Category: Resources

  • India’s Deep Tech Revolution: Paving the Way for Tomorrow’s Innovations

    India’s Deep Tech Revolution: Paving the Way for Tomorrow’s Innovations


    India’s Deeptech Ambitions: A Shift Toward Innovation

    India is making significant strides in developing its indigenous capabilities in deeptech, intellectual property, and product innovation, moving beyond its established role as a global technology services hub. This transformation is highlighted by a dynamic startup ecosystem, a wealth of engineering talent, and a consistent commitment to strategic policy initiatives.

    Despite these advancements, the transition of innovations in areas such as autonomous vehicles, drones, artificial intelligence, defence technologies, energy security, space, quantum technology, and security systems from laboratory settings to market leadership poses considerable challenges. By learning from the experiences of pioneers like the US and China, the Government of India (GOI) must urgently establish strong foundations to fulfil its deeptech ambitions.

    Government as Grant Provider and Key Customer

    The Government of India’s commitment to deeptech is robust at a rhetorical level but still lacks the necessary practical implementation and scaling efforts. Supporters of the GOI might note the considerable shift in focus towards fostering homegrown deeptech capabilities; however, the actual mechanisms needed for tangible assistance remain mired in bureaucratic obstacles.

    There’s no need to reinvent the wheel when it comes to this model; India can adopt successful strategies from other economies valued at over $5 trillion to operate at the required pace.

    The technological dominance of the US has been established over decades and continues to attract top talent due to vigorous bipartisan support for investment in maintaining this edge. Multiple US agencies, including DARPA, BARDA, NSF, NASA, and the Department of Defence, have collectively funneled trillions of dollars into national R&D across universities, corporations, and startups. These agencies also commit substantial procurement budgets to support commercial viability.

    An often-cited example of this approach is how Oracle’s first client for its relational database in the 1970s was the CIA. More recently, Anduril, a defence technology startup, secured several contracts from the US Department of Defence, which included $22 billion for augmented reality defence systems and $249 million for advanced air defence, allowing the company to achieve global relevance almost instantly.

    Investing in innovation driven by domestic talent and private businesses, rather than solely relying on public sector units (PSUs), is an established blueprint that should be at the heart of India’s strategy.

    China has effectively built its competitive edge against the US in three decades using state-sponsored intellectual property and process onshoring in various sectors, including luxury goods, electric vehicles, smartphones, and high-speed trains. Documented strategies illustrate a comprehensive approach addressing every significant sector of the global economy, particularly focusing on talent and technologies vital for national security and competitive advantage.

    Estimates from the FBI suggest that China’s appropriation of American intellectual property costs the US economy between $225 billion and $600 billion annually. A Wall Street Journal study highlighted that Huawei received approximately $46 billion in state-backed loans and around $25 billion in tax incentives from 2008 to 2018, illustrating significant support from the state across multiple sectors.

    While China’s methods may violate World Intellectual Property Organization (WIPO) standards and global market norms, its status as a global player in various tech sectors is unquestionable.

    Conversely, the GOI has focused on a PSU-led approach since independence, which has not fostered an indigenous innovation framework at the scale necessary for a $4 trillion GDP. In recent years, the current administration has taken notable steps towards revitalising this ecosystem, as seen in the success of the targeted military operation in 2025.

    Nonetheless, budget allocations and the necessary follow-up actions are inadequate to meet future demands. India’s recent commitment of INR 20,000 crore (approximately $2.4 billion) to deeptech is a positive start but remains insubstantial compared to the scale and predictability of investments from the US and China. One contract awarded to Anduril alone exceeds India’s entire annual defence R&D budget.

    The government’s role as a grant provider, primary customer, and facilitator of procurement for transformative local technology needs strengthening. Initiatives such as iDEX and the IndiaAI Mission are steps in the right direction; however, implementation has not kept pace with the ambitious vision of India’s leadership and the aspirations of its citizens. Securing a pilot project does not guarantee larger-scale outcomes, and many initiatives rely on limited grants or uncertain integration opportunities.

    Without significant and direct government investment, India’s deeptech ecosystem will struggle to achieve the financial stability required for global competition. The private sector cannot afford to make long-term investments in technologies that lack established commercial markets. The government must take the lead as the primary driver of grants and as an anchor client, ensuring that domestic deeptech firms can thrive in a secure environment conducive to innovation.

    What the GOI Needs to Implement

    • Substantially increase both the magnitude and continuity of grants and procurement commitments.
    • Significantly improve grant administration by implementing a merit-based process to attract experienced minds from private enterprises.
    • Simplify pilot-to-procurement pathways with transparent, time-sensitive frameworks and established teams incentivised to achieve results.
    • Create military and civilian test environments in cooperation with the industry and universities, allowing startups and local innovators to test before full deployment.
    • Encourage risk-taking among citizens and private enterprises while reducing dependence on PSUs and civil servant-driven planning.

    Long-term Policy and Investor Clarity

    Deeptech necessitates patient, long-term investment, which only local sources can provide if there is stability in regulations and policies. While the Indian venture capital landscape and family-operated office structures have matured, they predominantly adhere to traditional funding cycles, expecting returns within a decade.

    For these investors to substantially support deeptech initiatives, the investment environment must evolve. They require certainty regarding where to invest and whether the necessary policy frameworks will support and scale those companies over the long term.

    In contrast, deeptech investors in the US and China function within sophisticated, predictable ecosystems, bolstered by governments that have laid out decades-long industrial policies complemented by clear regulations, tax benefits, safe harbour provisions, and guarantees for market creation.

    The CHIPS and Science Act in the US, for instance, allocates $280 billion for federal investment in sectors like semiconductors, AI, and quantum technology, paired with comprehensive plans for implementation over five years. Meanwhile, in China, state-supported guidance funds, such as the $47.5 billion big fund or the National Integrated Circuit Industry Investment Fund, amalgamate equity investments with subsidised loans, tax exemptions, and government contracts, giving investors long-term visibility for revenue growth and scaling potential.

    The GOI must rebuild trust in its policies and processes, taking proactive steps to foster this confidence. Indian investors contend with a landscape marked by ambiguous regulations, unpredictable IP rules affecting dual-use technologies, and uncertain procurement flows. This situation creates a shortage of “15-year thesis” capital essential for establishing deeptech giants.



