Agentic AI in Indian BFSI: From Automation to Autonomous Banking
Agentic AI in Indian BFSI is moving beyond traditional automation and entering an era of intelligent autonomy. The Banking, Financial Services, and Insurance (BFSI) sector in India is experiencing a radical shift, as AI-powered systems evolve from scripted processes to adaptive agents that make decisions, learn from outcomes, and respond in real time. According to a 2025 Nasscom report, over 64% of BFSI leaders in India have already piloted agentic AI tools to enhance underwriting, fraud detection, and customer service. At Keev Capital, we view this transition as one of the most promising vertical applications of AI in emerging markets. Startups and institutions that embrace this change early will be best positioned to lead the next wave of digital finance. From Workflow Automation to Adaptive AI Agents For years, Indian BFSI institutions have relied on rule-based automation for tasks such as onboarding, KYC, loan processing, and customer support. These systems follow static logic, offering efficiency but lacking adaptability. Agentic AI, by contrast, brings contextual awareness and decision-making autonomy to the table. Instead of passively executing steps, agents can now interpret data, identify anomalies, and adjust strategies in real time. For example, credit scoring agents can now modify thresholds based on a customer’s cash flow history rather than fixed credit models. This evolution aligns closely with the innovation we track across fintech ventures, many of which are now integrating agentic AI to manage risk dynamically, simulate portfolio outcomes, and detect evolving fraud patterns. Use Cases Transforming BFSI in India One of the most notable applications of agentic AI is in intelligent underwriting. Fintech lenders in India are now deploying AI agents that review unstructured data—such as phone usage patterns, eCommerce activity, or GST filings—to create hyper-personalized credit decisions. This model expands access to financing for underbanked populations and MSMEs. Another emerging use case is real-time fraud detection. Instead of relying on hard-coded rules, BFSI firms are building agents that continuously learn from user behavior and generate new fraud signatures on the fly. In sectors like healthcare finance, where patient billing and insurance interactions generate high data velocity, agentic AI is enabling more transparent and secure transactions. Customer service is also being reshaped. Intelligent agents now respond to complex queries across voice, chat, and mobile apps—making decisions based on customer intent, historical sentiment, and financial behavior. These capabilities are increasingly relevant in consumer finance, where fast, adaptive support drives brand loyalty and retention. Infrastructure That Enables Autonomous BFSI While agentic AI promises speed and intelligence, it demands a strong digital foundation. Indian banks and NBFCs must modernize their data ecosystems to support live learning loops and real-time model training. Architectures like data lakehouses and microservices allow agents to access and act on updated information instantly. Governance is equally critical. Institutions must define access policies, traceability standards, and ethical guardrails for AI agents acting on behalf of the organization. This mirrors the foundational requirements discussed in our insights on data readiness for agentic AI where governance, access, and retraining systems form the core of trustworthy AI operations. The Role of Regulation and Responsible AI The transformation of Indian BFSI through agentic AI also intersects with regulation. The Reserve Bank of India (RBI) has been proactive in outlining AI auditability and transparency standards. As agentic systems take on more responsibility, maintaining interpretability and fairness becomes essential. New guidelines are expected to formalize explainability thresholds for AI in credit scoring, loan approvals, and automated compliance reporting. This trend aligns with the broader global emphasis on responsible AI governance, reinforcing the need for startups and institutions alike to build transparent, accountable systems. Conclusion: India’s BFSI Sector Is Entering Its AI-First Phase Agentic AI in Indian BFSI is no longer a futuristic concept—it is happening now, reshaping how financial institutions operate, serve customers, and manage risk. The leap from automation to autonomy is creating space for nimble startups, data-driven banks, and inclusive financial products. By adopting AI agents that act with intelligence and responsibility, Indian financial firms can address market complexity and scale their operations with precision. For founders building in fintech, insurance, or vertical AI infrastructure, this is a rare window of opportunity. At Keev Capital, we invest in startups transforming legacy systems with new intelligence. If you are building the future of financial autonomy in India, connect with our team to explore how we can partner with you in this AI-powered evolution.
