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The primary election was held on 2 June, and roughly 80% of ballots have been counted. California's lengthy vote-counting process, particularly for mail-in ballots, allowed Raman to erase an early eight-point deficit and move ahead of Pratt by more than 3,000 votes. View More
It is a consumer-first initiative that will help reduce confusion and strengthen trust across the edible oil value chain, says SEA President Sanjeev Asthana View More
The project is a massive urban renewal initiative aimed at transforming the slum colony in central Mumbai into a modern, integrated township View More
Engineering firm DDEL secured a significant Rs 386.83 crore contract from Bharat Petroleum Corporation Ltd. This order is set to be executed until February 2028, providing long-term revenue visibility. DDEL's order book now exceeds Rs 2,400 crore, positioning the company for sustained growth. The company is expanding its participation in high-value opportunities both domestically and internationally. View More
New Delhi: Engineering firm DDEL on Monday said it has bagged a Rs 386.83 crore contract from state-owned Bharat Petroleum Corporation Ltd (BPCL). The order, one of the largest domestic mandates secured by the company in recent quarters, is expected to be executed through February 2028 and provides long-term revenue visibility . Read more: Adani Ports bags 10-year contract for Argentina’s first LNG export project DEE Development Engineers Ltd (DDEL) recorded order inflows of Rs 631.91 crore during May, including amendments/currency fluctuations, while execution during the month stood at Rs 107.83 crore, a company statement said. With this, DEE's cumulative order inflow for 2026-27 reached Rs 681.85 crore as of May 31, 2026, providing strong execution visibility across its domestic operations and international subsidiaries. Live Events The order book growth was led by significant additions in both the power and oil and gas segments, which continue to be the company's core business verticals. "Our recent order wins, including the BPCL mandate and other strategic projects secured over the past few months, have strengthened our execution pipeline considerably. Read more: Hindustan Construction Company secures Rs 127 crore Bhutan hydropower project contract "Supported by a healthy order book of over Rs 2,400 crore, we remain well-positioned to deliver sustained growth while continuing to expand our participation in high-value opportunities across domestic and international markets ," K L Bansal, Chairman and Managing Director, DEE Development Engineers Ltd, said. .Pbanner{display:flex;justify-content:space-between;align-items:center;background-color:#ec1c40;margin-top:20px;padding:5px 10px;border-radius:4px;color:#fff;line-height:10px;} .Pbannertext{display:flex;align-items:center;font-size:16px;font-weight:600;font-family:'Montserrat';} .Pbannertext img{height:20px;margin:0 6px} .Pbannerbutton a{display:flex;align-items:center;background-color:#fff;color:#ec1c40;text-decoration:none;font-weight:600;padding:4px 8px;border-radius:6px;font-size:15px;font-family:'Montserrat';} .Pbannerbutton img{height:20px;margin-right:6px} .Pbannerbutton a:hover{background-color:#f7f7f7} Add as a Reliable and Trusted News Source Add Now! (You can now subscribe to our Economic Times WhatsApp channel) (You can now subscribe to our Economic Times WhatsApp channel)
Farm-level traceability, quality, value addition, and branding are key to converting export scale into global trust, according to experts. View More
India, the land of spices, is now facing the looming threat of losing its crown as the global leader in the spices trade. Although the country continues to dominate the global spice trade with exports of around Rs 40,000 crore annually, repeated shipment rejections and tightening international food safety standards have exposed a critical weakness in the value chain, experts say. A significant part of the problem, they say, originates at Indian farms, where indiscriminate pesticide use, the continued use of banned chemicals, limited adoption of integrated pest management (IPM), and poor awareness of sustainable alternatives are undermining the quality and export competitiveness of Indian spices. The fragmented structure of farms in the country makes this even worse. Spices are grown across vast, varied regions mostly by small and marginal farmers who lack modern tech, expert guidance, and affordable digital solutions. As global food safety rules tighten, experts say India needs a dedicated policy to deliver traceable, residue-safe, sustainable spices. Madhya Pradesh, Gujarat, Rajasthan, Andhra Pradesh, and Telangana are the major producers of spices in India. Source: Spices Board of India U. Karthik, Director of Asian Spices & Co. and Co-Chairman of the Federation of Indian Spice Stakeholders (FISS), believes that India needs a multidisciplinary committee, comprising scientists, industry representatives, farmer groups, and policymakers to periodically update cultivation protocols and develop scientifically validated packages of practices (POP) that can deliver pesticide-free, high-yielding, and fully traceable spice production. “Even within the recommended packages of practices of agricultural institutions, such as ICAR, chemical pesticides continue to be prescribed for crops like cumin,” he says. Karthik further highlights that export compliance challenges today extend beyond pesticide residues. “Importing markets, such as the UK and the European Union (EU), have introduced additional regulatory requirements. In cumin, for instance, testing for Pyrrolizidine Alkaloids (PAs) has become mandatory over the past two years, with a maximum allowable limit of 400 parts per billion (ppb),” says Karthik. Notably, India exports more than 225 spices and value-added spice products to nearly 200 countries, according to the Spices Board of India. India is the world’s largest consumer of spices. China, US, and Bangladesh are among the leading export destinations. Live Events In recent years, Indian spices have come under heightened scrutiny in key export markets, particularly in the US and the EU, following a series of shipment rejections linked to excessive pesticide residues, including ethylene oxide, microbial contamination such as Salmonella , and the presence of unapproved food additives. Global food safety regulators have repeatedly flagged and halted consignments for failing to comply with prescribed Maximum Residue Limits (MRLs) and other import standards. Source: Spices Board of India Traceability: The missing link Experts argue that export-quality spices begin with farmer-level traceability systems capable of linking cultivation practices, pesticide applications, testing records, and final consignments back to individual farms. Aditya Sesh, Member of the Expert Committee on eNWRS, an