    India’s Deeptech Innovation: Foundation Setting For The Future


    India’s Deeptech Innovation: Foundation Setting For The Future

    India’s deeptech innovation landscape faces significant challenges due to follow-through delays, such as the National Deep Tech Startup Policy announced in 2023 but still not operational. These delays deepen the concern among Indian long-term capital providers that policies in India often fail to be executed within the timely frameworks innovation cycles require. If the Government of India (GOI) is genuinely aiming to collaborate with private businesses and local capital, it must acknowledge these issues and work on building the necessary bridges.

    What The GOI Must Do

    Safe Harbour Provisions For Stability

    The government needs to provide comprehensive, long-term regulatory and incentive roadmaps across various industries. Protecting against retroactive policies, changes in taxation, and regulatory shifts will help mitigate baseline risks. For instance, establishing the Production-Linked Incentive (PLI) guidelines as a 10-year policy with non-cancellation protections would be highly beneficial for boosting significant capital expenditure investments in the country’s enterprises.

    Incentive Frameworks

    The introduction of tax incentives, co-investment funds, and R&D grants that reward long-term investments in deeptech sectors, energy security, and National Mission aligned companies is essential. Such frameworks should resemble the US’s Qualified Small Business Stock (QSBS) exemption.

    Transparency

    To instil confidence in investors, the government should publish a 15-year roadmap addressing deeptech, energy, food security, manufacturing, and other key areas. This should include sector-specific frameworks for export, dual-use, and intellectual property support.

    Building Integrated Ecosystems: The Role Of PSUs, Universities And Industry

    No nation excels in deeptech without an effective innovation ecosystem. Examples from Israel’s Iron Dome, America’s defence industrial base, and the Make in China 2025 strategy highlight the impact of collaboration among universities, industry, and government. India requires its own version of a military industrial complex that does not rely solely on Public Sector Undertakings (PSUs) and governmental employees.

    Historically, Indian PSUs have engaged in closed-loop development cycles over decades, often plagued by issues like corruption and inefficiency. A shift towards reimagining PSUs as incubators for home-grown innovation could transform this scenario.

    PSUs and organisations like ISRO, DRDO, HAL, and BEL have the potential to play a key role in partnering with startups and private enterprises for co-development and systems integration. Universities, especially institutions like IITs and IISc, can facilitate the transition from lab-based research to market-ready products through effective incubators and technology transfer offices.

    Successful models already exist, such as Israel’s collaboration between startups and intelligence testbeds for cybersecurity, or university-industry partnerships in the US involving Stanford and Silicon Valley. Indian universities sit on a wealth of research and possess much of the country’s best talent, yet their innovations seldom make it to market and the most gifted individuals often pursue opportunities abroad.

    Major Gaps

    Systems Integration

    Many Indian startups continue to develop standalone solutions. Effective operational deployment necessitates integration with existing defence and civilian systems, which calls for joint testbeds and standardised protocols.

    Testing Infrastructure

    Access to live-fire ranges, operational networks, and realistic testing environments is limited for most startups. This leads to late-stage identification of flaws, driving up costs and diminishing confidence among founders and investors.

    Talent And Trust

    While India’s founders and innovators possess significant technical skills, they often lack experience in operational defence or real-world deployment. Conversely, PSU and agency stakeholders tend to regard startups as outsiders, hindering effective collaboration.

    Constraints On Universities

    India’s top academics face heavy regulation, causing grant processes to move exceedingly slowly. The budget for 2025-26 announced support for research fellowships in AI, yet this initiative arrives three years after the launch of ChatGPT, highlighting a lag in response to the AI arms race.

    What GOI Must Do

    The GOI should deepen partnerships with PSUs and universities for joint product development, integration labs, and live testbeds. Establishing exchanges among founders, veterans, and PSU scientists will bring operational credibility to startups. Additionally, integrating private sector leaders into advisory roles within PSUs is crucial.

    An architecture akin to the National Payments Corporation of India (NPCI) is necessary for each deeptech and innovation vertical, spanning nuclear energy, space technology, materials engineering, and AI.

    Supporting modular “dual-use” architectures will allow innovations to cater to both sovereign and civilian markets. Clear specifications regarding sovereign use are needed to channel numerous projects towards universities and corporations for prompt development.

    The leadership of GOI grants should be driven by experts from private enterprises, similar to initiatives like Aadhar and UPI, to accelerate research on university campuses nationwide.

    The path is clear for the GOI: Integrate deeptech into national policy architecture or risk enduring technological dependency—a situation India has faced for the past 200 years.

    To compete effectively in the global innovation arena, India must transition from reactive measures to a proactive, risk-positive approach that embeds deeptech innovation within the very core of state capacity and national strategy. Historically, India’s strengths have included its talent, ambition, and resilience. To convert these into national and global competitiveness in deeptech, the government must urgently establish robust and flexible foundations.

    The post India’s Deeptech Innovation: Foundation Setting For The Future appeared first on StartupSuperb Media.



  • Unlocking Smarter Spend Control: The Surge of AI-Driven SaaS in Indian Enterprises

    Unlocking Smarter Spend Control: The Surge of AI-Driven SaaS in Indian Enterprises


    AI-Powered SaaS Revolutionises Financial Operations

    AI-Powered SaaS platforms ensure seamless scalability and effective integration with existing enterprise systems, including ERPs, HRMS, and banking platforms. The global SaaS market, projected to exceed $317 Bn in 2024, highlights the ongoing digital transformation across various sectors.

    Research shows that AI adoption in finance surged from 45% in 2022 to an anticipated 85% by 2025. This shift is analogous to the question surrounding the intrigue of AI: there is immense admiration for its capabilities alongside widespread confidence in its potential. This digital transformation wave has not only altered how Indian enterprises function in financial operations but has also fostered technological resilience.

    CFO’s New Focus: Beyond Cost Control

    Concerns are rising within financial roles, including chief financial officers and accounting teams, regarding the need to optimise every rupee of non-payroll expenditure for operational agility. Leveraging AI is proving to be a straightforward decision for these teams, as demonstrated by their increasing use of AI tools.

    A study from Gartner indicates that 58% of finance functions were actively utilising AI as of 2024, signalling a significant shift in the modus operandi of financial operations. Traditional spend management approaches must evolve beyond budget compliance to encompass real-time agility, regulatory adherence, and comprehensive visibility across all expense categories. In the past, finance teams relied on outdated combinations of Excel spreadsheets, multiple ERP iterations, and antiquated financial metrics.