Is Your Data Ready for Agentic AI? Building the AI‑Ready Foundations That Win Deals
Is your data ready for agentic AI? This question is now front and center for startups aiming to attract institutional investment and deploy next-gen AI capabilities. A recent report from TechRadar revealed that 78% of organizations are unprepared to support autonomous AI agents due to fragmented, inconsistent, or inaccessible data. At Keev Capital, we see this gap not just as a technical limitation but as a critical barrier to scalability. If you’re building in vertical AI, fintech, education, or healthcare, your ability to consolidate, label, and govern your data may determine whether your product wins the market—or gets passed over by investors. Why Agentic AI Needs Structured, Accessible Data Agentic AI systems go beyond automation. They act, decide, and adapt in real time, relying heavily on dynamic data environments. To function properly, they require consistent schemas, complete labeling, robust metadata, and secure access permissions. Startups looking to implement these systems must ensure that data pipelines are fast, normalized, and secure. Whether you’re developing solutions in vertical AI or intelligent consumer platforms, agentic models must be trained on live data ecosystems, not static dashboards or isolated SQL queries. What Investors See in Data-Ready Startups From an investment standpoint, startups with AI-ready data architectures stand out. At Keev Capital, our team evaluates data maturity across four dimensions: governance, real-time access, structure, and scalability. For example, fintech ventures with clean transaction logs, anti-fraud labeling, and secure client permissions tend to outperform peers during integration. Our experience with fintech deals shows that early attention to data cleanliness correlates directly with faster product-market fit and easier regulatory compliance. Consolidate with Modern Architectures Like Lakehouses To enable agentic AI, startups must move beyond outdated silos and embrace unified architectures like data lakehouses. These platforms combine the best of data lakes and warehouses, allowing both structured and semi-structured data to coexist with low latency and high flexibility. This model also supports real-time analytics, which are essential for agents that interact with customers or systems on the fly. We’ve seen promising early adoption in sectors like environmental tech where startups model sensor data, satellite feeds, and sustainability metrics in one accessible platform. Secure and Govern: Don’t Let AI Access Become a Liability With agentic systems accessing multiple endpoints, governance becomes critical. Your AI can only be as responsible as your access controls and audit trails. Founders should enforce permissioned access based on role, purpose, and context, just as they would for human staff. If you’re operating in healthcare, ensure HIPAA-compliant tokenization is in place before training or deploying models. This level of proactive governance not only reduces risk but also builds investor trust. Train on Feedback Loops and Real-World Signals An AI-ready dataset doesn’t stop at collection—it evolves through feedback loops. Autonomous agents must learn from success and failure, which means startups need systems that capture performance metrics, user interactions, and business outcomes. Whether your AI is tutoring a student, underwriting a loan, or analyzing carbon impact, it must be retrained regularly. We’ve seen strong signal refinement in education startups that incorporate human feedback into labeling and contextual prompts, boosting model accuracy over time. Conclusion: Data Maturity Is the New Technical Due Diligence In today’s AI-driven market, data maturity is not just a back-end concern—it’s front and center in technical due diligence. Investors now ask, “Is your data ready for agentic AI?” before funding rounds and strategic partnerships. Building strong data foundations signals readiness, scalability, and a founder’s understanding of AI’s operational needs. Founders who invest early in clean, governed, and unified data ecosystems will have a major edge in deploying agentic systems that drive real value. Startups that consolidate data infrastructure early can shorten development cycles, build trust faster, and gain a competitive edge. At Keev Capital, we actively seek out founders who view data readiness as core to their AI roadmap. If you’re building in vertical AI, fintech, healthcare, or climate innovation, and want to scale with agentic systems that investors trust, contact our team to explore how we can support your mission.
Managing Agentic AI as Your Digital Workforce: A Strategic Imperative for Startup Success
Managing agentic AI as your digital workforce is quickly becoming a strategic necessity for venture-backed startups. As agentic AI systems evolve from tools into autonomous agents capable of decision-making, execution, and adaptation, founders must treat them less like software and more like employees. According to McKinsey, 40% of large organizations are actively exploring agentic AI adoption in operational workflows. For early-stage ventures, this presents both a breakthrough and a risk. To thrive, founders must approach these systems with structured onboarding protocols, KPI frameworks, and permission governance, mirroring human resources strategies. By treating agentic AI systems like digital employees, startups can unlock productivity while mitigating the risks of AI sprawl. Define Clear Roles for Each Agentic AI System Tailor AI Roles to Your Startup’s Domain The first step in managing agentic AI is defining its role within your organization, just as you would with a new hire. What decisions can the system make independently? Where does it require approval? Is it a support function, such as a coding agent or a marketing assistant, or a revenue-generating one like autonomous trading or sales operations? In our vertical AI sector insights at Keev Capital, we emphasize the importance of vertical specificity when integrating AI tools. Businesses deploying these systems in healthcare, fintech, or education must tailor role design based on industry compliance, data sensitivity, and user interaction levels. Set KPIs That Reflect Performance and Autonomy Why Agentic AI Needs Metrics Just Like Human Staff Once the role is clear, define the KPIs that reflect performance, autonomy, and trustworthiness. Just as you’d track a marketing team’s lead volume or a salesperson’s close rate, agentic AI should be measured against task completion accuracy, cycle time reduction, and learning adaptability. In fintech applications, for example, agentic AI can streamline KYC verification or credit underwriting, but must be closely monitored for compliance consistency and false positives. Establishing baselines and tolerances early ensures that startups retain control while scaling efficiency. Control Access With Permissioning Best Practices Limit Risk Through