initiative under the Ministry of Agriculture & Farmers’ Welfare, says mixing produce from different farms during aggregation creates varying quality and chemical profiles, making traceability and contamination control harder before processing and exporting. “Past testing data showed failure rates of nearly 12% in some consignments, causing not just direct losses but reputational damage to Indian agricultural exports. A single rejected container can cost Rs 25 lakh to Rs 1 crore, excluding return freight, destruction, demurrage, extra inspections, and higher compliance costs on future shipments. Mixing of produce during aggregation remains a persistent traceability challenge. With the global food safety norms tightening, India must significantly scale up monitoring, farmer education, traceability, and scientific compliance systems,” adds Sesh. India’s reputation challenge Speaking at a PHDCCI event in April, Smita Sirohi, ICAR National Professor and MS Swaminathan Chair, highlighted the scale of the challenge facing India’s spice exports. During the event, she noted that India accounted for more than 6,800 of the nearly 13,800 global rejections recorded in the spices, flavours and salts category. Since 2003, the EU alone has issued nearly 413 alerts against Indian herbs and spices. “The main issue is pesticide contamination, especially ethylene oxide. Early cases triggered broad scrutiny, with isolated rejections hurting India’s reputation across categories like sesame. Varying regional regulatory limits have further amplified buyer concerns. The root problem is at the source. Fixing it needs coordinated action by the Spices Board and industry. Policy can enable, but closing gaps in production, processing, and compliance is key. Claims of natural occurrence or transit contamination need scientific proof via research with ICAR, unsupported explanations damage credibility. This signals a wider gap with global standards. India must back its export volume leadership with equal strength in quality and trust,” says Sirohi. Domestic GI tags aren’t enough, as India lacks GI recognition in key markets like the EU, while Sri Lanka’s GI cinnamon earns a premium, says Sirohi. At home, weak awareness, inconsistent quality, and poor branding dilute GI value. India also lags on value addition, exporting mostly raw ingredients while global demand shifts to finished blends for Western cuisines. “Similarly, products like turmeric are exported in raw form instead of higher-value derivatives like curcumin. Branding and product communication are also weak. International buyers expect detailed specifications, composition, active content, and quality metrics, which Indian exporters often fail to provide adequately. Finally, long-term relationships with global buyers remain underdeveloped. While India participates in trade fairs, it lacks sustained engagement with importers and industry bodies, unlike competitors who maintain continuous institutional linkages,” says Sirohi. R.G. Agarwal, Chairman Emeritus, Dhanuka Agritech , says Indian spice rejections aren’t only about contamination. They reflect farm practices, post-harvest handling, processing controls, destination-country standards, and trade compliance. While real cases include pesticide residues, ethylene oxide, aflatoxins, and microbial issues, not every rejection means systemic contamination across Indian spices. Source: Spices Board of India “A major challenge is regulatory divergence. Codex MRLs (maximum residue limits) are intended to support food safety and facilitate international trade, and the WTO-SPS framework encourages harmonisation around international standards. However, importing countries often apply their own residue limits or zero-tolerance positions, sometimes stricter than Codex. This creates a complex compliance environment for exporters, especially when one country permits a residue level while another treats the same residue as non-compliant. This is a critical gap to be addressed by global regulators and deliberate about how they can allow multiple standards for the same activity in the same crop with the same GAP across the globe,” adds Agarwal. Agarwal proposes a spice traceability system modeled on APEDA’s GRAPENET for grapes, digitally linking farm registration, pesticide use, residue testing, and consignment traceability to plot level. A “SpiceNet” run by the Spices Board or ICAR-NRCSS with exporters would let buyers source only from farmers following approved protocols, he says. The road ahead Industry leaders agree India needs an integrated farm-to-brand strategy. The spice challenge starts at the farm, not the port. Karthik stresses that proper threshing at the farm level is critical to remove stalks, stones, and sand. Cross-contamination between IPM-grade spices and allergens like mustard must be prevented. Post-procurement, batch testing and SOP-driven cleaning and sortex are essential. This farm-to-process integration ensures quality, consistency, and traceability. He argues global trust demands consistent quality, world-class processing, and certifications like ISO 22000 and BRC. “Despite a 5,000-year legacy, Indian spices aren’t the global benchmark for quality, aroma, or medicinal value,” says Karthik. GI-tagged spices need promotion and sustained global branding to build authenticity. Like Californian almonds, India should use stories of sustainability, traceability, and farmer livelihoods. In value addition, India exports over 70% of spices as raw bulk, losing margins from blends, oleoresins, and nutraceuticals. Low R&D hinders innovation in extraction and functional foods. India also has less than 1% of the $14 billion global seasoning market, lagging China and the US, a major missed opportunity,” says Karthik. A spice manufacturer says the ‘purity to prosperity’ chain, consumers, processors, and farmers, is misaligned: consumers want premium quality, but farms treat spices as bulk commodities, and poor mandi handling creates inconsistency, leaving processors to spend more on cleaning than innovation. “Multiple checkpoints raise costs, yet consumers pay for defect removal, not better quality. The goal is a “spice route” built on trust and consistency, not volumes,” he adds. .Pbanner{display:flex;justify-content:space-between;align-items:center;background-color:#ec1c40;margin-top:20px;padding:5px 10px;border-radius:4px;color:#fff;line-height:10px;} .Pbannertext{display:flex;align-items:center;font-size:16px;font-weight:600;font-family:'Montserrat';} .Pbannertext img{height:20px;margin:0 6px} .Pbannerbutton a{display:flex;align-items:center;background-color:#fff;color:#ec1c40;text-decoration:none;font-weight:600;padding:4px 8px;border-radius:6px;font-size:15px;font-family:'Montserrat';} .Pbannerbutton img{height:20px;margin-right:6px} .Pbannerbutton a:hover{background-color:#f7f7f7} Add as a Reliable and Trusted News Source Add Now!
