As artificial intelligence transitions from experimental promise to real-world impact, few sectors illustrate this shift more clearly than the nutraceutical industry. At the intersection of science, regulation, and innovation, AI is no longer just accelerating product development; it is redefining how responsible health solutions are designed and commercialised.

In this exclusive interview with AI Spectrum, Amit Srivastava, Founder and Chief Catalyst of Nutrify Today, shares how NutriGPT India’s first ISO-certified AI platform for nutraceutical innovation is setting a new benchmark for evidence-led, regulation-aware product formulation. From its audited RAG architecture and millions of curated, scientist-verified data points to its biochemical, pathway-driven approach, NutriGPT is challenging the limitations of generic AI models and reshaping trust in AI-driven health innovation.

Srivastava also offers insights into how AI can bridge ancient nutritional wisdom with modern biochemistry, navigate complex global regulations, and ultimately transform the entire nutraceutical value chain through platforms like NutrifyGenie and the upcoming DealSphere ecosystem. Together, they paint a compelling picture of an industry on the cusp of a science-first, AI-powered future.

How does NutriGPT's audited RAG architecture and 12 million curated data points practically enhance accuracy and reliability compared to generic AI models?

NutriGPT is a lot more accurate and dependable than generic AI models since it uses a Retrieval-Augmented Generation (RAG) architecture that has been examined and is specialised to its field. There are about 40 scientists with Master's and PhD degrees who are experts in important fields, including toxicology, clinical research, chemicals and regulatory processes that check the platform's more than 12 million carefully chosen data points. The intelligence is scientifically sound and extremely pertinent to the nutraceutical industry, thanks to this human-verified layer.  Also, its method uses a "biochemical mindset," which means that every suggestion is based on the basic questions of product design: Why this ingredient, what specific biochemical pathway is being changed, what is the expected dosage, and what are the possible toxicity profiles and interactions.  This stringent, evidence-based approach is a fundamental shift from generic models that might rely on less-vetted, marketing-led data combinations, thereby establishing a new standard for validated, reliable product formulation.

Can you share specific examples or early case studies where small or mid-sized companies have successfully formulated or accelerated products using the platform?

The NutrifyToday platform highlights several Success Stories and Success Cases that demonstrate accelerated product formulation, often leveraging their AI platform, NutrifyGenie. These examples illustrate the rapid development of specialised nutritional products, such as the UB Gold CoEnzyme Q10 Supplement and Esperer Onco Nutrition, both of which were developed in a notable 9-month timeframe using NutrifyGenie. Other successful accelerated products include the Nutrihance Multi-Omega Softgel, Enorma PCOD Management Supplement, and Nutrihance Complete Nutritional Powder. Furthermore, the platform has supported innovation in delivery systems, as seen with the Nanoveda Mouth Dissolving Strips. There are also specific case studies at the company level that show how the platform has helped create unique and responsible dietary supplement portfolios in the market. These include Esperer Nutrition's FORTITUDE in cancer nutrition, Shield Healthcare's advancements, and Euro Alliance Switzerland's NANOVEDA.

How does NutriGPT navigate varying regulations across multiple countries, and what safeguards ensure that its recommendations remain compliant and safe?

NutriGPT's audited knowledge layer directly addresses regulatory compliance, which is a major obstacle to the development of nutraceuticals. The platform has a huge dataset that includes verified regulatory requirements from 13 countries. These requirements are built right into the design process for the product. This integration makes sure that formulations follow the rules of the target market from the start, which cuts down on the time and risk that usually comes with getting approval in more than one country. Essential safety measures, such as using toxicology data to predict possible interactions and bad profiles, make safety even more certain. A biochemical mindset is the platform's main idea. This means that there must be proof of how the ingredient works and what health effects it has. Finally, NutriGPT is an ISO-certified AI platform that follows a neutral, ethics-based approach. It makes recommendations based only on scientific evidence, not business interests, which leads to product development that is safer and more responsible by nature.

How does NutriGPT validate traditional formulations through contemporary scientific methodology without losing the essence of ancient wisdom?

NutriGPT achieves a unique integration by connecting traditional knowledge systems from India and other ancient cultures with modern biochemistry. It confirms traditional formulations not by dismissing the wisdom, but by substantiating its effectiveness and safety through contemporary scientific methodologies. This validation involves applying the same rigorous analysis to traditional ingredients or combinations as is used for modern compounds.  Specifically, the platform searches for the underlying biochemical mechanism of action, verifies existing clinical evidence, and forecasts potential toxicity profiles. In doing so, NutriGPT preserves the essence of ancient wisdom by providing the definitive scientific proof—the pathway-based evidence—that explains why the traditional formulation works, thereby legitimising its use in the modern, science-based nutraceutical industry.

What does the ISO certification entail for users, and how does it influence trust, adoption, and regulatory confidence?

NutriGPT is India's first ISO-certified AI platform for responsible nutraceutical innovation. This means that it follows internationally recognised standards for how it works and is managed. This certification means that the platform's intelligence is based on ethics and evidence, not commercial bias. This gives users peace of mind that the platform is a responsible place to innovate and that the processes are honest. This formal, third-party approval makes Small and Medium-Sized Businesses (SMBs) and other companies that use the platform for compliant, science-based product design much more likely to trust and use it. The ISO standard gives regulators and healthcare systems confidence that the platform follows high-quality, auditable processes. When combined with its focus on biochemical mechanisms and predicting toxicity, this helps raise industry standards. This ultimately makes regulators more confident in products made with the platform, which is part of the overall move toward safer, more reliable nutraceuticals.

With the addition of NutrifyGenie and the upcoming DealSphere ecosystem, how do you envision the future of AI-driven nutraceutical commercialisation? Will AI eventually reshape the entire value chain?

The combination of NutriGPT, NutrifyGenie, and the upcoming DealSphere ecosystem clearly envisions a future where AI reshapes the entire nutraceutical value chain. NutriGPT initiates the process by serving as the science-based co-pilot for validated formulation. This is then integrated with NutrifyGenie, described as the world's first idea-to-commercialisation AI engine, which will guide the full development journey. Finally, the DealSphere offering is designed to create a streamlined, data-driven ecosystem that can enable the entire idea-to-market process in an astonishingly short timeframe, estimated to be as little as 30–45 days. This new way of doing things will replace the old, slow, and network-dependent model at every stage. AI will take over idea generation and research and development by providing proven science. It will also manage the supply chain by smartly matching audited suppliers and contract manufacturers to opportunities. Finally, it will speed up commercialization and market launch by a huge amount. The main goal is to make AI-driven, science-based, and ethical innovation the norm in the future. This will change the industry from a slow, broken process into a fast, digitally optimised value chain.