Layered Access and Audit Trails Another critical practice is permissioning: determining what data an agent can access, what systems it can alter, and who can override its actions. Without clear access policies, startups risk shadow AI, unintended consequences, or even security breaches. This is especially crucial for startups in environmental tech and healthcare, where regulatory standards such as HIPAA or carbon disclosure require controlled information flows. Treat permissions like access cards: grant minimal privilege, track behavior, and adjust based on performance and reliability. Log and Document Every AI Decision and Update Build Institutional Knowledge and Transparency Another overlooked strategy is documenting agentic AI onboarding as part of the company’s operational playbook. Startups often grow fast and hire quickly; unless AI systems are tracked like team members, knowledge gaps emerge. Document decisions made, KPIs tracked, model updates performed, and exceptions handled. Just as HR departments log employee reviews, businesses must maintain agent logs. This parallels the logic we apply when evaluating tech stacks in consumer goods ventures, where scalable, auditable processes separate top performers from chaos. Promote Collaboration Between Humans and AI Agents Teach Teams How to Delegate and Escalate Effectively Agentic AI also benefits from human-AI collaboration training. Much like onboarding a junior staff member, you don’t just assign tasks, you build shared context. In education technology, we’ve observed that blended models, combining AI with human guidance, lead to better learning outcomes and trust. Apply this logic internally: coach your team on how to delegate effectively to AI systems, when to intervene, and how to escalate exceptions. Frictionless collaboration between humans and AI maximizes return on automation. Conclusion: Build an AI Workforce You Can Trust and Scale In conclusion, managing agentic AI as your digital workforce isn’t just a technical integration, it’s a leadership mindset. Define its role, set KPIs, manage permissions, document its journey, and enable human collaboration. These five steps mirror the best HR onboarding practices and serve as the foundation for responsible and scalable AI growth. Founders who embrace this approach will not only avoid AI sprawl and compliance risk, they will gain a strategic advantage by scaling with intelligence and intention. Startups that master this shift now will be the ones to scale rapidly and responsibly in the agentic AI era. Keev Capital believes in backing forward-thinking ventures ready to build not just AI-powered platforms but AI-governed organizations. If your startup is working in vertical AI, fintech, healthcare, or sustainable tech, and you’re ready to scale with intelligent systems, contact our team to learn how we can help accelerate your mission.
India’s Export Economy Under Pressure From Global Tariffs
India’s export economy is becoming a headline issue in 2025, driven by a sharp rise in global protectionist policies. The U.S., EU, and Southeast Asia have all introduced or increased tariffs on goods imported from India, resulting in a 2.6% year-over-year drop in India’s exports in Q2 2025. As exports contribute nearly 20% to the national GDP, this poses a risk not only to the trade balance but also to employment, capital markets, and startup valuations. Pharma Exports Face Tighter Scrutiny and Pricing Pressure U.S. Tariffs Hit API Supply Chains India’s pharmaceutical sector, which supplies over 20% of global generic drugs, is now facing U.S.-imposed tariffs on active pharmaceutical ingredients (APIs). These barriers increase costs and slow regulatory clearances, affecting leading players such as Sun Pharma and Lupin. To mitigate these risks, investors are leaning toward startups focused on biosimilars, domestic production, and smart diagnostics. As part of our investment focus at Keev Capital, we continue to evaluate long-term opportunities within India’s healthcare innovation sector that prioritize R&D autonomy and supply chain resilience. Textiles and Apparel Exports Lose Ground in Europe Sustainability and Tariffs Drive New Compliance Challenges India’s textile industry supports over 45 million jobs and earns $40 billion+ annually through exports, primarily to the EU and the U.S. However, new EU carbon tariffs and material sourcing rules are pushing buyers to seek alternate vendors. Indian manufacturers must now integrate sustainability with vertical automation. Electronics and Tech Hardware Exports Face Southeast Asian Competition Vietnam, Indonesia Gain Trade Advantages India’s mobile and electronic components sector is feeling the squeeze from Southeast Asian competitors who benefit from more favorable trade deals. While India’s PLI scheme has driven local production, the next leap will come from embedding vertical AI into smart manufacturing workflows. Fintech Under Indirect Pressure From Reduced Export Flow Capital Movement Affected by Slowing Trade Volumes Tariffs don’t directly hit fintech, but cross-border payments, trade financing, and transaction volumes shrink when exports decline. That’s why resilience in India’s fintech landscape now requires platforms that enable agile, multi-market operations with minimal dependency on legacy infrastructure. Environmental Tech and Education Feel the Policy Ripple Effect Green Equipment Exports and SaaS Edtech Models Face Constraints India’s climate technology innovators and green hardware producers may face friction when exporting to nations with shifting tariff policies. Localized production and R&D are becoming vital. For investors targeting environmental tech, this means re-evaluating supply chains and partnerships. Digital education and edtech platforms exporting content or remote learning services may face new service taxes or cross-border remittance rules. The growing education innovation sector will need to incorporate compliance-ready infrastructure from day one. India’s Path Forward: Innovation, Diversification, and Smart Capital India’s export economy under pressure is not a short-term issue. It signals a structural realignment of global trade, where regional blocs and self-reliant ecosystems are replacing legacy trade networks. To maintain competitiveness, India must shift from low-margin manufacturing to high-value innovation, especially in tech, healthcare, and AI. Keev Capital is actively identifying resilient sectors, including healthcare, vertical AI, and consumer goods, that can scale amid global uncertainty. The rising wave of tariffs is more than just a policy trend; it’s a strategic signal. India must now focus on product diversification, local sourcing, and innovation that attracts global capital even Tin a deglobalizing world. Companies prepared to adapt will not only survive, they will lead the next era of smart trade. Investors, founders, and strategic partners can learn more about how Keev Capital supports this shift through our contact page.