AION-Tech Solutions is leveraging the convergence of AI, analytics, asset intelligence, and digital logistics to build an integrated enterprise intelligence ecosystem. View More
The tech world is moving beyond mere digitization towards extensive, data-driven decision-making as businesses eagerly implement AI, analytics, and intelligent operations . In this context, AION-Tech Solutions is placing itself where enterprise intelligence, asset intelligence, and digital logistics meet, creating platforms that enable organizations to gain operational visibility, improve efficiency, and derive actionable insights. Chanakya Bellam, Whole-Time Director at AION-Tech Solutions, shares insights on the company's expansion, the development of its ROQIT and ETO Motors platforms, new prospects in AI-driven enterprise shifts, and the future direction as companies adopt connected, intelligent, and sustainable practices. Edited excerpts. The Economic Times (ET): How would you describe FY26 for AION-Tech Solutions in terms of strategic progress, business expansion and the evolution of the company’s technology platforms? Chanakya Bellam (CB): FY26 marked an important transition year for AION-Tech Solutions as we crossed Rs 100 crore in revenue from operations while strengthening our position across enterprise analytics, asset intelligence and digital logistics. We evolved into a full-stack enterprise intelligence provider by integrating software licensing, consulting, implementation and managed services, while expanding our analytics and data intelligence capabilities. ROQIT evolved from an EV-focused monitoring platform into a modular asset intelligence platform capable of supporting fleets, industrial equipment, rail assets and other connected infrastructure through real-time analytics, operational intelligence and sustainability monitoring. At the same time, ETO Motors continued its transformation into a technology-enabled logistics and mobility platform, expanding its capabilities across first-mile and last-mile connectivity, employee transportation and digital logistics management. Live Events Together, these developments have strengthened our platform ecosystem, enhanced operational intelligence capabilities and positioned AION-Tech Solutions to capitalize on the growing demand for data-driven decision-making, intelligent operations and digital transformation. ET: AION-Tech Solutions today operates across enterprise intelligence, asset intelligence and digital logistics. How do these businesses complement one another, and how does this diversified model position the company for future growth? CB: Our three business pillars—enterprise intelligence, asset intelligence and digital logistics—are closely interconnected and built around a common objective: helping organisations make better decisions through data, visibility and intelligent operations. Our enterprise intelligence business enables customers to unlock value from data through analytics, business intelligence and digital transformation solutions. Through ROQIT, these analytics capabilities are applied directly to physical assets, enabling organisations to monitor utilisation, efficiency, maintenance requirements, operational performance and sustainability metrics in real time. What makes this model particularly powerful is the synergy between these businesses. The data generated from assets and logistics operations can be analysed and transformed into actionable intelligence, creating a continuous cycle of insight, optimisation and operational improvement. This allows us to offer customers integrated solutions rather than standalone services. From a growth perspective, this diversified model gives us exposure to multiple high-growth sectors while creating opportunities for cross-selling, innovation and platform-led expansion. As enterprises increasingly adopt data-driven decision-making, connected operations and intelligent mobility solutions, we believe AION-Tech Solutions is uniquely positioned to capture value across the entire digital operations ecosystem. ET: What structural shifts are you seeing in the enterprise technology landscape, particularly around AI, data analytics, intelligent operations and digital transformation, and how is AION-Tech Solutions aligning with these trends? CB: We are witnessing a fundamental shift from traditional digital transformation towards intelligent, data-driven operations. Enterprises today are moving beyond simply digitising processes and are increasingly focused on leveraging AI, advanced analytics and real-time operational intelligence to improve decision-making, enhance efficiency and create measurable business outcomes. Another important trend is the convergence of IT and operational technologies, where organisations are seeking greater visibility across assets, operations and supply chains through connected platforms and intelligent automation. We are also seeing organisations shift from isolated technology deployments towards integrated intelligence ecosystems that connect data, assets, operations and decision-making on a single digital foundation. At the same time, there is growing demand for cloud-native architectures, data modernisation and scalable AI solutions that can deliver actionable insights across the enterprise. AION-Tech Solutions is well aligned with these shifts. Our enterprise intelligence business helps organisations build modern data foundations and unlock value through analytics and business intelligence. Through ROQIT, we are applying AI and analytics to operational data generated by connected assets, helping organisations move from reactive asset management to predictive and data-driven decision-making. Our focus is on creating an integrated ecosystem that combines data, AI and operational intelligence to help customers make faster, smarter decisions. As enterprises increasingly prioritise intelligent operations, automation and data-led growth, we believe AION-Tech Solutions is well positioned to support this transformation and capture emerging opportunities across industries. ET: Enterprise intelligence and analytics continue to be a core focus area for the