    A considerable amount of time was previously wasted on resolving obstacles; however, AI and streamlined workflows have introduced dynamism to complex business needs. The CFO recognises that AI-driven SaaS platforms provide unmatched granular visibility, predictive analytics, and automated anomaly detection. It is no surprise that AI is frequently referred to as a disruptor in the industry.

    Companies implementing these solutions have observed reductions in maverick spending of up to 20% through automated policy enforcement, further illustrating the measurable benefits of intelligent spend management.

    The Synergy of AI and SaaS: Breaking Free from Traditional Software

    The uptake of intelligent spend management platforms is accelerating across industries such as manufacturing, BFSI, retail, and IT services. Changes in regulations, including GST, have prompted the need for agile tools, while consumers increasingly expect immediate solutions at their fingertips.

    The collaboration between artificial intelligence and SaaS models has established a strong foundation for modern financial operations. SaaS architecture facilitates seamless scalability and connection with existing enterprise systems, including ERPs, HRMS, and banking platforms. Such integration eradicates data silos, creating a unified framework for financial management.

    A cloud-native methodology ensures quick deployment without heavy IT infrastructure costs. Furthermore, real-time dashboards enable business leaders to make informed purchasing decisions based on in-depth spend analytics. Machine learning algorithms continually assess spending habits, predict future trends, and identify anomalies with little manual input. Research suggests that AI adoption in finance will rise from 45% in 2022 to an anticipated 85% by 2025, with businesses leveraging AI-based solutions managing to reduce reimbursement turnaround times by 70%.

    Small and medium-sized enterprises (SMEs) and mid-market organisations are particularly drawn to modular SaaS offerings that deliver enterprise-level functionalities without the intricacies and expenses tied to complex ERP implementations. Such platforms empower lean finance teams to function with the accuracy and insights generally associated with larger enterprises.

    A shift from reactive to proactive spend management denotes a significant evolution in financial operational philosophies. AI-enhanced platforms allow finance teams to foresee spending patterns, recognise cost-saving opportunities, and put proactive measures in place before problems arise.

    Unified platforms, which consolidate travel management, procurement, and rewards programmes, mitigate shadow IT risks and lessen data fragmentation. Decision-makers can access an all-encompassing view of operational expenditures through a single interface, leading to better-informed strategic planning.

    The Future of AI-Driven Platforms

    Indian enterprises find themselves at a crucial turning point where traditional cost control methods must adapt to meet new business demands. With the global SaaS market expected to surpass $317 Bn in 2024, this reflects broader digital evolution across sectors.

    The incorporation of AI features into SaaS platforms signifies more than just technological progress; it represents a fundamental rethinking of financial operations. These solutions offer measurable cost reductions while enhancing governance structures, operational agility, and readiness for future challenges.

    For senior executives, embracing AI-based spending management platforms goes beyond mere digital transformation. It is essential for survival in an increasingly regulated and competitive landscape. Organisations adopting these technologies can navigate economic uncertainties with enhanced resilience and strategic awareness.

    The integration of artificial intelligence with cloud-native SaaS models presents unparalleled opportunities for Indian enterprises to transform their financial operations. As companies continue to face complex regulatory landscapes and competitive pressures, intelligent spend management platforms will become vital for sustained growth and operational excellence.

  • The Surge of Domestic Capital Transforming India’s Venture Capital Landscape

    The Surge of Domestic Capital Transforming India’s Venture Capital Landscape



    Domestic VC Investment in India: Unlocking Potential

    Domestic VC Investment in India: Unlocking Potential

    Summary

    Domestic capital is currently a small contributor in India’s venture capital ecosystem, in contrast to China’s thriving local LP-driven surge. Allocating 5–10% of investments to domestic VC can protect against fluctuations in USD and capitalise on India’s digital consumption narrative. Experienced local teams and well-sized early-stage funds are essential for generating wealth across Indian families.

    In 2024, private-market investment in India recovered to approximately $43 billion—accounting for one-fifth of all Asia-Pacific investments and ranking second only to China in the region. The deal count reached an all-time high of 1,270 VC transactions, despite a 20% decrease in average investment sizes. International investors are enthusiastic, with 87% of the world’s 30 largest funds now committed to investing in Indian rupees. However, local investors—including family offices, corporate treasuries, and insurance companies—still play a minor role. Unlike China, where local LPs fueled the growth in the 2010s, Indian investors currently contribute only a fraction of VC assets, representing both a risk and an untapped opportunity.

    Why Homegrown Money Matters

    Stability & Alignment

    Foreign investment tends to be more volatile; in contrast, Indian wealth is stable and denominated in rupees, making it ideal for founders whose exits are increasingly realised through local IPOs or block trades. In fact, public markets constituted around 59% of exit value in 2024.

    Nation-Building Upside

    Reforms such as GST, IBC, and Digital India have not only attracted foreign megafunds but also opened avenues for domestic savers to engage in wealth creation within private markets.

    A few local General Partners (GPs) are successfully raising onshore capital, exemplified by ChrysCapital’s $2.1 billion fund and Kedaara’s $1.7 billion Fund IV, both supported by Indian families and institutions. However, when compared to the over 60% increase in competing funds since 2016, local contributions remain relatively modest.

    India Is Not Silicon Valley—Experience Counts

    Effective investing in India requires not just capital, but contextual understanding. The market comprises 28 states, each with unique cash-flow dynamics and a complex regulatory environment that often rewards those with seasoned experience. This explains the rise in buyouts—where operational expertise takes precedence over rapid scaling—growing from 37% to 51% of private equity value in two years. Teams with decades of business experience in India can identify promising niches, such as Tier-II lending or emerging med-tech exporters, far ahead of traditional investment strategies.

    Taming The Power Law

    While India generates unicorns, the timeline for exits is slower: only 36% of buyouts exceeding $100 million from 2018–19 have completely exited in five years, compared to 50% for the 2012–13 group. Successful funds in this environment merge conventional power-law strategies with anchor investments—companies capable of achieving earnings growth of 20% to 30% over a decade in sectors like housing finance, healthcare outsourcing, or defence electronics. These anchor investments help stabilise returns while waiting for significant growth opportunities.