U.S. Tariffs on India: Will Pharma Exports Lose Their Competitive Edge?
The imposition of new U.S. tariffs on India pharma exports has raised alarm in both trade and investment communities. India currently supplies over 20% of the world’s generic drugs, making it a critical player in global healthcare. According to Pharmexcil, this dominance is now at risk as the U.S. introduces new tariffs and stricter scrutiny on APIs and finished formulations. With compliance costs increasing, India’s pharma sector could lose pricing advantages and market share. India’s Pharma Dominance Under Threat India’s pharmaceutical exports reached $25.3 billion in FY2024, and nearly one-third of this went to the U.S., based on Statista data. Indian firms have thrived due to their ability to offer high-volume, FDA-compliant production at low cost. However, U.S. domestic manufacturing incentives and policy shifts are now eroding this advantage. As Keev Capital continues to explore innovation in healthcare, we are closely tracking how Indian pharmaceutical companies respond to these new global challenges with product upgrades, process improvements, and regulatory reinvention. How Tariffs Increase Supply Chain Friction Rising Costs and Delays in Regulatory Approvals These tariffs not only raise costs but also create logistical slowdowns at U.S. customs. According to the United States Trade Representative, the new trade policy is part of a broader national reshoring effort. This shift results in delayed port clearances and increased warehousing needs, particularly affecting smaller exporters. For Indian firms that rely on streamlined export cycles, this creates risk across the board. As observed in our vertical AI investment thesis, supply chain automation and compliance intelligence are becoming essential to maintain operational efficiency and reduce export friction. Opportunities in Vertical Integration and AI-Driven Compliance Can Indian Pharma Turn Challenges into Transformation? Rather than view the U.S. tariffs on India pharma exports solely as a setback, forward-looking pharma companies are using this moment to vertically integrate and build control over their supply chains. This includes owning raw material sources, APIs, and formulation facilities within India to reduce dependency on third-party suppliers. Digital transformation is also accelerating. AI-powered platforms are now used to manage FDA submissions, automate quality checks, and reduce regulatory risk. This aligns with Keev Capital’s interest in AI-enabled compliance and manufacturing tools, which are rapidly becoming a necessity for global competitiveness. Long-Term Investor Outlook: Resilience Over Scale Indian pharma’s ability to adapt has already been proven during the COVID-19 pandemic, when companies rapidly scaled to meet international demand. The question now is whether they can shift from volume-based leadership to value-added specialization. We are seeing cross-sector convergence, where pharmaceutical innovation overlaps with environmental tech in sustainable packaging, consumer goods in wellness formulations, and education in compliance training. These are core themes in Keev Capital’s investment strategy. Conclusion: Pharma at a Turning Point The U.S. tariffs on India’s pharma exports are not simply regulatory changes. They signal a deeper realignment in global supply chains and trade policy. India must respond not by cutting costs, but by upgrading its production infrastructure, expanding strategic partnerships, and investing in innovation. Keev Capital is committed to backing startups and scale-ups that are building next-generation healthcare infrastructure. Our portfolio across healthcare, vertical AI, and regulatory technology reflects our belief that resilience, not just reach, will define global leadership in pharmaceuticals.
