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  • EU Lawmakers Push Bloc-Wide Tax on Major Tech Firms and Online Gambling to Fund €2 Trillion Seven-Year Budget

    This article was generated by AI and cites original sources.

    The News

    European Union lawmakers are pressing for a bloc-wide tax aimed at major technology firms and online gambling businesses, with the stated goal of raising new revenue for the EU’s upcoming seven-year budget. As reported by Tech-Economic Times, the budget target is two trillion euros, and the measure is currently at the negotiation stage between the European Parliament and EU member states.

    A Fiscal Policy Mechanism for Technology and Gambling Sectors

    The core policy proposal is straightforward: apply an EU-wide tax to large technology companies and online gambling operators, then use the proceeds to support the next multi-year EU spending plan. The tax is directed at technology firms and online gambling businesses as a revenue tool that would affect how major digital services and platforms operate within the EU market.

    For industry observers, the most immediate relevance is that taxes can influence product pricing, compliance workflows, and corporate cost structures. While the source does not provide technical details such as how the tax would be calculated, which revenue bases would be used, or what definitions would apply to “major technology firms,” the fact that the proposal is bloc-wide suggests an attempt to reduce fragmentation across member states. Uneven or country-by-country rules can create operational burdens for companies with cross-border services.

    Budget Scale and Tax Design Considerations

    The source ties the proposal to the scale of the EU’s upcoming seven-year budget—two trillion euros. It also states that negotiations are underway between the European Parliament and member states to secure the additional revenue. This combination of large funding targets and an ongoing legislative process suggests that policymakers will likely focus on a tax structure that is both collectable and politically feasible across jurisdictions.

    From an industry perspective, the budget figure provides context for why lawmakers may be looking toward firms with large digital footprints. The source does not specify whether the tax is intended to address particular digital business models such as advertising, platforms, cloud, or gaming, but it does explicitly include online gambling businesses alongside technology firms. This pairing suggests the policy could target companies whose value is linked to online distribution and user engagement, though the source does not elaborate on the policy rationale.

    Ongoing Negotiations Between Parliament and Member States

    According to Tech-Economic Times, the proposal is not final. The article states that negotiations are underway between the European Parliament and member states to secure this additional revenue. For the technology sector, this matters because the outcome of such negotiations can determine practical implementation details. The presence of a multi-actor process typically affects timelines, compliance requirements, and the scope of covered businesses.

    In EU policymaking, member-state involvement often influences how rules are applied in practice. Even when an initiative is described as bloc-wide, the final text can shape how compliance is handled, how disputes are managed, and whether implementation is uniform across the EU. The source does not provide any indication of a target date for agreement or rollout.

    Potential Implications for Technology Operations

    Because the source offers only a high-level description, any implications must remain conditional. A bloc-wide tax on major technology firms could raise operational questions for companies that do business across the EU. For example, firms may need to assess whether they fall under the proposal’s definition of “major technology firms,” and how “online gambling businesses” would be categorized relative to other gaming or entertainment services. The source does not clarify these definitions, but such criteria typically determine whether a tax regime applies.

    This proposal reflects the ongoing pattern of governments seeking additional revenue from the digital economy. The focus here is on how the EU frames technology firms and online gambling operators as contributors to long-term public budgeting. If the negotiations result in a workable tax mechanism, it could establish a precedent for how the EU links digital-sector activity to multi-year funding plans.

    Observers may also watch for how the final policy balances revenue goals with the administrative burden on covered companies. The source does not discuss enforcement mechanisms, reporting requirements, or whether there would be exemptions or thresholds. However, the stated objective of raising funds for a two trillion euro seven-year budget suggests that policymakers will need a structure that can generate predictable collections.

    Summary

    EU lawmakers are pushing for a bloc-wide tax on major technology firms and online gambling businesses to help fund the EU’s upcoming seven-year budget of two trillion euros. Negotiations between the European Parliament and member states are underway. The details that determine how companies comply—definitions, calculation methods, and timelines—are not included in the source report.

    Source: Tech-Economic Times

  • Intel and Google Expand AI Chip Partnership to Advance CPUs and Custom Infrastructure Processors

    This article was generated by AI and cites original sources.

    Intel and Google are deepening their hardware collaboration focused on artificial intelligence compute. According to Tech-Economic Times, the companies plan to advance AI CPUs and create custom infrastructure processors, responding to a shift in AI workloads from training toward deployment. Google will use Intel’s Xeon processors and Xeon 6 chips, while the companies will co-develop processing units for more efficient computing.