    Right Sizing Early-Stage Bets

    Seed and Series A investments are currently averaging in the low single-digit millions, indicating that the market cannot support numerous INR 4,000 crore seed funds. Investment vehicles within the INR 200-400 crore (US $25-50 million) range are sufficiently sized to lead funding rounds, maintain pro-rata positions, and return capital without depending on a single high-risk investment. Oversized funds tend to focus on larger markets and dilute returns.

    What This Means For India’s UHNIs & Family Offices

    Diversification Inside The Border

    Investing 5–10% of alternative assets in domestic VC can safeguard against USD fluctuations and leverage the digital consumption trends that have already attracted foreign investment.

    Preferred-Partner Status

    Local limited partners often gain co-investment rights and more favourable fee arrangements—benefits that international investors strive to secure.

    Impact With Returns

    Capital invested connects with businesses that generate employment, tax revenues, and strategic capabilities—delivering value beyond financial returns.

    The Call To Action

    To elevate India’s venture ecosystem, input from those who fully understand the local landscape—Indian families and institutions—is critical. Collaborating with investment teams familiar with the Indian market, which blend long-term strategies with selective high-risk investments and keep early-stage funds agile, can transform upcoming innovations into generational wealth. The opportunity is ripe, and it would be unfortunate if the primary beneficiaries of India’s technological advancement continued to be predominantly offshore.


  • The Future of Indian Startups: Embracing the Era of Invisible Agents

    The Future of Indian Startups: Embracing the Era of Invisible Agents



    AI Agents Transforming India’s Startup Landscape



    AI Agents Transforming India’s Startup Landscape

    AI Agents vs. Traditional Apps

    AI agents are built for delegation, while traditional apps focus on interaction. Unlike apps that you open and navigate, AI agents facilitate tasks quietly in the background. They are designed to talk, text, negotiate, draft, compare, and finalise deals across various channels and platforms. If apps represented digitisation, AI agents will embody orchestration, automating processes like follow-ups, extracting data from PDFs, managing customer inquiries rapidly, and voice-enabled inventory management.

    From Interaction to Delegation

    In the initial phase of India’s startup evolution, applications took centre stage—platforms like Swiggy made food accessible, Zerodha simplified stock trading, and CRED added rewards to credit card usage. A new generation of innovators tackled obvious consumer needs through mobile-first solutions. However, the upcoming trend will focus on invisible AI agents that assist users behind the scenes, significantly enhancing productivity.

    Shifting Interfaces in Technology

    Apps are centred on user interaction, requiring users to navigate through screens to achieve their goals. In contrast, AI agents focus on delegation; users simply communicate their needs, and the agents handle the rest autonomously. For example, a recent project involved developing an AI voice agent capable of managing incoming calls, qualifying leads, and scheduling appointments using natural language. This eliminates the need for apps, onboarding, or tedious learning curves, creating a seamless user experience.

    Leveraging India’s Unique Edge

    While Silicon Valley engages in high-level discussions about artificial general intelligence, Indian entrepreneurs have significant opportunities to build AI agents that address current inefficiencies at scale. Missed calls, WhatsApp groups, and handwritten records remain prevalent among local businesses. If apps represented a step towards digitisation, AI agents signify a leap towards true orchestration, automating tasks like follow-ups and inventory management.

    Real-World Applications of AI Agents

    Recently, in collaboration with Indian grocery retailers, voice-based agents were developed to take daily orders and answer queries, providing real-time updates without the need for a user interface or software downloads. This straightforward approach has proven highly effective.

    Adapting to User Tolerance Levels

    Indian users display a remarkable tolerance for minor inefficiencies, such as slight delays or errors, as long as the end result is beneficial. This adaptability makes India an ideal environment for testing the next generation of agent-based software solutions.

    Innovative Startups in a New Wave

    The new startups emerging in this domain will not mirror the traditional SaaS or direct-to-consumer models. They are likely to be experimental, messy, and intricately woven into industry workflows. Founders will focus on rapid development and constant iteration, evolving their agents according to user feedback.

    A Shift in Founders’ Profiles

    The profile of the next wave of founders may diverge from the conventional path. The future unicorn founder might not necessarily be an IIT graduate with significant seed funding but could very well be a solo entrepreneur from Bhubaneswar creating a logistics assistant that processes numerous daily calls using integrated AI technologies.

    Global Opportunities for Indian Innovators

    As international founders aim for billion-dollar valuations, Indian innovators have a unique chance to become essential contributors in the development of global AI agents. Indian teams are already constructing systems for professionals in the US, such as therapists and real estate agents, producing invisible assistants that enhance efficiency behind the scenes.

    The Future of Startup Development

    Emerging startups will not question, “What app should I create?” Instead, they will focus on, “What human tasks can we automate completely?” They will analyse existing processes, such as how a store manager coordinates deliveries and how an accountant files taxes, and create AI agents that can perform those tasks autonomously rather than merely assisting.

    A New Era of Embedding Technologies

    The future landscape will not celebrate ostentatious launches. Instead, it will thrive on quiet integration, effective demos, and satisfied users. This represents a transition to a new technological stack focused on invisible agents and their visible impacts.


  • Can Indian Startups Flourish in the Absence of Incentives for LLM Development?

    Can Indian Startups Flourish in the Absence of Incentives for LLM Development?



    Government Support for Indian LLM Development


    Government Support for Indian LLM Development

    Government support is vital for infrastructure such as GPU resources necessary for creating sovereign LLMs that deliver affordable AI solutions for the broader public. India boasts a robust emerging AI research ecosystem across both academia and industry, holding the third position globally in producing high-quality AI publications.

    Support must encompass more than hardware; it should also involve well-curated local datasets, comprehensive AI governance frameworks, and a skilled workforce proficient in various roles from data annotation to AI leadership.

    The Importance of Indian Government Support for LLMs

    The pressing question today is how crucial government support from India is for the advancement of Indian LLMs and if local startups can effectively create LLMs without governmental backing. This contemplation extends to whether government assistance is essential for large-scale AI advancements.

    Global Context and Examples

    To understand this, it is useful to look at global examples. Major LLMs such as GPT-4o, Gemini, Llama, Claude, Mistral, and others are predominantly developed and funded by private enterprises and startups, often assisted by venture capital. Usually, substantial tech companies like Google or financially robust startups like OpenAI are behind the development and implementation of these models. For instance, OpenAI has substantial support from Microsoft, while Llama benefits from an extensive open-source ecosystem, partly funded by Meta.

