we’re seeing is AI’s ability to drive a more patient-centric model. In healthcare, AI will continue to move the focus from hospitals to home-based care, enabling patients to manage chronic conditions with remote monitoring and AI-driven tools. This shift enhances convenience and reduces pressure on hospitals, improving healthcare access and efficiency.

AI is also revolutionizing diagnostics and treatment personalization. With advances in AI, healthcare providers can use sophisticated algorithms to mine medical data, predict outcomes, and tailor treatment plans to individual patients with unmatched precision. For example, AI is being used to accelerate drug discovery, significantly cutting down the time and cost of finding new treatments.

Looking ahead, we anticipate breakthroughs like AI-powered digital twins—virtual models of patients that simulate their health data and predict how they will respond to treatments. This approach could dramatically improve the effectiveness of personalized medicine.

AI will also power the next generation of preventive care, where tools such as wearables, continuous monitoring devices, and predictive algorithms will identify potential health risks before they become severe, enabling early interventions.

Regarding business innovation, AI democratization means that even smaller health tech startups can leverage advanced AI tools without deep technical expertise, accelerating their entry into the market.

These innovations don’t just improve care; they redefine how healthcare is delivered, making it more proactive, personalized, and efficient.

I’m excited about the future of AI in healthcare because it’s not just about automating tasks—it’s about fundamentally reimagining how we care for people. The opportunities for founders entering this space are immense, and the tools to make a real impact are more accessible than ever.

You emphasize user-centered design. How can AI enhance the user experience in product strategy and development, and what are some key challenges in balancing AI innovation with user needs?

I often say, "The best product is going to be a product of one." With AI, each experience can be hyper-personalized, meaning what I experience on a product will vastly differ from what you do, explicitly tailored to individual needs. AI allows us to deliver this level of personalization at scale, from dynamic content curation to real-time adaptive interfaces, creating a bespoke experience for every user.

However, one key challenge is ensuring that AI enhances the user experience without introducing unnecessary complexity. This is where I like to apply the electricity test: if AI in a product operates so seamlessly that users don’t even realize it’s there—much like electricity—it’s likely adding value. But if AI becomes too visible or starts adding friction to the user journey, it’s a sign that it’s over-engineered.

For example, we recently advised a startup against adding a summarization feature. While it sounded innovative, the feature created confusion during otherwise simple transactions. It is a prime example of AI for the sake of AI, which ultimately detracts from the user experience rather than enhancing it. Users want efficiency, not unnecessary layers of interaction.

The challenge is ensuring that AI is an invisible enabler seamlessly integrated into the product’s flow. When AI passes the electricity test—delivering value without being noticed—it has the potential to create intuitive, user-friendly experiences that genuinely improve engagement and satisfaction. Ultimately, AI should solve problems effortlessly, not intrusively, and the ability to strike this balance is key to successfully incorporating AI into user-centred product strategies.

What role does AI play in enhancing marketplace platforms' effectiveness and user experience, and how do you see it evolving in the next few years?

At its core, a marketplace solves two fundamental problems: discovery and trust. With the abundance of choices available today, finding the right product without getting overwhelmed is key. AI plays a crucial role in enhancing discovery by offering personalized recommendations, ensuring users can quickly find what they need without falling into the paradox of choice. Whether leveraging machine learning algorithms to analyze browsing history or using natural language processing to understand user intent better, AI helps streamline the entire product search process, creating a more intuitive experience.

AI also contributes significantly to trust. One great example is how Amazon’s AI-driven summarization of reviews helps users make informed decisions faster, distilling thousands of reviews into concise summaries highlighting key insights. It fosters a sense of trust in the product and the seller. Similarly, AI-powered vendor tools can assist sellers in crafting detailed, trustworthy profiles with accurate and helpful information, improving transparency on the platform.

Finally, AI’s ability to detect fraud is pivotal in building trust in marketplaces. By flagging suspicious products, vendors, and transactions in real time, AI ensures that users and sellers are protected from fraudulent activities. AI will continue refining these systems as they evolve, becoming even more effective in discovery and trust-building efforts.

What advice would you give to someone who wishes to join your team?

Be open-minded, embrace learning and remember to have fun.