    From Training to Deployment: The Shift in AI Hardware Focus

    The core technical rationale for this partnership is that AI is moving from training to deployment. Tech-Economic Times characterizes this as a growing need for generalist chips—processors that prioritize broad workload coverage over narrow, training-only design. While the source does not define “generalist” in specific engineering terms, the implication is that inference and production environments require a wider mix of compute capabilities, memory access patterns, and system-level efficiency than earlier training-focused systems.

    Deployment workloads typically run continuously across many models and variations, requiring integration into existing data center operations. This shift suggests that CPU roadmaps and system integration are becoming more central to AI infrastructure strategy, not just specialized accelerators.

    Expanding the Intel-Google Collaboration

    Per the source, Intel and Google will “advance artificial intelligence CPUs” and “create custom infrastructure processors.” The partnership encompasses both improving existing CPU families and designing custom processing units aimed at infrastructure-level efficiency.

    On the Intel side, Google will use Intel’s Xeon processors and Xeon 6 chips. This indicates that Google’s deployment targets are tied directly to Intel’s server CPU lineup. The mention of Xeon 6 suggests the collaboration aligns with a specific generation cycle, though the source does not provide technical specifications such as core counts, memory bandwidth, or interconnect details.

    On the co-development side, the companies will “co-develop processing units for more efficient computing.” The source does not specify the exact scope of these processing units or whether they are CPU variants, auxiliary accelerators, or components integrated into larger infrastructure systems. However, the phrase “more efficient computing” connects the chip work to system-wide efficiency goals—potentially related to power consumption, performance per watt, or cost per inference, though these specific metrics are not stated in the source.

    Two-Track Approach: CPUs and Custom Processors

    The partnership combines AI CPUs and custom infrastructure processors in what appears to be a two-track strategy. The first track leverages Intel’s Xeon platform for AI-related CPU workloads. The second track involves building or refining additional processing units jointly to improve efficiency for infrastructure environments.

    This approach suggests that general-purpose server CPU families will handle a broad workload set, while custom or co-developed components optimize the parts of the stack that dominate production costs. However, because the source does not describe the architecture of the custom units, deeper technical conclusions would exceed what the reporting supports.

    Google’s decision to use Intel Xeon processors—including Xeon 6—indicates the company expects value in the CPU layer for AI workloads. The source does not specify whether these processors will be used for training, inference, or both; it only states that the partnership responds to AI’s shift from training to deployment.

    Implications for Infrastructure Planning

    For infrastructure planners and technology professionals, the key takeaway is that AI hardware roadmaps are increasingly shaped by where workloads are deployed. If AI deployment is driving demand for generalist chips, then CPUs—particularly major server platforms like Xeon—may receive more direct optimization for AI-related performance and efficiency.

    The partnership also indicates that large-scale AI operators continue to influence CPU design and system integration through co-development. This suggests that future AI deployments may be more closely tuned to specific CPU generations, including Intel’s Xeon 6, rather than relying on generic compute layers.

    The collaboration reflects a response to a significant workload transition: “as AI shifts from training to deployment.” This shift affects key operational variables for data centers, including latency targets, throughput requirements, and cost structures. Intel and Google are aligning CPU and infrastructure processor development to address deployment realities.

    Source

    Source: Tech-Economic Times

  • CoreWeave and Meta expand $21 billion AI cloud capacity deal

    This article was generated by AI and cites original sources.

    CoreWeave announced on Thursday that it has entered into an expanded agreement to provide Meta Platforms with $21 billion in cloud capacity as the social media company scales its infrastructure to support increasingly complex AI workloads, according to Tech-Economic Times.

    The announcement

    CoreWeave said it has entered into an expanded agreement with Meta Platforms to provide $21 billion in cloud capacity. The deal is directly tied to Meta’s infrastructure scaling efforts as AI workloads become more complex. The agreement positions cloud capacity as a critical resource for supporting Meta’s AI operations.

    What the deal signals about AI infrastructure demand

    The size of this commitment highlights the practical mechanics of AI compute procurement—capacity planning, workload growth, and the technical supply chain behind model training and deployment. Large-scale AI systems are increasingly constrained by hardware availability and data center capacity. Deals of this magnitude are less about a single model launch and more about securing sustained compute access as workloads evolve over time.

    The reported agreement indicates that Meta expects workload complexity to rise. Capacity planning is a core engineering concern: teams must match GPU and accelerator availability, networking throughput, and storage needs to the cadence of experimentation and production rollouts. From the perspective of a cloud provider like CoreWeave, the engineering challenge is to deliver capacity that can be sustained at scale.

    Implications for AI infrastructure procurement

    The announcement underscores that major AI users are increasingly treating compute access as a strategic procurement category. A deal of this size can influence how the industry approaches capacity availability—particularly when AI workloads scale in both breadth (more models, more features) and depth (more intensive training runs, more complex inference graphs).