company. What is driving customer demand in this segment, and how do you see enterprise decision-making evolving in the age of AI and data-driven operations? CB: Customer demand is being driven by a growing need for faster, more informed decision-making in an increasingly complex business environment. Organisations are generating vast amounts of data, but the real challenge lies in converting that data into actionable insights that improve performance, efficiency and competitiveness. As a result, enterprises are investing in modern data infrastructure, advanced analytics and AI-enabled intelligence platforms that provide greater visibility across their operations. At AION-Tech Solutions, we are seeing strong demand for solutions that help customers modernise their data ecosystems, integrate information across functions and leverage analytics to drive better business outcomes. Our integrated approach—combining technology licensing, consulting, implementation and managed services—enables organisations to unlock value across the entire data and analytics lifecycle. Looking ahead, enterprise decision-making will become increasingly real-time, predictive and AI-driven. We are also seeing enterprises move from descriptive analytics to predictive and increasingly prescriptive intelligence, where AI not only explains what happened but also recommends what should happen next. Rather than relying solely on historical reporting, organisations will use AI and advanced analytics to anticipate trends, optimise operations and respond proactively to changing business conditions. We believe the future belongs to enterprises that can seamlessly connect data, intelligence and execution, and AION-Tech Solutions is focused on helping customers build that capability through our enterprise intelligence platforms and analytics expertise. ET: ROQIT has expanded beyond EV asset monitoring into a broader asset intelligence platform serving sectors such as logistics, mining and industrial operations. What opportunities are driving this expansion, and where do you see the strongest momentum building? CB: The expansion of ROQIT is being driven by a broader industry shift towards connected operations, real-time visibility and data-driven asset management. While the platform was initially developed for EV asset intelligence, we recognised that the underlying need for monitoring, utilisation optimisation and operational insights extends across a wide range of asset-intensive industries. Today, organisations in logistics, mining, construction and industrial operations are increasingly looking for solutions that can help them track assets in real time, improve utilisation, reduce downtime and make faster operational decisions. ROQIT addresses these requirements through telemetry, tracking and intelligent analytics, enabling customers to gain deeper visibility into their operations. The platform is designed to help organisations understand not only where an asset is, but how effectively it is being utilised, what operational risks exist, how sustainability objectives are being tracked and where efficiency improvements can be achieved. Our long-term vision is to create a unified asset intelligence layer that connects operational data, sustainability metrics and AI-driven insights across multiple industries. We also see increasing demand for asset intelligence platforms that support sustainability reporting, carbon monitoring and ESG objectives alongside operational performance. We are seeing particularly strong momentum in fleet and mobility intelligence, industrial asset utilisation and digital logistics. The pilot deployments we have undertaken in mining and industrial environments have also been encouraging, highlighting the significant potential for asset intelligence solutions in resource-intensive sectors. As enterprises continue to prioritise efficiency, productivity and operational visibility, we believe the opportunity for ROQIT to evolve as a comprehensive asset intelligence platform is substantial. ET: Through ETO Motors, AION-Tech Solutions is building a technology-enabled logistics ecosystem. How do you assess the opportunities emerging from India’s logistics modernisation journey, and what role will digital platforms play in improving operational efficiency across the sector? CB: India's logistics sector is undergoing a significant transformation driven by infrastructure modernisation, growing supply chain complexity and the increasing adoption of digital technologies. As businesses seek greater efficiency, visibility and reliability across their logistics networks, we see substantial opportunities for technology-enabled solutions that can optimise the movement of people, goods and resources. Through ETO Motors, we are focused on building a digitally connected logistics and mobility ecosystem that goes beyond traditional transportation services. Our capabilities span first-mile and last-mile connectivity, employee transportation, multimodal mobility solutions and logistics management services, supported by digital platforms and operational analytics. We believe digital platforms will play a central role in the future of logistics by enabling real-time visibility, data-driven decision-making and more efficient resource utilisation. By integrating mobility intelligence, analytics and logistics management capabilities, organisations can improve operational efficiency, reduce costs and enhance service quality. The growing traction of our rail parcel platform and the addition of new customers further reinforce the opportunity for technology-led logistics solutions in India. As the sector continues to modernise, we believe digital platforms will become central to creating more connected, efficient and sustainable logistics networks. ET: As you look ahead, what are the key growth levers and potential challenges that could shape AION-Tech Solutions’s trajectory over the next 12–18 months? CB: Over the next 12–18 months, our key growth drivers will be the continued expansion of our enterprise intelligence, asset intelligence and digital logistics businesses. India's accelerating digital transformation, infrastructure