    This reality substantiates the notion that resourceful LLMs can be developed even without governmental support.

    The Case for a Sovereign AI Approach

    However, if a sovereign AI is needed from a governmental perspective to provide cost-efficient LLM resources for the public, it strongly recommends that the government supports the necessary infrastructure, like GPU resources, to create such LLMs.

    A Balanced Approach to AI Development

    The writer suggests a balanced approach, where a healthy mixture of sovereign and commercial models can be cultivated. Beyond merely supplying hardware, the support required for a thriving startup ecosystem to build LLMs extends to various components, including:

    • Establishing a solid ecosystem for AI research.
    • Creating well-curated localised data repositories.
    • Implementing a strong AI governance structure to monitor and enhance models.
    • Developing a robust human resource ecosystem that nurtures talent from data labelers to AI managers and chief AI officers.

    India’s Emerging AI Research Ecosystem

    India is witnessing an evolving AI research ecosystem, supported by institutions such as IITs, IIITs, NITs, and commercial labs like Google Research India, Microsoft Research India, and IBM Research India. Despite being third globally in high-quality AI research publications, as analysed by the research agency Itihaasa, it still trails behind China significantly.

    Nonetheless, there are encouraging signs of growth in India’s AI research landscape.

    Government Contributions to Data Repositories

    The government can play a pivotal role through initiatives like AIKosh, which serves as a repository for Indian-centric datasets. This initiative has been well-received and is anticipated to greatly benefit the LLM development efforts of AI startups and other sector participants. Expanding the scope, variety, and reliability of datasets within AIKosh will immensely support Indian LLM initiatives.

    AI Governance and Skills Development

    On the governance side, the IndiaAI mission under MietY is set to introduce a framework tailored for AI governance in India, concentrating on ensuring safe and responsible AI while fostering innovation. Several MietY round tables have involved stakeholders from academia, government, and startups, aimed at shaping this framework in accordance with existing models from UNESCO and the EU AI Act.

    Regarding skills, India holds great potential to become a global leader in AI talent development. This encompasses results from extensive AI/ML degree programmes offered by engineering and management institutes, as well as certification programmes for ongoing professional education. Furthermore, targeted CXO awareness initiatives on AI/ML will enhance India’s standing as the global hub for AI skills.

    On these fronts, alongside infrastructure support, it is evident that government assistance could significantly accelerate innovations in AI and LLM technologies.

    A comprehensive support strategy across the areas of data repositories, AI governance, AI research, and workforce development, complemented by infrastructure availability, is crucial for the growth of India’s LLMs. In an age where LLMs are increasingly becoming part of daily life, tailoring these technologies to fit India-specific data and use cases is of utmost importance.


  • Unlocking India’s GenAI Potential Through Vertical SaaS Innovations

    Unlocking India’s GenAI Potential Through Vertical SaaS Innovations



    Vertical SaaS: Driving India’s $17 Bn AI Market Growth

    Vertical SaaS: Driving India’s $17 Bn AI Market Growth

    SUMMARY

    As reported by NASSCOM, India’s artificial intelligence market is anticipated to expand at a CAGR of 25-30%, reaching $17 billion by 2027. One major advantage of vertical SaaS in the Generative AI era is the speed at which it can provide ROI. Vertical SaaS platforms are more than merely software solutions; they serve as a digital infrastructure that supports compliance, workflows, and data structures.

    Generative AI and Its Role in Vertical SaaS

    Generative AI is making headlines due to its extensive capabilities, ranging from content creation to customer support. However, its true potential is realised when it is integrated into the specific workflows of various industries. This is where vertical SaaS plays a crucial role, not merely as a trend but as a transformative approach.

    According to NASSCOM, India’s AI market is poised to experience substantial growth driven primarily by B2B applications. Innovations such as smart chatbots and intricate CRM systems enabled by Generative AI are creating personalised experiences. They extract valuable insights from unstructured data and produce actionable results. This transition underscores the necessity for SaaS platforms to integrate AI while also recognising the industry’s architecture to effectively scale.

    In a complex environment like India, characterised by diverse languages, regions, cultures, and niche industry needs, vertical SaaS emerges as a significant asset.

    Horizontal SaaS vs Vertical SaaS

    Horizontal SaaS tools are designed for broad functionalities across multiple industries, whereas vertical SaaS platforms target a specific sector. Examples of horizontal SaaS include Hubspot and Notion, which cater to various industries without focusing on any particular one.

    In contrast, vertical SaaS solutions function as digital infrastructures tailored to meet the regulatory, workflow, and data requirements of specific sectors such as healthcare, manufacturing, and logistics. This deep integration enables vertical SaaS platforms to leverage Generative AI more effectively. This facilitates context-rich automation, accurate insights, and quicker decision-making that horizontal tools struggle to deliver. When Generative AI is layered onto software that comprehends industry-specific terminology and logic, its impact is significantly amplified.

    Challenges of Horizontal AI Tools

    Generic AI tools often fall short when tasked with resolving industry-specific challenges. Their performance can be inadequate for specialised functions. For instance, a horizontal AI chatbot might competently address common customer inquiries, but when faced with specialised industry concerns—such as those in the used car market—it will likely lack the ability to produce tailored responses without external intervention. It also requires a dedicated knowledge base specific to that industry to train the AI effectively, which can be a complex undertaking.

    Moreover, horizontal tools generally rely on manual configuration, dashboard setup, and significant integration efforts to create value across any industry. Conversely, vertical SaaS platforms are pre-configured for their respective sectors, offering plug-and-play tools and AI features that align seamlessly with existing workflows, simplifying onboarding and enhancing efficiency from day one.

    Vertical SaaS and Generative AI: A Perfect Partnership for India

    India’s landscape of small and medium enterprises, alongside its unique regulatory frameworks and vernacular complexities, provide a rich environment for vertical SaaS innovations. For instance, Indian startups like Minkasu, Pharmarack, and Posify are leveraging AI to automate workflows, gain insights from various interactions, and enable intelligent decision-making, thereby helping organisations operate more efficiently while maintaining compliance.

    Startups across the food and beverage, pharmaceutical, fintech, and retail sectors have tapped into the burgeoning billion-dollar B2B market, crafting solutions that address particular challenges such as CRM, dashboards, activity management, and analysing seasonal trends.