    For the broader AI cloud market, the reported expansion suggests that large platform operators are willing to commit substantial capital to secure compute capacity. The scale of this commitment indicates that capacity agreements may become an increasingly common mechanism for aligning AI development timelines with infrastructure constraints.

    Such agreements can also affect architecture decisions. If capacity is planned in advance, teams may design training schedules, batch sizes, or rollout strategies around expected availability. The connection between this deal and infrastructure scaling for increasingly complex AI workloads is consistent with the idea that compute provisioning can shape operational planning.

    What to watch

    The most concrete details from the announcement are the parties involved (CoreWeave and Meta Platforms), the nature of the agreement (an expansion), and the figure ($21 billion) tied to cloud capacity. The announcement also states the motivation: Meta is scaling infrastructure to support increasingly complex AI workloads.

    Industry observers may look for follow-on disclosures that provide additional technical details about the agreement. For example, information on the scope of workloads covered by the capacity—whether it is optimized for training, inference, or both—or the operational timeline for scaling would provide greater clarity on how the capacity will be deployed.

    The reported deal provides a clear signal about the direction of AI infrastructure: as AI workloads grow more complex, compute capacity becomes a major operational lever. For technologists, this matters because model performance and deployment reliability often depend on how effectively systems can scale compute resources while maintaining throughput and latency requirements.

    Source

    Source: Tech-Economic Times

  • Ola Electric Announces 46100 LFP Cell Readiness, Scales Gigafactory to 6 GWh

    This article was generated by AI and cites original sources.

    Ola Electric shares rose nearly 20% to hit the upper circuit on April 9, closing at ₹36.34 versus ₹30.29 the previous close, after the company announced on April 7 that its in-house developed 46100 Lithium Iron Phosphate (LFP) cell is ready. Alongside the battery milestone, Ola is ramping its Gigafactory capacity to 6 GWh from 2.5 GWh, while vehicles using 4680 Bharat Cells are already on the road, according to Inc42 Media.

    New 46100 LFP cell format announced

    On April 7, Ola announced its new 46100 format LFP cell, developed as part of its vertically integrated battery innovation efforts. In a statement cited by Inc42 Media, the company described the cell as “bigger than the current NMC 4680 Bharat Cell” and said it represents “a step change in scale, cost efficiency, and applicability across both mobility and energy storage solutions.”

    According to the company statement, the 46100 format LFP cell “will begin entering Ola’s products starting next quarter.” The announcement signals a planned transition path for battery hardware and pack-level engineering. However, the source does not specify which models will use the 46100 LFP cell first, nor does it provide measured performance metrics such as energy density, cycle life, or pack-level efficiency.

    Gigafactory capacity expansion to 6 GWh

    Ola is currently ramping up its Gigafactory’s capacity to 6 GWh from 2.5 GWh. The company has vehicles already integrated with 4680 Bharat Cells on the road.

    The parallel timing of cell readiness and capacity expansion suggests Ola is aligning its battery development roadmap with factory scaling. The source does not detail how Ola’s production lines will handle the transition between the “current NMC 4680 Bharat Cell” and the larger “46100 format LFP cell,” or address manufacturing constraints such as equipment utilization, formation and testing throughput, and pack line configuration.

    Market activity and investor response

    On April 9, over 42 crore shares changed hands during the session, with a turnover of approximately ₹147 crore. The company’s market capitalization stood at ₹16,029 crore (approximately $1.7 billion) at the end of the session. These figures reflect investor response to the technical milestone announced by the company.

    Battery strategy: vertical integration and cross-application use

    Ola’s April 7 statement ties the 46100 LFP cell to vertical integration and positions it for use across multiple application categories. The company stated the new cell format is “applicable across both mobility and energy storage solutions.”

    This cross-application approach could indicate a strategy to reduce fragmentation by standardizing parts of the cell ecosystem and leveraging manufacturing learning across product lines. However, the source does not confirm whether the 46100 LFP cell will be used in stationary storage products immediately, nor does it describe any energy storage system configurations. Any expectations about how quickly the technology will translate beyond vehicle packs would be speculative based on the provided information.

    Related hardware announcements: ebike PLI certification and pricing

    Earlier in April, Ola secured Production Linked Incentive (PLI) certification for its ebike Roadster X+ 4.5 kWh, confirming compliance with domestic value addition norms and making it eligible for government incentives.

    The company also reduced the price of the Roadster X+ 9.1 kWh by 31% last week. These announcements indicate that Ola’s product roadmap extends beyond passenger vehicles and that its battery and energy hardware strategy is linked to incentives and manufacturing localization. However, the source does not explicitly connect the Roadster X+ announcements to the 46100 LFP cell transition.