modernisation and growing adoption of intelligent operations technologies continue to create significant opportunities across our core markets. We see strong opportunities arising from increasing enterprise investments in AI, data analytics, intelligent operations and digital transformation. The growing adoption of ROQIT as a scalable asset intelligence platform across logistics, mobility, industrial, infrastructure and sustainability-focused use cases Another key lever will be our platform-led approach, supported by strategic technology partnerships, innovation and the expansion of our analytics and data intelligence capabilities. We also see increasing demand for sustainability and operational intelligence Solutions as organisations seek greater visibility, efficiency and measurable outcomes. From a challenges perspective, the pace of technological change continues to be rapid, requiring constant innovation and investment. As customer expectations evolve, the ability to scale platforms, attract specialised talent and maintain execution excellence will remain critical. However, with our diversified business model, strong technology ecosystem and focus on solving real-world operational challenges, we believe AION-Tech Solutions is well positioned to capture the significant opportunities emerging across the digital economy. .Pbanner{display:flex;justify-content:space-between;align-items:center;background-color:#ec1c40;margin-top:20px;padding:5px 10px;border-radius:4px;color:#fff;line-height:10px;} .Pbannertext{display:flex;align-items:center;font-size:16px;font-weight:600;font-family:'Montserrat';} .Pbannertext img{height:20px;margin:0 6px} .Pbannerbutton a{display:flex;align-items:center;background-color:#fff;color:#ec1c40;text-decoration:none;font-weight:600;padding:4px 8px;border-radius:6px;font-size:15px;font-family:'Montserrat';} .Pbannerbutton img{height:20px;margin-right:6px} .Pbannerbutton a:hover{background-color:#f7f7f7} Add as a Reliable and Trusted News Source Add Now!
Hexagon Nutrition’s Rs 139 crore IPO saw strong retail demand on Day 2, with the retail portion subscribed 2.43 times. The grey market premium (GMP) indicates a potential 15% listing gain. The issue closes on June 9, with allotment expected on June 10 and listing on June 12. View More
The Rs 139 crore Hexagon Nutrition IPO entered its second day of bidding, with grey market sentiment moderating from earlier levels. The IPO is currently commanding a GMP of around Rs 7 per share, implying a potential listing gain of about 15% over its issue price of Rs 45, compared with nearly 26% earlier. Based on the current GMP, the stock is expected to list at approximately Rs 52 per share. Subscription momentum remained healthy on Day 1, with the issue subscribed 1.65 times the 2.16 crore shares on offer. Retail investors led the charge, bidding 2.43 times their reserved portion, while the Non-Institutional Investor (NII) category was subscribed 2.03 times. The public issue, which opened for subscription on June 5, will close on June 9, 2026. Hexagon Nutrition's IPO is entirely an Offer for Sale (OFS) of 3.09 crore shares, aiming to raise Rs 138.87 crore. Share allotment is likely to be finalised on June 10, with the company's stock expected to list on both the NSE and BSE on June 12. The IPO is priced in the range of Rs 42-Rs 45 per share, with a lot size of 333 shares. At the upper end of the price band, retail investors need to invest a minimum of Rs 14,985 to participate in the issue. Hexagon Nutrition IPO subscription status The Rs 139 crore Hexagon Nutrition IPO was subscribed 1.65 times on Day 1, as per data available on the BSE. Live Events Retail Individual Investors (RIIs) continued to drive demand, subscribing 2.43 times their reserved quota of 1.08 crore shares. The Non-Institutional Investor (NII) segment also witnessed healthy participation, with subscriptions reaching 2.03 times against the 46.26 lakh shares allocated to the category. Meanwhile, Qualified Institutional Buyers (QIBs) had not yet placed any bids for their reserved portion of 61.72 lakh shares, indicating that institutional participation is yet to pick up. About Hexagon Nutrition Incorporated in 1993, Hexagon Nutrition Ltd. is a research-focused nutrition company engaged in the development and manufacturing of a wide range of products, including micronutrient premixes, branded wellness and clinical nutrition solutions, therapeutic formulations, and ready-to-use foods. The company operates four manufacturing facilities—three in India located at Nasik (Maharashtra), Chennai (Tamil Nadu), and Thoothukudi (Tamil Nadu), along with an international unit in Tashkent, Uzbekistan. Its two SEZ-based facilities in Chennai and Thoothukudi offer logistical advantages such as port proximity and duty-free imports, strengthening export efficiency. About Hexagon Nutrition Hexagon Nutrition operates across three core business verticals: Branded wellness and clinical nutrition products (B2C) Premix formulations (B2B2C) Ready-to-Use Foods (RUFs) and Micronutrient Powders (MNPs) catering to ESG-driven nutrition and public health initiatives The company has established a robust omnichannel distribution network in India, covering retail pharmacies, hospital chains, e-commerce marketplaces, online pharmacy platforms, and its own digital brands, including Pentasure, Obesigo, Pediagold, and Nutrone. Its domestic reach is supported by more than 358 distributors, eight of which operate across multiple states. Internationally, Hexagon Nutrition has expanded its footprint through offices in South Africa, Uzbekistan, and Hong Kong. Between FY23 and FY25, the company exported its products to over 75 countries across Asia, Africa, Europe, and South America. Financial Performance Hexagon Nutrition has delivered consistent growth, with FY25 marking a notable improvement in profitability. Total income rose to Rs 331.29 crore in FY25 from Rs 304.62 crore in FY24. Profit after tax (PAT) nearly doubled to Rs 24.38 crore from Rs 12.21 crore, while EBITDA increased significantly to Rs 40.07 crore from Rs 24.88 crore during the same period. For the nine months