DPDPA Day One: Turning Compliance into a Competitive Edge for India’s Vertical-AI Start-ups
India’s DPDPA Day One marks a defining moment for vertical-AI start-ups. The Draft Digital Personal Data Protection Rules 2025, now open for consultation, are expected to become enforceable later this year. For founders in fintech, ed-tech, and health-tech, these rules are not just compliance hurdles; they are strategic opportunities. According to the International Association of Privacy Professionals, early compliance can boost investor confidence and mitigate regulatory risks. This is why Keev Capital’s vertical-AI investment focus emphasizes privacy-by-design as a foundational growth driver. Understanding DPDPA Day One The DPDPA introduces three core pillars for start-ups handling personal data: localisation, children’s data protection, and cross-border transfer regulation. Data localisation mandates that certain categories of sensitive or critical data remain within India. This impacts vertical-AI players in fintech and health-tech, where transaction histories or patient records cannot leave the country without explicit clearance. Children’s data protection is another high-stakes requirement. Ed-tech start-ups, a focus area for Keev Capital’s education sector investments, must now secure verified parental consent and implement age-appropriate safeguards. Finally, cross-border transfer restrictions introduce operational complexity but also potential moats. Firms that can securely navigate approvals for AI model training using global data will hold an advantage in a market that American Bar Association experts call “increasingly trust-driven.” Keev’s Diligence Checklist for Founders Before raising capital or launching products in a regulated space, vertical-AI start-ups should align with a privacy-first framework. Keev Capital’s diligence for fintech, ed-tech, and health-tech founders includes: Data Localisation Map all personal and sensitive data flows. Ensure servers handling regulated data are physically located within India. This is especially critical for companies in fintech, where payment and identity data trigger strict localisation requirements. Start-ups should also audit third-party vendors and cloud service providers for localisation compliance to avoid downstream violations. Children’s Data and Consent Build robust parental verification mechanisms and clear opt-in processes for any platform targeting minors. Apply minimal data collection principles to lower compliance overhead. Ed-tech start-ups must additionally ensure that privacy policies are transparent, age-appropriate, and accessible in regional languages, aligning with India’s multi-lingual, youth-driven user base. Cross-Border Transfer Readiness Develop clear data-transfer protocols, including encryption, anonymisation, and government-approved pathways for cross-border flows. This includes creating fallback systems for data access if approvals are delayed. Health-tech ventures supported by Keev’s healthcare portfolio gain investor confidence by documenting these processes in their compliance logs, showing preparedness for audits and partnership due diligence. Ongoing Governance and Privacy Audits Beyond initial compliance, Keev also expects start-ups to institute regular privacy audits and designate a Data Protection Officer (DPO) or similar governance lead. This person should oversee adherence to DPDPA mandates, employee training, and coordination with legal advisors on evolving regulatory updates. By embedding these practices early, vertical-AI start-ups demonstrate a maturity that de-risks investment and opens doors to strategic partnerships, especially with enterprise clients and government-facing platforms. Compliance as a Strategic Moat While compliance is often seen as a cost center, DPDPA Day One turns it into a defensible moat. Investors increasingly view regulatory readiness as a proxy for operational maturity. In highly regulated verticals, the ability to manage data responsibly becomes a competitive differentiator. Vertical-AI start-ups that master compliance can expand faster, win enterprise contracts, and access sensitive data domains safely. This advantage compounds in emerging spaces like AI-driven patient analytics and adaptive learning platforms, where data trust is a market gatekeeper. Conclusion and Call to Action The arrival of DPDPA Day One reshapes India’s AI start-up landscape. Fintech, ed-tech, and health-tech founders who embrace compliance early will not only avoid penalties but also position their companies for premium valuations and faster market adoption. Investors like Keev Capital see regulatory alignment as a core part of de-risking vertical-AI opportunities. Companies that integrate data privacy into product design are building future-ready businesses. For start-ups looking to raise capital or validate their compliance roadmap, Keev Capital provides the strategic insight and sector expertise to accelerate growth. To explore how regulatory readiness can enhance your market positioning, connect with our team and discover how privacy-driven innovation builds sustainable value.