    What this means for EV manufacturing

    The April 9 share movement reflects investor interest in two operational developments: a new in-house 46100 LFP cell format ready for product entry “starting next quarter,” and a Gigafactory capacity ramp to 6 GWh from 2.5 GWh. Together, these steps point to a manufacturing-focused approach—develop the cell format, validate readiness, and scale output capacity in parallel.

    Industry observers may track how quickly Ola converts the “ready” cell into production volumes and whether the transition from the “current NMC 4680 Bharat Cell” to the “bigger” 46100 format affects pack integration, supply chain sourcing, and manufacturing yield. The source does not provide those downstream indicators, so the immediate takeaway is the company’s stated intention and timeline rather than confirmed field outcomes.

    Ola’s framing of the 46100 LFP cell as part of “vertically integrated battery innovation efforts” suggests the company is pursuing in-house battery development. If Ola continues to expand battery format options while scaling capacity, this could influence how the company designs its battery supply chain and standardizes components across mobility and energy storage. The extent of that impact will depend on execution details not included in the available reporting.

    Source: Inc42 Media

  • Canva Acquires Simtheory and Ortto to Expand AI and Marketing Capabilities

    This article was generated by AI and cites original sources.

    Canva, the design and content platform, has acquired Simtheory and Ortto to strengthen its AI and marketing capabilities, according to Tech-Economic Times. Both companies were founded by Chris and Mike Sharkey, who will join Canva in leadership roles to contribute expertise across the company’s marketing and other teams.

    The Acquisitions: Simtheory and Ortto

    Canva’s acquisitions of Simtheory and Ortto represent a capability expansion focused on AI and marketing technology. According to the source, both companies share common founders in Chris and Mike Sharkey. The acquisitions position Canva to integrate these entities into its broader platform strategy around AI-powered marketing and content operations.

    As part of the deal, the Sharkeys will assume leadership roles at Canva and contribute their expertise across the company’s marketing and other teams. This founder-led integration approach is common in acquisitions, as it can facilitate knowledge transfer and alignment of acquired capabilities with the acquirer’s systems and priorities.

    Leadership Continuity and Integration

    The involvement of the Sharkeys in Canva’s leadership structure suggests a structured approach to integrating the acquired companies. Retaining founders and technical leaders from acquired firms can help preserve product context and strategic direction while aligning them with the parent company’s objectives.

    The source indicates that the Sharkeys will contribute across marketing and other teams at Canva, implying that their expertise is expected to influence multiple platform components. This suggests that Canva views the acquired capabilities as applicable across several areas of its business, not just isolated marketing features.

    Strategic Direction: AI and Marketing Convergence

    The stated rationale for these acquisitions—strengthening AI and marketing capabilities—reflects a broader trend in the technology industry: the convergence of content creation tools with marketing performance workflows. Modern creative and marketing platforms increasingly need to connect asset creation with downstream distribution, targeting, and measurement capabilities.

    By acquiring Simtheory and Ortto, Canva is pursuing expansion through acquisition rather than relying solely on internal development. This approach could indicate that Canva identified gaps in its existing AI-enabled marketing stack or sought to accelerate time-to-market by acquiring established products and engineering teams.

    The acquisitions align with a broader industry pattern where design platforms and marketing technology are becoming more tightly integrated at the software architecture level, with AI serving as a connecting layer between content creation and marketing operations.

    What Comes Next

    The source provides limited details about specific features or timelines for integration. The most concrete indicators of progress will likely be organizational announcements and product roadmap updates tied to marketing and AI improvements.

    For enterprise buyers and technology observers, key questions include how Canva will integrate the acquired capabilities into its existing platform, whether AI-driven marketing features will become more tightly coupled with content creation tools, and how the leadership involvement of the Sharkeys translates into engineering priorities and product direction.

    This acquisition pair underscores how platform companies use mergers and acquisitions to expand into adjacent technical domains. Canva’s move reflects the industry trend that design and marketing are increasingly intertwined at the software architecture level, with AI acting as the connecting layer between these domains.

    Source: Tech-Economic Times

  • BlackBerry forecasts strong first-quarter revenue, cites cybersecurity and QNX automotive software demand

    This article was generated by AI and cites original sources.

    BlackBerry is forecasting strong first-quarter revenue that it expects to exceed market expectations, and the company says its turnaround is complete. In a Tech-Economic Times report published on April 9, 2026, the Canadian software firm attributes the outlook to robust demand for its cybersecurity and embedded software, with particularly strong performance from its QNX division, which supports automotive systems. The report also points to plans for increased investment and potential acquisitions—a combination that could shape how BlackBerry positions its software stack across enterprise security and connected vehicles.

    BlackBerry’s revenue outlook and strategic shift

    According to the source, BlackBerry anticipates strong first-quarter revenue that will be above market expectations. The report frames this as evidence that the company’s strategic shift is producing results. Rather than centering on hardware or consumer devices, the emphasis is on software segments—specifically cybersecurity and embedded software.