ended December 31, 2025, the company reported total income of Rs 275.57 crore, PAT of Rs 27.03 crore, and EBITDA of Rs 37.55 crore. The IPO is being managed by Catalyst Capital Partners Private Limited and Cumulative Capital Private Limited, while KFin Technologies Limited has been appointed as the registrar to the issue. (Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of Economic Times) .Pbanner{display:flex;justify-content:space-between;align-items:center;background-color:#ec1c40;margin-top:20px;padding:5px 10px;border-radius:4px;color:#fff;line-height:10px;} .Pbannertext{display:flex;align-items:center;font-size:16px;font-weight:600;font-family:'Montserrat';} .Pbannertext img{height:20px;margin:0 6px} .Pbannerbutton a{display:flex;align-items:center;background-color:#fff;color:#ec1c40;text-decoration:none;font-weight:600;padding:4px 8px;border-radius:6px;font-size:15px;font-family:'Montserrat';} .Pbannerbutton img{height:20px;margin-right:6px} .Pbannerbutton a:hover{background-color:#f7f7f7} Add as a Reliable and Trusted News Source Add Now! (You can now subscribe to our ETMarkets WhatsApp channel) (You can now subscribe to our ETMarkets WhatsApp channel)
As India accelerates its sovereign AI ambitions, the focus is shifting from infrastructure to outcomes, how businesses can harness AI to improve productivity, efficiency, and competitiveness. View More
India's drive for sovereign AI is gaining traction with projects like the IndiaAI Mission and funding for local computing power. However, the significant potential goes past GPUs and data centers. With businesses wanting greater command over their data, models, and AI decision-making, the discussion is moving towards developing AI ecosystems for India that are localized, speak multiple languages, and are tailored to specific industries. Simultaneously, there are unanswered questions regarding whether the advantages of AI will extend to the nation's extensive network of MSMEs and manufacturers, rather than solely benefiting large corporations. During a conversation with ET Digital, Xebia's Global CEO, Anand Sahay, covers India's sovereign AI prospects, the increasing need for companies to manage their AI infrastructure, the development of AI that understands context and industry, and how smaller firms can leverage AI for better results despite limited resources. Edited excerpts. The Economic Times (ET): India is rapidly expanding sovereign AI infrastructure through the India AI Mission. Why is this moment strategically important for enterprises?Anand Sahay (AS): India’s sovereign AI push is strategically significant because it lowers one of the biggest barriers to AI adoption, which access to compute infrastructure. AI experimentation, model development, and enterprise-scale deployments require substantial compute power, and sovereign GPU initiatives can meaningfully accelerate AI adoption across industries by making that infrastructure more accessible. However, the opportunity extends far beyond infrastructure alone. India has a unique advantage in building domain-specific and multilingual AI systems that are aligned to local business realities, regional languages, and industry-specific requirements. This creates the foundation for India to evolve not just as an AI consumer market, but as one of the world’s largest applied AI economies. For enterprises, this is an opportunity to move faster on AI adoption while simultaneously building systems that are more contextual, localized, and aligned with emerging governance and regulatory expectations. Live Events ET: The conversation around sovereign AI often focuses on data localization. Is sovereignty becoming a broader enterprise issue?AS: Absolutely. Sovereignty today is no longer limited to the question of where data resides. Enterprises are increasingly evaluating whether they control the broader AI stack, including infrastructure, models, governance frameworks, and operational outcomes. Regional cloud infrastructure addressed part of the challenge around data residency, but organizations are now asking much deeper questions around ownership and control. They want to understand who controls the models, where inference happens, how enterprise knowledge is protected, and how much operational autonomy they truly possess within AI environments. This becomes especially critical for regulated sectors such as banking, financial services, healthcare, telecom, and public sector environments, where governance, risk management, and data sensitivity are central to enterprise operations. The broader industry conversation is now shifting from “Where is the data stored?” to “Who controls the intelligence layer?” ET: How does India’s sovereign AI push create opportunities for multilingual and domain-specific AI systems?AS: India’s diversity itself creates the opportunity. Enterprise AI systems in India cannot rely solely on generalized English-language models if they want meaningful adoption across industries, regions, and user groups. There is growing demand for AI systems trained on regional languages, industry-specific workflows, enterprise knowledge, and localized operating environments. This is where sovereign compute becomes strategically important. It enables organizations to fine-tune or build models that are aligned to Indian business realities and domain-specific operational requirements. As enterprises increasingly move toward agentic AI systems, contextual intelligence becomes even more critical. AI systems must understand enterprise processes, regulatory frameworks, operational nuances, and industry-specific workflows — not just generic internet-scale information. The ability to build localized and contextual AI systems will become a major differentiator for enterprises operating in India’s diverse business environment. ET: What should enterprises prioritise as they prepare for sovereign AI adoption?AS: The first priority should be clarity around business outcomes. Organizations need to begin by identifying which workloads genuinely require sovereign deployment, which workloads can continue leveraging public cloud AI services, and where governance or regulatory