Tokenised Real-World Assets: How RBI’s Sandbox Redefines Indian Fintech
The emergence of tokenised real-world assets is transforming Indian fintech. With the Reserve Bank of India (RBI) and the International Financial Services Centres Authority (IFSCA) now piloting tokenisation frameworks through regulatory sandboxes, the country is aligning with global leaders like Singapore and Abu Dhabi. These initiatives are more than experiments; they are laying the groundwork for new asset classes to trade seamlessly across India’s digital rails. Platforms like InvestaX show how secondary markets for tokenised assets are rapidly evolving, signaling a new era of compliance-focused innovation. Keev Capital’s fintech expertise positions start-ups to capture value in custody, compliance, and secondary-trading layers that plug directly into UPI and ONDC. India’s Tokenisation Push and Global Context Tokenising real-world assets (RWAs) converts physical or financial assets—like bonds, real estate, or invoices- into blockchain-based digital tokens. RBI’s sandbox and IFSCA’s IFSC pilots provide a structured environment to test these models without full market exposure. Singapore’s Monetary Authority and Abu Dhabi Global Market are already experimenting with tokenised bonds and private credit, showing that Asia is becoming a hub for asset digitalisation. For Indian fintechs, the opportunity is twofold: integrating local settlement infrastructure such as UPI and ONDC while ensuring global-grade compliance. Keev’s portfolio approach to vertical AI and automation also plays a role, as machine learning enhances transaction monitoring and smart-contract-driven settlement. Custody, Compliance, and Secondary Trading as Growth Drivers The key to scaling tokenised real-world assets lies in robust custody, risk management, and liquidity solutions. Custody Solutions for Tokenised Assets Secure, regulated custody is critical as investors and regulators demand protection for tokenised holdings. Start-ups providing compliant digital vaults and API integrations with banks are becoming essential in India’s sandbox ecosystem. Compliance Layers and Reporting RWA tokenisation introduces cross-border and multi-asset complexities. Automated KYC/AML and integrated regulatory reporting give Indian players a competitive advantage. Keev Capital sees opportunities for healthcare-focused and ESG-aligned fintechs to lead in data protection and auditable flows. Secondary Trading on UPI and ONDC Liquidity is where tokenisation creates real market impact. By connecting tokenised assets to India’s real-time payment infrastructure, start-ups can enable frictionless peer-to-peer transfers and small-ticket participation. Open marketplaces powered by ONDC will accelerate the distribution of tokenised consumer and environmental-tech assets, bridging retail and institutional interest. The Strategic Advantage for Indian Start-ups Building on RBI’s sandbox allows Indian fintech innovators to create globally competitive models while ensuring domestic regulatory alignment. Global investors are increasingly seeking markets that combine robust compliance with scalable rails, and India’s fintech ecosystem is uniquely positioned to deliver. Tokenised real-world assets are no longer a futuristic idea—they are becoming a core infrastructure layer for next-generation capital markets. Keev Capital views these developments as a catalyst for start-ups integrating custody, compliance, and secondary-market capabilities into the fintech stack. From tokenised micro-loans to real-estate-backed instruments, the possibilities are vast, and regulatory clarity is accelerating adoption. Conclusion and Call to Action The rise of tokenised real-world assets represents a turning point for Indian fintech. RBI and IFSCA’s sandbox initiatives create a safe space for innovation while pushing the market toward fully regulated, high-liquidity digital assets. Companies that master custody, compliance, and secondary trading will define the backbone of India’s token economy, and early movers can claim defensible positions in global capital flows. Keev Capital supports start-ups transforming financial infrastructure with tokenisation and compliance-first models. As sandboxes evolve into permanent frameworks, fintechs that plug into UPI and ONDC will drive the next wave of digital asset adoption. Founders exploring tokenised asset models can leverage Keev’s experience in fintech innovation and access to strategic guidance by connecting with our team to turn regulatory readiness into lasting market leadership.
Silicon Swadeshi: Building Domestic Hardware Moats with RISC-V Edge-AI
The rise of Silicon Swadeshi marks a turning point for India’s hardware and AI ecosystem. Mindgrove has just launched the country’s first commercial RISC-V system-on-chip (SoC) designed for IoT and edge AI applications, signaling a major step toward domestic silicon capabilities. According to Wire Unwired, local silicon innovation not only boosts self-reliance but also strengthens national technology security. Keev Capital sees strategic value in supporting hardware–software co-design start-ups that serve the growing wave of vertical-AI applications dependent on efficient, in-country chip supply. Why Edge-AI and Domestic Silicon Matter The proliferation of IoT devices, industrial sensors, and AI-enabled edge nodes is driving an exponential demand for specialized processors. Unlike cloud-only AI, edge AI requires low-latency inference close to the data source. For India, relying solely on imported silicon introduces supply-chain vulnerabilities and cost inflation. Building a domestic ecosystem aligns with the vision of “Silicon Swadeshi,” where local chip design and fabrication underpin critical sectors like healthcare innovation and smart manufacturing. Mindgrove’s RISC-V SoC reflects this shift, offering a modular, license-free architecture that allows rapid customization for AI workloads. Globally, the RISC-V movement is gaining momentum, with open hardware initiatives lowering entry barriers for next-generation chipmakers. By integrating such processors into IoT and industrial networks, India can accelerate both digital transformation and hardware independence. The Case for Hardware Moats in Vertical AI Vertical-AI start-ups, from precision agriculture to medical imaging, require predictable, secure access to specialized silicon. Domestic production creates a hardware moat, ensuring supply even during global chip shortages. It also allows tighter hardware–software integration, which improves AI inference speed and energy efficiency. Keev Capital is particularly interested in start-ups that bridge design and deployment by co-developing algorithms optimized for local chips. For example, consumer-tech and environmental-tech solutions can integrate edge processors to monitor energy usage or air quality with real-time analytics, creating regulatory and market advantages. This co-design approach also makes compliance with export restrictions and data-localization rules more straightforward. RISC-V and Global Hardware Trends Globally, open-source RISC-V architectures are disrupting proprietary models long dominated by ARM and x86. In markets like the U.S., EU, and