    This matters for technology watchers because it highlights a product strategy focused on two software domains: security capabilities for protecting systems, and embedded software for running software reliably in constrained environments. The source indicates that demand is robust for both areas, which suggests that BlackBerry is targeting workloads where long-term integration, compliance, and platform stability are central purchasing factors.

    Cybersecurity and embedded software demand

    The Tech-Economic Times report states that BlackBerry’s demand profile is robust for its cybersecurity and embedded software. While the source does not provide additional technical specifics—such as named products, feature sets, or customer verticals beyond the automotive link for QNX—it does establish the categories that BlackBerry is prioritizing.

    From a technology perspective, the pairing of cybersecurity and embedded software addresses both sides of system risk: the need to secure software and the need to ensure that software runs correctly in production environments. If the turnaround is complete, as the report claims, then BlackBerry’s software portfolio may be gaining traction with customers who require vendors capable of supporting both secure operations and dependable runtime behavior.

    However, the source does not disclose how much of the first-quarter revenue outlook is attributable to cybersecurity versus embedded software. What can be stated directly is that the company points to both categories as areas with strong demand.

    QNX performance and automotive software

    A key detail in the report is that BlackBerry’s QNX division—described as crucial for automotive systems—is performing exceptionally well. QNX is positioned in the source as central to automotive systems, which ties the company’s embedded software strength to the broader trend of software-defined vehicles.

    The implication for the industry is that automotive software platforms are increasingly important, and performance in that division can influence how software vendors are evaluated by automakers and suppliers. The report’s language suggests that BlackBerry’s embedded software strategy is accelerating through QNX.

    However, because the source does not provide metrics such as revenue growth rates, unit volumes, or customer counts, it is not possible to quantify the scale of QNX’s contribution from the information provided. Observers may watch for further disclosures in subsequent filings or earnings materials to understand the extent of QNX’s contribution to overall performance.

    Investment plans and potential acquisitions

    The Tech-Economic Times report states that BlackBerry is poised for further growth and mentions plans for increased investment and potential acquisitions. For a software company, this combination typically involves scaling internal development—such as expanding engineering capacity or deepening existing product areas—and acquiring capabilities that can fill gaps or accelerate time-to-market.

    Because the source does not specify which technologies or company targets are under consideration, the acquisition language should be treated as directional rather than concrete. The mention of acquisitions aligns with the idea that cybersecurity and embedded software are areas where specialized capabilities—such as security tooling, secure runtime components, or systems integration expertise—could be valuable.

    The report’s claim that the turnaround is complete could affect how the market interprets future capital allocation. If investors and customers see that the company’s strategy is translating into revenue strength, then increased investment and potential acquisitions may be viewed as steps to sustain and extend that momentum.

    Implications for technology buyers and platform strategists

    BlackBerry’s forecast and segment emphasis provide a snapshot of how enterprise and automotive software ecosystems are evolving. The source ties its outlook to cybersecurity, embedded software, and QNX performance. In practical terms, this suggests BlackBerry’s technology roadmap is focused on software layers that can be integrated into existing systems—an approach that typically requires long-cycle engineering work, ongoing support, and continued platform reliability.

    For technology buyers, the news may signal that BlackBerry is positioning its products for continued adoption in environments where security and embedded reliability are key requirements. For platform strategists, the report underscores that automotive software platforms remain a competitive arena, with QNX highlighted as a key component.

    What remains unclear from the source is the depth of technical detail behind the growth—such as which cybersecurity capabilities are seeing demand or what specific embedded software performance metrics are improving. The report’s central message is that BlackBerry expects revenue strength in the first quarter, credits its strategic shift, and points to QNX and cybersecurity as the primary drivers.

    Source: Tech-Economic Times

  • Swageazy Raises Rs 5.4 Crore in Follow-On Funding Round Led by Info Edge Ventures

    This article was generated by AI and cites original sources.

    The Funding Round

    Swageazy, an India-based corporate gifting platform, raised Rs 5.4 crore in a follow-on funding round led by Info Edge Ventures, with participation from founders of HR tech firms OnGrid and HROne. According to Entrackr, the company plans to use the proceeds to expand its product and technology teams, strengthen its sales function, and deepen its presence among enterprise clients.

    Platform Capabilities and Workflow Automation

    Swageazy provides a platform where businesses can design branded merchandise, manage inventory, automate gifting workflows, and ship orders globally. The platform’s workflow automation is tied to HR-triggered events. Swageazy integrates with HRMS tools to enable automated gifting for events such as onboarding, birthdays, and work anniversaries. This integration allows the platform to determine eligibility, timing, and recipient lists based on HR data sources.