requirements demand tighter operational control. The second priority is data readiness. Many enterprises possess large volumes of data, but not necessarily structured, trusted, or usable knowledge that AI systems can effectively leverage. As AI systems become more autonomous and context-aware, the quality and governance of enterprise data become foundational to success. Finally, organizations need flexible and modular architectures. AI innovation cycles are evolving rapidly, and enterprises should avoid overly rigid infrastructure strategies. Instead, they should focus on building adaptable environments that can evolve alongside changing technologies, models, and business requirements. The conversation should not begin with infrastructure procurement alone. It should begin with workload strategy, governance clarity, and business value realization. ET: Xebia recently expanded its AI engineering presence in Hyderabad. How does that connect to India’s sovereign AI opportunity?AS: The Hyderabad expansion reflects the growing enterprise demand for AI-native engineering capabilities and scalable AI transformation expertise. As organizations move from experimentation toward enterprise-wide AI adoption, they require stronger capabilities around AI engineering, cloud-native architectures, governance frameworks, and domain-specific AI implementation. India is entering a phase where enterprises are not just consuming AI tools but actively building AI-enabled operating models. That shift requires deep engineering expertise, modernization capabilities, and the ability to operationalize AI at scale across enterprise environments. The expansion strengthens Xebia’s ability to support enterprises as they navigate this transition toward sovereign, modular, and enterprise-scale AI systems while also helping organizations build more future-ready and context-aware AI ecosystems. ET: Much of the AI conversation is dominated by large enterprises with deep pockets and dedicated technology teams. Are small and mid-sized businesses at risk of being left behind in the AI transition, or are you seeing a different reality on the ground?AS: We see a very different reality emerging on the ground. Large enterprises may dominate the AI narrative because they have the scale, budgets, and visibility to invest aggressively, but small and mid-sized businesses are often far more pragmatic and outcome-oriented in their adoption approach. They are not approaching AI as a large transformation exercise or a technology showcase. Instead, they are evaluating it through a much sharper operational lens -how to improve productivity, reduce downtime, optimise costs, and become more competitive in a rapidly evolving market. What is important is that AI is no longer confined to organizations with massive infrastructure or dedicated research teams. The ecosystem has matured significantly over the last few years. Cloud-native AI platforms, modular architectures, smaller domain-specific models, and managed AI services have made adoption far more accessible and commercially viable for mid-sized organizations. Businesses today can start with focused use cases, prove measurable outcomes, and scale gradually without making disproportionate upfront investments. In many ways, the real divide is not between large enterprises and SMBs. The real divide is between organizations that are building AI-ready operating models and trusted data foundations versus those that are still treating AI as an isolated experimental layer on top of fragmented systems. SMBs that move with focus, operational clarity, and agility can often adopt AI faster and more effectively than larger organizations constrained by legacy complexity. ET: How do the AI needs of a 100-person manufacturing company differ from those of a large multinational enterprise? Are SMBs looking for fundamentally different outcomes from AI, or simply more accessible ways to achieve them?AS: The desired outcomes are often similar, but the operational realities are fundamentally different. A large multinational typically approaches AI from the perspective of scale, governance, global integration, and enterprise-wide transformation. Their focus is on building standardized AI ecosystems that can operate across multiple geographies, business units, and compliance environments. A 100-person manufacturing company, however, operates much closer to day-to-day business outcomes. Their priorities are immediate, operational, and ROI-driven, like reducing machine downtime, improving quality control, optimizing inventory planning, lowering energy consumption, and enabling faster decision-making on the shop floor. They are not looking for overly sophisticated AI stacks or large transformation programs. They are looking for accessible, modular, and measurable solutions that can integrate quickly into existing operational environments. This is where the AI conversation needs to evolve. Smaller manufacturers often do not require massive foundational models or highly centralized AI systems. In many scenarios, specialized AI deployments trained around specific workflows or machine environments deliver far greater business value. For example, a lightweight domain-trained model running closer to the edge can enable real-time operational intelligence without requiring large-scale infrastructure investments. The future of manufacturing AI will not be defined purely by scale. It will be defined by precision, contextual intelligence, adaptability, and the ability to embed AI directly into operational ecosystems where decisions need to happen in real time. ET: Many AI solutions appear to be designed for organizations with vast data resources and complex IT infrastructure. What are the biggest barriers preventing smaller businesses from moving beyond experimentation and adopting AI at scale?AS: One of the biggest misconceptions in the market today is that AI adoption is primarily a technology challenge. In reality, the larger challenge is organisational readiness. Many businesses already possess significant amounts of data, but very little of it is contextualised, structured, governed, or maintained in a way that