    However, sectors like energy, the used car market, and construction still operate using outdated methods such as physical registries and inconsistent communications, leading to increased operational costs and delays.

    As online platforms become the primary entry point for customers, businesses must adapt their strategies, and vertical SaaS platforms are effectively bridging this gap.

    The Future of Used Car Sales

    According to the CARS24 report, the anticipated number of used car sales is projected to reach 10.8 million by 2030, with an annual growth rate of 13%. This underscores the necessity for digital transformation, making the adoption of AI-driven, industry-specific platforms essential for simplifying operational complexities through user-friendly dashboards and understanding the behaviours of Indian consumers, resulting in a more intuitive and impactful experience.

    Fast ROI with Vertical SaaS

    One of the main advantages of vertical SaaS in the Generative AI era is the rapid return on investment. Traditional digital transformation initiatives typically take time to yield results. However, AI-enhanced vertical SaaS platforms can produce measurable benefits within weeks.

    These platforms come pre-trained with relevant data tailored for specific use cases, allowing businesses to avoid the lengthy process of building infrastructure or training datasets from the ground up. This approach removes the most significant hurdle of AI implementation—time and complexity—enabling firms to focus solely on outcomes without the burden of orchestration. This makes Generative AI adoption viable not only for large enterprises but also for medium-sized players in Tier II and Tier III cities.

    The Path Forward

    As Generative AI advances from generating content to facilitating strategic decision-making, vertical SaaS providers are in a prime position to lead the forthcoming wave of intelligent automation. Their industry expertise, paired with embedded AI capabilities, ensures that their solutions are not only intelligent but also align strategically with market demands.

    For Indian entrepreneurs, investors, and technology leaders, this represents more than a mere opportunity in technology; it signals a transformation in business models. Vertical SaaS is primed to redefine customer experiences and accelerate growth in Tier II and Tier III regions, unlocking value that horizontal solutions cannot accomplish.

    The future of SaaS is not a universal model; it is customised, vernacular-ready, and prioritises an AI-first approach. For those innovating in India, the focus should shift to developing vertical solutions, as this is where the true Generative AI revolution will unfold.


  • “Empowering India’s Middlemen: The AI Revolution”

    “Empowering India’s Middlemen: The AI Revolution”



    AI Revolutionises the Intermediary Ecosystem in India

    AI Revolutionises the Intermediary Ecosystem in India

    AI is reshaping India’s intermediary landscape by addressing challenges such as information asymmetry, operational inefficiencies, and scaling issues. This innovative technology enables intermediaries to manage real-time dialogues with numerous parties, effectively enhancing their capabilities.

    Three Is Not a Crowd, It’s a Party in India’s Economy

    Searching for a home in India usually involves multiple parties. Booking a flight? That involves another set of intermediaries. Even acquiring a SIM card frequently requires the input of an additional person apart from the buyer and the seller.

    Intermediaries play a crucial role in India’s economic framework not because of inefficiencies or a lack of technological solutions, but due to a low-trust ecosystem where personal relationships are paramount. When an Indian consumer is making a major purchase, they often consult someone recommended to them whom they trust, rather than going directly to a platform or company. Many Indian startups have struggled with this reality, often burning substantial resources to offer significant discounts in an effort to bypass these intermediaries, leading to unsustainable business models due to a misunderstanding of India’s commercial fabric.

    AI Creates Unique Opportunities for Intermediaries

    Rather than displacing intermediaries, AI can enhance their functions—closing information gaps, amplifying capabilities, and supporting scalability, all while retaining the valued human relationships in India.

    Expert-Level Insights Without Years of Training

    A startup integrating AI into commercial fitouts captures countless data points from construction projects. Their system effectively calculates material requirements, detects productivity variations between shifts, and optimises labour allocation with exceptional accuracy that surpasses human management capabilities.

    This reflects the metamorphosis of intermediaries through AI-enhanced expertise. A contractor utilising this platform can make informed decisions as if they possess decades of industry experience, all without enduring years in the field. AI empowers a new breed of highly capable intermediaries within India’s construction sector, enabling a wider distribution of knowledge that was once limited to a select few.

    Automating Complex Multi-Party Interactions

    Another enterprise serves as an AI shopping assistant via WhatsApp, allowing consumers to simply request what they desire. Behind this seamless interaction, the AI simultaneously conducts multiple conversations with local vendors, comparing prices, checking on availability, and negotiating terms that would otherwise overwhelm a human aide.

    This scenario illustrates how AI empowers intermediaries by undertaking tasks that were previously unfeasible—navigating simultaneous, real-time communications with various parties. Unlike Western models that seek to eliminate human involvement, this startup enriches the intermediary approach by coordinating complex multi-party interactions while keeping the final judgement in the hands of a trusted advisor, aligning with India’s preference for relationship-based transactions while alleviating communication bottlenecks.

    From Service Provider to Strategic Advisor

    A local insurance agent in tier-II cities, who traditionally managed 50-100 client accounts, can now effectively cater to over 500 clients with the assistance of AI. AI tools can automatically carry out policy evaluations and routine inquiries while identifying significant life events in client data—such as a child nearing college age or a property acquisition—that indicate possible changes in coverage needs.

    This exemplifies how AI elevates intermediaries to roles with greater value. What was once a reactive, transaction-based system transforms into a proactive, insight-driven operation.

    The Importance of Scalability in the Indian Context

    This scalability is crucial given that vast populations in India remain underserved in key sectors like healthcare, education, and financial services. AI allows trusted intermediaries to broaden their reach more effectively than direct digital models, bridging service gaps while upholding the relationship-driven focus that consumers in India prioritise.

    A Distinctly Indian Approach to AI Adoption

    A distinctive approach emerges that resonates with India’s economic context. While Western economies frequently see AI as a substitute for human roles, India’s potential lies in adopting it as a collaborative tool that enhances human capabilities.

    Intermediaries can become more empowered rather than redundant—equipped with data-driven insights, relieved of administrative tasks, and capable of amplifying their influence. This effectively addresses the trust deficit that complicates digital transactions in India while preserving the personalised interactions that consumers value. The future does not belong to those who can replace human connections but to those who can best augment and enhance them.