    For enterprise customers, this kind of integration can reduce manual coordination by moving from manual gift requests to automated processes triggered by HRMS-linked events.

    Operational Infrastructure and Fulfillment

    Beyond software, Swageazy operates warehousing infrastructure across Delhi and Bengaluru and is setting up in-house printing capabilities to improve turnaround times. In-house printing affects how the platform handles order states, production timing, and quality control, with the stated goal of reducing the time between design approval and shipment.

    Swageazy currently serves over 800 enterprises, including Amazon, LinkedIn, Wipro, Coursera, and PhonePe. Serving this many enterprises typically requires reliable inventory visibility and production scheduling capabilities.

    Company Background and Growth

    Founded by Sameer Wahie and Sneh Setu, Swageazy has expanded significantly since its seed round in 2021. According to the company, it has grown 10x, expanding its enterprise client base and fulfillment network. This growth figure is self-reported by the firm rather than independently verified.

    Enterprise Software Integration as Strategy

    Swageazy’s technology stack centers on integrations and workflow automation, with a go-to-market strategy focused on enterprise clients. The combination of enterprise sales and HRMS integrations suggests a strategy where the product’s technical capabilities align with the operational needs of large organizations.

    As Swageazy expands its technology team, the HRMS integration capability may face ongoing product maintenance needs, particularly when HRMS platforms change interfaces, data schemas, or event triggers.

    Broader Enterprise Software Trends

    This funding round reflects a broader pattern in enterprise software: systems that manage people-related workflows are increasingly extending into employee experience touchpoints. Swageazy’s focus on onboarding, birthdays, and work anniversaries ties gifting to recurring HR events rather than one-off campaigns.

    The follow-on funding use—expanding product and technology teams—suggests Swageazy expects continued demand for its platform’s automation and integration features. The company is also investing in fulfillment performance through warehousing and in-house printing, which could help it meet enterprise expectations for consistent delivery timing.

    The participation of founders from HR tech firms OnGrid and HROne reinforces the connection between corporate gifting and HR technology, suggesting an ecosystem where HR tooling and employee engagement services can converge.

    Source: Entrackr : Latest Posts

  • India’s 5G scale-up targets: more than a billion 5G users by 2030 and the infrastructure stack behind it

    This article was generated by AI and cites original sources.

    India’s Union Minister of Communications, Jyotiraditya M Scindia, said the country is on track to reach over a billion 5G users by 2030, citing what he described as rapid network buildout and earlier growth milestones. Speaking at AIMA’s 11th National Leadership Conclave (as reported by mint), Scindia tied the 5G growth target to specific deployment figures—500,000 towers and ₹450,000 crore in capex—along with a broader infrastructure narrative that includes 6G, DPI infrastructure, and the United Payments Interface (UPI).

    The statement matters for technology watchers because it frames India’s telecom progress not only as consumer adoption, but as a stack of network and digital infrastructure projects—some oriented toward connectivity (5G, fibre) and others toward application-layer systems (UPI). While the remarks are policy- and program-oriented, they also point to engineering and deployment choices that determine how quickly networks can scale and how services can run on top of them.

    5G rollout metrics and the adoption curve

    Scindia’s remarks anchored the 5G target in deployment and adoption numbers. He said India had the fastest 5G rollout in the world and cited 500,000 towers alongside ₹450,000 crore worth of capex. He also described a short adoption window: in four years, 400 million consumers reached 5G.

    From there, he projected a growth trajectory: 5G consumers will go from 400 million to over a billion by 2030. In other words, the minister’s thesis is that early scale in tower deployment and capital investment can translate into a rapid expansion of end-user adoption—provided the network capacity and coverage keep pace with demand.

    For technologists, the key takeaway is that the target is tied to measurable infrastructure indicators (tower counts and capex) and a measurable user milestone (400 million within four years). Even without additional engineering details in the source, this framing suggests that India’s 5G program is being managed as a capacity-and-coverage buildout problem, not just as a service launch.

    From 4G execution to 5G scale—and a stated 6G direction

    Scindia said India “followed the world on 4G” and “marched with the world on 5G,” then added that India “will lead the world in 6G.” The source also reports that he positioned India’s digital infrastructure efforts as parallel tracks: he referenced DPI infrastructure and UPI as examples of systems that scale through both infrastructure and operational throughput.

    In telecom terms, the move from 4G to 5G is often described as a transition in radio technology and network architecture. The source does not provide technical specifications about India’s 6G plan, so any interpretation of what “lead” would mean technically would be speculative. However, his comments do indicate a narrative continuity: 5G rollout is presented as a platform for subsequent generations, with 6G framed as a future leadership objective.