China, semiconductor strategies increasingly emphasize resilience and localization. India’s entry into this arena is timely, as domestic AI adoption is projected to grow 20% year-over-year in industrial and consumer IoT segments. Start-ups participating in this trend can plug into a robust hardware value chain: edge devices feeding UPI-enabled fintech systems, AI-enhanced consumer goods, and smart city deployments. Partnerships with local fabs and research institutes will further shorten innovation cycles while attracting ESG-focused investors seeking sustainable, resilient supply chains. Keev Capital’s Investment Lens At Keev Capital, we believe the convergence of Silicon Swadeshi, edge AI, and vertical applications creates a once-in-a-decade opportunity. We prioritize start-ups building hardware–software co-design solutions that can scale across IoT, industrial automation, and regulated sectors. Integrating chip design expertise with vertical-AI domain knowledge delivers defensible IP and high switching costs for global and domestic customers. This thesis extends to education and skills development, where learning-tech platforms can train the next generation of chip designers and embedded AI engineers. The long-term goal is to foster an ecosystem where India moves from chip consumer to chip creator, strengthening both economic and strategic moats. Conclusion and Call to Action The Silicon Swadeshi movement is more than a slogan, it is the foundation of India’s next technology leap. By combining RISC-V edge-AI chips with vertical-AI applications, domestic start-ups can create sustainable hardware moats, reduce reliance on imports, and deliver energy-efficient solutions at scale. As global supply chains remain volatile, local silicon ensures both resilience and market differentiation. Keev Capital is committed to supporting start-ups that integrate hardware and AI for maximum market impact. Founders building edge-AI devices, IoT analytics, or chip-optimized software stacks can benefit from our experience in co-design investment strategies. Our team is ready to partner with innovators who see silicon independence as the next frontier for India’s AI-driven growth.
Blue-Carbon Premium: Mangrove Offsets Outpace Forest Credits
The rise of the Blue-Carbon Premium is transforming global voluntary carbon markets. Recent reports from Nature Net Zero and other market trackers show that mangrove offsets are trading at nearly three times the price of traditional forest-carbon credits, driven by their dual impact on carbon sequestration and coastal resilience. For India, home to over 7,500 km of coastline, this shift presents a once-in-a-generation opportunity for climate-aligned investments. Keev Capital’s environmental-tech focus is exploring the investible stack that can bring blue-carbon projects from concept to scalable, finance-ready assets. Why Mangrove Credits Command a Premium Mangroves are nature’s carbon powerhouses, storing up to four times more carbon per hectare than terrestrial forests due to their rich soil carbon pools. Beyond sequestration, they provide critical co-benefits, protecting coastlines from erosion, supporting biodiversity, and shielding communities from storm surges. These co-benefits translate to higher buyer willingness in voluntary carbon markets, where demand for high-quality, verifiable credits is accelerating. India’s coastline, including the Sundarbans and Andhra mangrove belts, is emerging as a priority project zone. Verified blue-carbon projects can access international buyers seeking premium offsets that align with both climate and ESG mandates. Start-ups working in this space are increasingly integrating digital measurement, reporting, and verification (MRV) to ensure their credits meet global registry standards. This is where vertical AI applications add value by automating satellite imagery analysis and reducing MRV costs for large-scale mangrove restoration. Building the Investible Blue-Carbon Stack The future of blue-carbon investments lies in a tech-enabled, community-first model that can deliver verifiable, high-integrity credits while ensuring local buy-in. Keev Capital identifies four layers of the investible stack: Remote-Sensing MRV Platforms Satellite and drone-based MRV reduces the high cost of manual verification and enables continuous project monitoring. AI-driven analytics can calculate biomass growth and soil carbon accumulation with increasing accuracy. Community Engagement and Livelihood Platforms Mangrove restoration only succeeds with local participation. Platforms that provide incentives, ranging from micro-payments to sustainable aquaculture models, can ensure projects are maintained for decades. Integration with financial inclusion initiatives, often powered by fintech solutions, enhances project sustainability. Climate Finance and Tokenisation Voluntary carbon markets are moving toward digital-first credit issuance. Tokenizing verified blue-carbon credits enables fractional ownership and global liquidity, a model increasingly explored by impact-oriented investors. Field Ops and Data Integration IoT sensors, edge devices, and mobile field apps can link on-ground restoration data with digital MRV dashboards. This layer complements the emerging trend of blended climate-tech models that combine software, hardware, and local operations. By supporting start-ups that integrate these layers, Keev Capital aims to create a pipeline of investible climate solutions that can tap both global carbon markets and domestic CSR-driven demand. Why Keev Capital Sees Long-Term Value in Blue-Carbon Investing in the Blue-Carbon Premium is not just an environmental play, it is a strategic market opportunity. Rising corporate net-zero commitments and the scarcity of high-quality offsets mean that blue-carbon credits are likely to remain supply-constrained and price-resilient. Start-ups that combine restoration science, digital MRV, and scalable community engagement models will be well-positioned to capture this upside. Keev Capital’s climate thesis focuses on companies that create measurable environmental and social outcomes while building defensible revenue streams. Projects that demonstrate credible verification, local livelihood integration, and repeatable operational models align closely with our environmental-tech portfolio. Conclusion and Call to Action The Blue-Carbon Premium reflects a powerful convergence of climate science, market demand, and coastal resilience. With mangrove credits trading at triple the price of traditional forest offsets, early movers in this sector have the potential to deliver exceptional environmental and financial returns. By leveraging digital MRV, community engagement platforms, and innovative finance structures, India can become a global leader in blue-carbon markets. Keev Capital partners with start-ups and project developers, driving the next wave of high-integrity climate investments. Founders building MRV platforms, tokenised carbon solutions, or community-first restoration models can benefit from our experience in climate-tech and blended finance. Our team is ready to collaborate on creating scalable, premium blue-carbon projects that deliver both market value and measurable impact.