  • Fostering a Self-Sufficient Drone Manufacturing Landscape in India

    Fostering a Self-Sufficient Drone Manufacturing Landscape in India



    India’s Drone Tech Ecosystem: A Focus on Key Areas for Advancement

    India’s Drone Tech Ecosystem: A Focus on Key Areas for Advancement

    Summary

    India’s development in the drone tech ecosystem requires emphasis on five critical areas: propulsion systems, battery technology, semiconductor-driven sensors, flight software, and advanced materials. Creating simplified drone certification sandboxes for non-defence purposes and establishing state-level single-window systems could significantly reduce compliance costs. The government must streamline policies, support research and development initiatives, and serve as an anchor buyer to further enhance the drone tech ecosystem.

    The Growing Use of Drones in India

    The application of drones in India has broadened immensely, spanning from recreational use to vital roles in agriculture and defence. Despite this expansion, the country’s manufacturing largely depends on imported components, creating a disconnect between the potential and the actual performance of the drone sector.

    The government has taken steps such as implementing an import ban and initiating the production-linked incentive (PLI) scheme aimed at promoting local manufacturing to achieve self-reliance. However, significant challenges remain, including fragmented supply chains, dependence on imports for critical components, insufficient research and development funding, protracted processes, and persistent perceptions on quality.

    Fixing India’s Fragmented Drone Supply Chain

    India’s journey into drone manufacturing must begin by addressing its fragmented supply chains. The original PLI scheme, while ambitious, failed to tackle grassroots challenges. For instance, sourcing fundamental components like motor controllers and carbon-fibre composites can be time-consuming. Many micro, small, and medium enterprises (MSMEs), lacking assured demand, are hesitant to invest in niche areas such as aerospace manufacturing.

    Nevertheless, the revised scheme, designed with streamlined processes and a focus on supplier networks, holds promise. By encouraging anchor manufacturers to mentor MSMEs, the sector could replicate the success seen in the mobile industry. If implemented on a national scale, this model could significantly support the “Make in India” initiative.

    Another pressing concern is the continued reliance on imported subsystems. Although the ban on finished drone imports introduced in 2022 has had some impact, critical components like lithium batteries, sensors, and flight controllers still come from abroad, particularly China. Hence, it is crucial to create an indigenous system that promotes self-reliance.

    To facilitate this, India should focus on propulsion systems, battery technology—potentially partnering with ISRO for space-grade solutions—semiconductor-driven sensors, local flight software development, and advanced materials like carbon fibre. The EY-FICCI report forecasts a market of INR 2,300 Cr by 2030, contingent on this strategic pivot.

    Bridging the Research and Development Gap

    Equally important is addressing the research and development divide. Institutions like CSIR-NAL provide necessary testing infrastructure, yet a cooperative effort between academia and industry is needed. Academic institutions can foster innovation while industry participants bring indigenous scientific advancements to life, creating drones that can compete globally.

    To harness this potential, initiatives such as the establishment of a national R&D cluster or a “Drone Valley,” similar to Hyderabad’s Pharma City, should be pursued, complemented by tax incentives for intellectual property (IP) generation and collaborations with the government to address sector-specific challenges, like optimising crop-spraying drones for Indian agriculture.

    India’s drone supply chain also faces regulatory uncertainties around certifications, which can delay production. Enhancing self-reliance requires a streamlined approval process through unified digital platforms and support for domestic manufacturing, which could include grants for material innovation and tax rebates for private sector collaborations.

    Bureaucratic processes must be simplified to enable innovation. For startups, lengthy certification processes from application to final tests can hinder growth. Creating simple certification sandboxes for non-defence applications and state-level single-window systems, like the trailblazing model in Gujarat, could drastically reduce compliance costs. Additionally, defence contracts should prioritise startups in niche technology procurement.

    Finally, efforts should focus on dispelling the notion that ‘Made in India’ drones lack quality. Establishing industry standards, adopting ASTM International guidelines, creating a “Drone Mark” certification, and showcasing Indian-produced drones at international events (such as logistics corridors in Dubai) can help rebuild confidence.


  • Navigating AI Hallucinations: A Guide to Ethical AI Management for Startups

    Navigating AI Hallucinations: A Guide to Ethical AI Management for Startups



    AI Hallucinations Management: Ensuring Fairness in Startups

    AI Hallucinations Management: Ensuring Fairness in Startups

    AI hallucinations management is becoming essential as most deployed AI systems still lack the ability to fairly assess data sets or compensate for issues in their raw materials. A recent report reveals that 82% of Americans and Europeans believe careful management of AI hallucinations is necessary.

    Concerns Surrounding AI Hallucinations

    A report from the Centre for the Governance of AI at the University of Oxford from 2024 highlights several concerns about AI usage in startups. Issues range from surveillance and misinformation to data privacy violations, hiring biases, and the reliance on autonomous vehicles and drones. The increasing reliance on machines to propagate injustices raises questions about the implications of AI in modern society.

    The Need for Fairness Testing in AI Systems

    Bias in AI can arise from flawed data inputs that might be outdated, poorly selected, or reflective of historical societal prejudices. As AI systems grow, they might amplify existing unfairness, potentially making biased decisions appear as global truths. Current AI systems do not consistently conduct fairness tests on their data sets or address their inherent issues.

    Algorithmic Bias in AI Startups

    Within AI startups, algorithmic bias is a serious concern. For example, if price variations are based on shopping behaviours that correlate with gender or race, it can lead to significant ethical and legal challenges for those businesses.

    Strategic AI Ethics Management for Startups

    Startups are contemplating the ethical frameworks guiding their operations. Prominent figures like Microsoft president Brad Smith advocate for ethical considerations around technologies such as facial recognition. Google has formed an AI ethics advisory council, while Amazon is collaborating on initiatives with the National Science Foundation.

    Over the past three years, discussions on AI governance have intensified, including contributions from the Institute of Electrical and Electronics Engineers (IEEE). They have created a global crowd-sourced document addressing the ethics of autonomous and intelligent systems.

    Global Perspectives on AI Ethics

    Developing a global perspective on AI ethics is necessary, as viewpoints on privacy and ethics differ significantly. For instance, UK citizens may accept video surveillance in certain areas due to historical events, while Germans have a more privacy-centric outlook, influenced by past intrusions by the Stasi. In China, there is a level of acceptance of AI implementations like facial recognition due to cultural values prioritising social order.

    Startups are increasingly focusing on developing standardised AI ethics and compliance frameworks. Microsoft’s AI ethics research entails ethnographic studies to analyse varying cultural behaviours with insights from experts.