    That matters because next-generation cellular rollouts depend on coordinated work across spectrum strategy, device ecosystem readiness, and network software evolution. Even without those details here, the way Scindia linked 5G to 6G implies that the industry may be expected to maintain momentum in research, standards engagement, and deployment planning while 5G adoption continues.

    The “DPI + UPI” analogy: infrastructure that scales transactions

    Beyond cellular networks, Scindia cited India’s “DPI infrastructure” and UPI as examples of infrastructure systems that can scale in operational terms. He said: “Think about it, 20 billion transactions a month. USD 3.4 trillion dollars exchanged over our UPI infrastructure.”

    These figures provide a different measurement lens than tower counts or subscriber numbers: they emphasize application-layer throughput and transaction volume. In the minister’s analogy, 5G rollout speed and 6G leadership ambition are paired with digital infrastructure capability, suggesting that connectivity and digital services are being treated as mutually reinforcing.

    For observers, the implied technology question is how these systems interact. The source does not describe technical dependencies between 5G and UPI, so it’s not possible to assert that one directly enables the other. Still, the inclusion of UPI transaction scale in the same remarks as telecom rollout metrics suggests that policymakers and industry leaders may be looking at end-to-end digital capacity: network availability, performance, and the ability of digital platforms to handle large volumes.

    Fibre connectivity, BharatNet, and the broader infrastructure framework

    Scindia also discussed connectivity infrastructure through the BharatNet program. He cited ₹1.39 lakh crore as the program’s value and said 55 per cent of the funds went toward operational expenses to maintain fibre connectivity across every village for ten years.

    This detail is technically relevant because fibre networks are not only about deployment; they require ongoing maintenance and operations to preserve performance. By highlighting operational expenses and a ten-year maintenance horizon, the source indicates an emphasis on lifecycle management rather than one-time construction.

    He also described India reaching an “inflection point” and pointed to a “3S” framework consisting of Stability, Scalability, and Strategic Autonomy. The source does not define how this framework is implemented in technical terms, but it provides a policy framing that may guide how telecom and digital infrastructure programs are prioritized.

    Separately, the minister projected a transformation for India Post into a logistics powerhouse. He said India Post recorded revenues of ₹13,280 crore in the 2024-25 fiscal and aimed for double-digit growth in the latest fiscal, with a goal to transition from a “government cost centre to a profit center by the year 2029-30.” While this is not telecom technology per se, it extends the infrastructure theme into logistics operations—areas that increasingly depend on digital systems for routing, tracking, and service delivery. The source does not provide specific technology plans for India Post, so any deeper linkage would be conjecture.

    Why the billion-user target matters for the tech ecosystem

    If India’s stated trajectory holds, the engineering challenge shifts from early rollout to sustained capacity scaling. Scindia’s cited numbers—400 million 5G consumers in four years, with a plan to reach over a billion by 2030—suggest that the network must support a growing base of users over time, not just deploy towers. The source also ties the rollout to large-scale investment (₹450,000 crore capex), which may reflect the cost profile of densification, backhaul, and spectrum-related deployment.

    At the same time, the inclusion of DPI infrastructure and UPI transaction scale in the same remarks suggests that the broader digital stack is part of the same strategic storyline. For the technology industry, this could mean that connectivity targets and digital service performance targets are being discussed together, potentially influencing how companies plan for network readiness, application performance, and operational scaling.

    Finally, the “lead the world in 6G” statement indicates that the industry may continue to monitor how quickly near-term deployment goals transition into longer-term standards and research efforts. The source does not provide a 6G roadmap, so readers should treat that as a direction rather than a detailed plan. Still, it positions 5G rollout as a step in a longer generational strategy.

    Source: mint – technology

  • Zerodha adds fixed deposits to Coin, expanding platform beyond mutual funds

    This article was generated by AI and cites original sources.

    Zerodha has added fixed deposits (FDs) to its Coin platform, enabling users to invest in FD schemes across partner banks while tracking those deposits in a single interface. According to Entrackr, the move expands Coin beyond a mutual-fund app into a platform where retail investors can manage multiple asset categories in one place.

    Fixed deposits on Coin: distribution across partner banks

    Zerodha launched fixed deposits on Coin on Thursday, enabling users to invest in FD schemes offered by partner banks and view them through the platform’s interface. Zerodha operates as a distributor for FD products provided by partner banks such as Suryoday Small Finance Bank, Utkarsh Small Finance Bank, and Unity Small Finance Bank.

    In such arrangements, platforms typically earn backend commissions from banks for sourcing deposits, while end users are not charged any fees. This keeps the offering competitive and aligned with Zerodha’s zero-cost positioning for retail investors.