Micro-Insurance for Her: Building Risk Covers That Empower Rural Women
The rise of Micro-Insurance for Her is redefining how financial inclusion reaches India’s rural women. Recent insights from Women’s World Banking highlight that women holding Jan-Dhan accounts are significantly under-protected against health, livelihood, and climate shocks. Micro-insurance is emerging as a crucial lever for financial resilience, yet product penetration remains below 20% in many rural blocks. Keev Capital’s inclusive-fintech investments focus on creating embedded-insurance products that are low-cost, low-friction, and designed to scale sustainably. Why Micro-Insurance for Rural Women Matters Rural women often shoulder the highest economic risk with the least financial safety nets. Health emergencies, crop failures, and sudden income shocks can destabilize entire households. While government-led programs like Pradhan Mantri Suraksha Bima Yojana and Jan-Dhan-linked insurance have provided a foundation, uptake is still uneven. Data shows that women are 15–20% less likely than men to own active insurance policies, primarily due to limited awareness and distribution gaps. Micro-insurance tailored for rural women can reduce vulnerability and unlock new financial behaviors. Keev Capital’s perspective aligns with education-focused initiatives that emphasize literacy and digital onboarding as a core adoption driver. Embedded-Insurance APIs: The Scalable Path Forward The next wave of micro-insurance will be defined by embedded-insurance APIs. Instead of selling standalone policies, insurers can integrate coverage directly into payments, lending, and savings platforms used by rural women. For example, a micro-loan disbursed via a rural fintech app can automatically include health or crop cover, reducing opt-out friction. APIs allow seamless policy activation, premium deduction, and claims without requiring branch visits. This is particularly powerful in combination with Aadhaar, UPI, and Jan-Dhan rails, where low-CAC acquisition is critical. Start-ups using vertical AI to predict risk and automate underwriting can create stickier, higher-margin insurance offerings. AI also reduces claim-processing times, increasing trust and long-term engagement. Keev Capital’s Inclusive-Fintech Guardrails At Keev Capital, our investment thesis in micro-insurance follows a clear set of inclusive-fintech guardrails: Affordability and Accessibility Products must be priced at or below ₹200 per year for health or accident coverage to ensure uptake in low-income rural segments. Embedded Distribution Policies should be delivered through existing fintech, agri-tech, or payments platforms to minimize customer acquisition costs. Verified Impact Metrics We evaluate start-ups based on coverage-to-claims ratios, claims turnaround times, and measurable improvements in women’s financial resilience. Blended Finance Compatibility Solutions that attract donor or CSR support in the early stages can bridge operational gaps until premium pools achieve sustainability. Local Trust Anchors Partnerships with SHGs (Self Help Groups) and local health workers ensure awareness and adoption in communities historically excluded from formal insurance. Our broader thesis also looks at synergies with consumer goods and rural distribution, where trusted channels can serve as last-mile insurance educators. Building Financial Resilience at Scale Micro-Insurance for Her is not just a social good—it is a commercially viable opportunity when designed with stickiness and trust at its core. Embedded-insurance APIs lower distribution costs, improve claims efficiency, and make products truly accessible to rural women. Start-ups that master this model can transform financial inclusion while building defensible, low-CAC businesses. Keev Capital actively partners with founders who see micro-insurance as a key driver of rural financial resilience. By combining fintech rails, AI-driven underwriting, and inclusive field strategies, we can scale impact and unlock long-term profitability. Founders building products for women-centric micro-insurance can leverage Keev’s sector experience and blended-finance insights to accelerate market adoption. Our team is ready to collaborate with innovators shaping the future of inclusive fintech and rural resilience.