AI systems can effectively utilise. As enterprises move from traditional analytics toward more autonomous and agentic AI systems, the quality of enterprise data becomes foundational. AI is only as effective as the operational context it can access. If organizations have fragmented systems, siloed workflows, inconsistent documentation, or weak governance structures, scaling AI becomes extremely difficult regardless of how advanced the models are. The second barrier is economic clarity. SMBs operate with far tighter investment discipline than large enterprises. They need a clear line of sight between AI investments and measurable business value. If organizations cannot directly connect AI deployments to productivity gains, operational efficiency, cost optimization, or revenue growth, adoption naturally slows down. There is also a significant capability gap in the broader ecosystem. Many AI solutions are still designed assuming the presence of mature engineering teams, sophisticated cloud environments, and advanced infrastructure capabilities. That is not the operating reality for most mid-sized businesses. The industry needs to move toward more modular, domain-aware, and implementation-friendly AI ecosystems that simplify adoption instead of increasing complexity. ET: India's manufacturing sector is increasingly embracing digital transformation. Which AI use cases are delivering the most immediate and measurable value for small and medium manufacturers — productivity, quality control, supply chain management, predictive maintenance, or something else?AS: For small and medium manufacturers, the AI use cases delivering the most immediate and measurable value are the ones directly connected to operational efficiency and production continuity. Predictive maintenance is one of the strongest examples because the business impact is immediate, measurable, and financially visible. When AI systems can identify anomalies in machine behavior before failures occur, organizations can significantly reduce downtime, improve asset utilization, optimize maintenance cycles, and avoid costly production disruptions. For manufacturers operating on tight margins, that operational continuity creates direct business value. Quality control is another high-impact area where AI adoption is accelerating rapidly. Computer vision systems and edge-based intelligence are helping manufacturers detect defects in real time, reduce wastage, improve consistency, and enhance production accuracy across assembly lines. Traditionally, many of these processes relied heavily on manual inspection, which limited scalability and precision. AI is fundamentally changing that equation by enabling faster and more intelligent quality assurance workflows. We are also seeing increasing adoption around supply chain visibility, inventory forecasting, energy optimization, and real-time operational analytics. However, one of the most important shifts happening now is the movement toward edge AI and specialized smaller language models. Manufacturers increasingly want intelligence to sit closer to machines, devices, and operational systems rather than relying entirely on centralized cloud environments. As AI becomes more embedded into industrial operations, the organizations that succeed will be the ones that can combine localized intelligence, operational agility, and real-time decision-making into their production ecosystems. ET: There is a perception that the current AI wave is being built primarily for large corporations. Do you believe the industry has done enough to democratize AI for smaller businesses, and what needs to change to make advanced AI accessible to the broader business ecosystem?AS: The industry has made meaningful progress in democratizing access to AI, but accessibility and availability are two very different things. Technology availability has improved significantly. Today, businesses have access to cloud AI platforms, open-source models, modular deployment frameworks, and increasingly affordable compute infrastructure. Government-led initiatives around sovereign compute and AI infrastructure are also accelerating access, particularly in markets like India. However, true democratization requires more than access to tools. It requires simplification. Many AI solutions are still designed around the assumption that organizations already possess mature data environments, advanced engineering capabilities, and highly evolved governance structures. That assumption excludes a very large part of the business ecosystem. The future of AI adoption will depend on how effectively the industry can reduce complexity for businesses that are still early in their digital maturity journey. Organizations need AI systems that are modular, easier to deploy, domain-specific, and aligned to measurable business outcomes rather than large transformation narratives. Equally important is the question of data readiness. Many organizations today have enormous volumes of data, but not necessarily the right data architecture or contextual intelligence required for AI-driven decision-making. Businesses that focus first on building trusted data foundations, operational governance, and adaptable architectures will be far better positioned to scale AI successfully over the next decade. Ultimately, AI will not become mainstream because the models become larger. It will become mainstream when the ecosystem becomes simpler, more outcome-oriented, and accessible to businesses of every size. .Pbanner{display:flex;justify-content:space-between;align-items:center;background-color:#ec1c40;margin-top:20px;padding:5px 10px;border-radius:4px;color:#fff;line-height:10px;} .Pbannertext{display:flex;align-items:center;font-size:16px;font-weight:600;font-family:'Montserrat';} .Pbannertext img{height:20px;margin:0 6px} .Pbannerbutton a{display:flex;align-items:center;background-color:#fff;color:#ec1c40;text-decoration:none;font-weight:600;padding:4px 8px;border-radius:6px;font-size:15px;font-family:'Montserrat';} .Pbannerbutton img{height:20px;margin-right:6px} .Pbannerbutton a:hover{background-color:#f7f7f7} Add as a Reliable and Trusted News Source Add Now!