    The integration adds a product type with different lifecycle mechanics than equities or mutual funds. Coin must now present FD offerings, enable investment, and maintain a consolidated view of user deposits across multiple banks. This addresses what analysts describe as “fragmentation,” where users often hold deposits across different institutions and cannot easily track them together.

    Unified interface as the core product change

    Analysts note that integrating FDs into Coin “addresses a key friction point: fragmentation. Users often hold deposits across multiple banks, making tracking difficult. A unified interface improves convenience and keeps users within the platform.”

    From a technology perspective, a unified interface requires more than a design decision. It signals that Coin is handling cross-product data aggregation and user-state management across multiple financial instruments and providers. Users can invest in FD schemes across partner banks and track their investments in one place, which means Coin must normalize deposit information into a single user experience, even though the underlying FD products originate from different banks.

    The feature is part of an effort to deepen engagement. With equities, mutual funds, and FDs in one place, Zerodha strengthens its position as a one-stop platform. Combining these asset types within one app increases the scope of what Coin must orchestrate: users should be able to move between product categories while maintaining continuity in account views and investment tracking.

    Revenue model: thin commissions, broader platform strategy

    Analysts note that FD distribution offers thin commissions and is unlikely to be a significant primary revenue driver. Instead, the feature appears to be a strategic move to capture a larger share of user savings, especially among conservative investors.

    This distinction clarifies what “product expansion” means in practice. If commissions are thin, the technology work behind FDs is likely intended to improve retention and wallet share rather than to immediately increase topline revenue.

    According to analysts, by keeping equities, mutual funds, and FDs available in one interface, Zerodha could “increase the scope to cross-sell higher-margin products like trading and derivatives.” The move could improve retention and engagement, though this represents an opportunity created by broader coverage rather than a guaranteed outcome. Still, it indicates that Coin’s expanding catalog is being treated as a pathway to connecting user behavior (saving in FDs) with other investment flows (trading and derivatives).

    Coin’s evolution and platform ecosystem implications

    Zerodha launched Coin in April 2017 as a direct mutual fund platform, and it has since evolved into a broader investment offering. This timeline situates the FD addition as another step in a multi-year shift from single-product distribution toward platform bundling.

    During FY25, Zerodha’s consolidated revenue saw a decline of 11.5% year-on-year to Rs 8,847 crore, while profits stood at Rs 4,237 crore during the same period. While this timing provides context for why a platform might pursue additional product surfaces, the FD launch appears designed to attract users more likely to prefer conservative instruments.

    Looking forward, observers may watch whether adding FDs changes how users engage with Coin over time. The larger objective appears to be “deepening user relationships,” “increasing wallet share,” and “reinforcing long-term platform stickiness” rather than driving immediate topline growth. If those goals are realized, the technical groundwork—integrating partner-bank FD offerings into a unified tracking interface—could become a template for further expansion into other savings or deposit-like products.

    Source: Entrackr : Latest Posts

  • Harshita Arora Joins Y Combinator as Youngest General Partner

    This article was generated by AI and cites original sources.

    Y Combinator has named Harshita Arora as its youngest general partner, according to Tech-Economic Times. Arora’s background includes self-taught coding, building a cryptocurrency app, and cofounding AtoB. In her new role, she will work directly with founders at every stage of their companies’ evolution.

    The Appointment and Role

    Arora’s appointment as a general partner places her in a position to engage directly with founders throughout their company development journey. As a general partner at Y Combinator, she will work with founders across all stages—from early formation through scaling. This role positions her within YC’s core mentorship structure, where partners provide ongoing guidance to portfolio companies.

    Background and Experience

    Arora’s path to the general partner role reflects diverse technical and entrepreneurial experience. She is a self-taught coder who built a cryptocurrency app and cofounded AtoB. Her background demonstrates hands-on experience in product development and technical execution, combining non-traditional coding education with practical startup experience.

    Y Combinator’s Track Record

    Y Combinator is known for backing companies including Airbnb, Stripe, and Dropbox. These companies span consumer marketplaces, payments infrastructure, and cloud storage—sectors that require careful engineering, go-to-market strategy, and scaling expertise. Arora’s addition to the partner team adds another operator with direct startup experience to YC’s mentorship network.

    Implications for the Startup Ecosystem

    Arora’s appointment as YC’s youngest general partner reflects how accelerators are recruiting partners from varied technical and entrepreneurial backgrounds. Her profile—combining self-taught development with cryptocurrency and startup experience—suggests that YC values operator experience alongside traditional credentials. This approach may influence how founders perceive mentorship access and the types of technical guidance available within the accelerator.

    As Arora begins her role, founders and observers may track how her experience shapes the mentorship and support YC provides to its portfolio companies, particularly in areas where product engineering and emerging technologies intersect.

    Source: Tech-Economic Times