    Mitigating AI Hallucinations for Startups

    As startups invest heavily in creating AI-driven products, public trust is not something that can be taken for granted. Fairness, transparency, and accountability are paramount in establishing trust in AI technologies. However, even researchers in the field struggle to agree on a singular definition of fairness, leaving room for ambiguity regarding affected groups and evaluative metrics.

    Engaging in the Discussion on AI Ethics

    Startups must actively engage in the discussion surrounding ethical AI practices. Avoiding the issue of “bad” AI will not resolve it; instead, identifying founders willing to contribute to dialogue and establish consistent standards is essential. Appointing a Chief AI Ethical Officer could help promote awareness and commitment to AI ethics within startups.

    When aligned with ethical practices, AI startups can deliver significant benefits, such as educational interventions for underserved communities and improved healthcare outcomes through responsible data use. The focus should now be on ensuring that AI design and deployment are fair, transparent, and accountable, paving the way for meaningful regulations and standards in AI ethics that serve all stakeholders.


  • India’s Defence Technology Revolution: A Call for Venture Capital Engagement

    India’s Defence Technology Revolution: A Call for Venture Capital Engagement



    India’s Defence Tech Revolution: A Call to Action for VCs


    India’s Defence Tech Revolution: A Call to Action for VCs

    India’s defence tech landscape is experiencing a significant transformation, merging deeptech with national security, where startups are becoming integral to the defence strategy.

    The Timing Is Perfect

    India’s defence technology potential is now a reality, with clear indicators emerging:

    • More than 100 defence tech startups are currently operating.
    • The projected defence budget for FY25-26 has surpassed INR 79,000 Cr, with around 70% allocated for domestic purchases.
    • Defence exports reached $2.63 Bn in FY24, marking a 32% increase year-on-year.
    • Key institutional frameworks such as iDEX, Mission DefSpace, and the Technology Development Fund are fully functional.

    Indigenous Procurement: A Major Step Forward

    In a substantial move towards self-reliance, the defence ministry recently awarded a contract worth INR 62,700 Cr to Hindustan Aeronautics Ltd (HAL) for 156 light combat and utility helicopters. This significant order to an Indian public sector unit signals the government’s commitment to nurturing domestic capabilities on a large scale. For entrepreneurs and venture capitalists, this highlights the urgency of investing in technologies that can enhance India’s industrial defence infrastructure.

    Defence as the Pioneer of Deeptech

    History demonstrates that numerous major technological advances, including GPS, the internet, radar, and space exploration, have emerged from defence research facilities. India’s Defence Research and Development Organisation (DRDO) has successfully transitioned dual-use innovations into mainstream applications: consider bio-toilets for Indian Railways, lightweight ballistic vests for police personnel, and high-altitude rations for disaster management.

    Currently, startups such as ideaForge, NewSpace Research, Big Bang Boom, Tonbo Imaging, and Optimized Electrotech focus on addressing critical defence requirements with scalable technology. These are not mere prototypes; they are functional systems, some of which have already been exported or are ready for initial public offerings.

    Convergence of Defence and Commercial Markets

    This is where the realms of defence and commercial total addressable market (TAM) begin to overlap, making it essential for venture capitalists to take notice.

    India’s Opportunity to Follow a Global Path

    The framework is already established globally. In the United States, venture-backed defence innovators like Palantir and Anduril are reshaping the landscape where private funding meets national security needs.

    Palantir originally focused on intelligence agencies and has expanded to supporting military strategy and public health initiatives. Anduril, founded by Oculus co-founder Palmer Luckey, developed AI-enhanced surveillance systems and autonomous drones, rapidly growing into a $14 Bn defence technology enterprise within a decade.

    These firms forged ahead without waiting for approvals, infusing speed and software solutions into an industry dominated by traditional contractors. They demonstrated that startups are capable of, and can compete for, major defence contracts.

    India stands at the cusp of a similar evolution. With robust engineering talent, a more accessible procurement process, and the geopolitical necessity to foster sovereign capabilities, Indian startups are well-positioned to spearhead a new wave of global defence innovation. However, this growth will require courageous entrepreneurs, committed investors, and a venture ecosystem that appreciates both intellectual property and societal impact.

    Overcoming Challenges in Defence Tech

    Engaging in the defence sector is distinct from software as a service (SaaS). The funding cycles are extended, the primary buyer is often the government, and the market still favours public sector undertakings and established conglomerates with long-standing contracts.

    Challenges include:

    • Complex procurement and lengthy approval processes.
    • Unfavourable practices by large legacy players, including OEM pressuring, undervalued mergers and acquisitions, and equity stakes.
    • Capital inefficiency caused by delayed payments.
    • Investor unfamiliarity with defence compliance, intellectual property laws, and foreign direct investment regulations.

    Strategies for Venture Capital in Defence Tech

    For those looking to thrive in defence tech, consider the following strategies:

    • Focus on Core Science and IP: Prioritise supporting startups that are developing innovations in autonomy, intelligence, surveillance, reconnaissance, cybersecurity, and signal processing.
    • Strategise Capital Allocation: Assist startups in leveraging TDF/iDEX grants, bank guarantees, and credit options to reduce equity dilution.
    • Encourage Defence Expertise: Motivate teams to recruit former military personnel and procurement experts who understand the nuances of government systems.
    • Support Dual-Use Innovations: Consider investments in firms that can also serve commercial markets, such as drone technology, AI surveillance, and resilient networks.
    • Think Globally: Recognise that many defence solutions, particularly in drone technology and counter-UAS systems, can appeal to markets in the Global South and Indo-Pacific.
    • Adopt a Long-Term Perspective: Understand that the defence sector rewards patience, depth in intellectual property, and collaboration across various domains.

    More Than Just a Sector for Investment

    It is uncommon for a field to present both economic opportunities and strategic importance. Defence technology occupies this crucial space.

    The focus is on developing self-sufficient capabilities. It aims to reduce dependency on international supply chains for national security. Moreover, the goal is to foster globally competitive deeptech companies that embody genuine intellectual property and enduring value.

    The demand for patient capital and investors with strong conviction in this area is greater than ever. Additionally, there is a need for more entrepreneurs who are willing to design solutions for defence while adapting them for global application.

    The opportunity to invest is present. The supportive conditions are favorable. The pivotal question remains: Will Indian venture capital rise to the occasion?