IOTHYAI TECH VENTURES PRIVATE LIMITED
Integrates AI, IoT, and XR technologies for automotive, supply chain, medical, and data services.
Website: https://www.iothyai.com
Cover Block
PUBLIC
| Field | Value |
|---|---|
| Company | IOTHYAI TECH VENTURES PRIVATE LIMITED [TheCompanyCheck, September 2026 update] |
| Tagline | Integrates AI, IoT, and XR technologies for automotive, supply chain, medical, and data services. [F6S, September 2017] |
| Headquarters | Chennai, India [TheCompanyCheck, September 2026 update] |
| Founded | 2024 [TheCompanyCheck, September 2026 update] |
| Stage | Pre-Seed [F6S, September 2017] |
| Business model | B2B [F6S, September 2017] |
| Industry | Deeptech [F6S, September 2017] |
| Technology | AI / Machine Learning [IoTHyAI] |
| Geography | South Asia [TheCompanyCheck, September 2026 update] |
| Founding team | Abeneth S. Ramachandran, Vijay Subramanian, Yukti Makkar [F6S, September 2017] |
| Funding label | Undisclosed [F6S, September 2017] |
Links
Public sources
Executive Summary
PUBLIC IoTHyAI Tech Ventures is a newly incorporated Chennai deeptech company that positions itself at the intersection of AI, IoT, and XR, and it merits investor attention because the team appears to be aiming at complex industrial and healthcare workflows rather than a narrow software feature set [TheCompanyCheck, September 2026 update] [F6S, September 2017] [IoTHyAI, retrieved 2024]. Public records indicate the company was incorporated on 13 June 2024, while its outward-facing materials describe a services-led model spanning software development, artificial intelligence, connected-device systems, and XR design for sectors including automotive, supply chain, medical, pharmaceutical, and biomedical applications [TheCompanyCheck, September 2026 update] [F6S, September 2017] [IoTHyAI, retrieved 2024].
The current differentiation, based on public evidence, is less a single packaged product than an integration thesis: combining sensor-led IoT systems, AI and data engineering work, and immersive design capabilities for industry-specific deployments [IoTHyAI, retrieved 2024] [F6S, September 2017]. That can be commercially useful if customers want one technical partner across hardware-adjacent systems, analytics, and interface design, but the public record does not yet show named customers, repeatable productization, or deployment scale [IoTHyAI, retrieved 2024] [F6S, September 2017].
The team is the most concrete reason to keep the company on the radar. Abeneth S. Ramachandran is described in public profiles as having more than 15 years of experience in product development, project management, and IoT and AI implementation, while Vijay Subramanian's background includes senior analytics and transport roles, including former Chief Analytics Officer at Rent The Runway and CEO of Passenger Rail Systems at Titagarh Rail System Ltd. [Abeneth S Ramachandran - LinkedIn, retrieved 2026] [Abeneth S Ramachandran - Topmate, retrieved 2026] [Bloomberg Markets, retrieved 2026] [Forbes, August 2014]. Yukti Makkar is listed as part of the founding team on F6S, and ZoomInfo identifies her as a Program Director, Product Management at IBM, although the operating nature of her role at IoTHyAI is not independently established in the available public material [F6S, September 2017] [ZoomInfo, retrieved 2026].
On capital, the company looks early and lightly financed. F6S describes IoTHyAI as bootstrapped and links it to AIC T-Hub SpaceTech Program Cohort 2, while company-data records report authorised and paid-up capital of ₹1 lakh each; no confirmed external funding round, lead investor, or valuation was identified in the cited sources [F6S, September 2017] [TheCompanyCheck, September 2026 update].
Over the next 12 to 18 months, the key question is whether IoTHyAI can turn a broad cross-domain technical pitch into evidence of commercial repeatability, whether through named customer wins, a clearer flagship product, or a more visible funding base [IoTHyAI, retrieved 2024] [F6S, September 2017]. The early signs are directionally interesting, particularly the blend of enterprise analytics, IoT, and XR backgrounds, but the evidence base remains thin and still leans heavily on company-authored descriptions rather than independent operating proof [IoTHyAI, retrieved 2024] [F6S, September 2017] [TheCompanyCheck, September 2026 update].
Company-stated, unverified -- Core company existence and incorporation details are corroborated by company-data records, but product scope, traction framing, and most operating claims in this section rely primarily on company-authored sources and directory profiles.
Taxonomy Snapshot
| Axis | Value |
|---|---|
| Stage | Pre-Seed |
| Business Model | B2B |
| Industry / Vertical | Deeptech |
| Technology Type | AI / Machine Learning |
| Geography | South Asia |
| Founding Team | Co-Founders (3+) |
| Funding | Undisclosed |
How the Company Got Here
PUBLIC
IOTHYAI TECH VENTURES PRIVATE LIMITED appears, first and most concretely, as a newly incorporated Indian private company rather than a venture with a long public operating record. Corporate records cited by TheCompanyCheck place the company in Chennai, India, and show incorporation on 13 June 2024 under the name IOTHYAI TECH VENTURES PRIVATE LIMITED [TheCompanyCheck, September 2026 update]. The same source identifies Abeneth S. Ramachandran, Subramanian Arumugalakshmi, and Subramanian Vijay as directors, and reports authorised and paid-up capital of ₹1 lakh each [TheCompanyCheck, September 2026 update].
The public company description is broad and services-led. On F6S, IoTHyAI describes itself as combining AI, IoT, and XR technologies, with offerings across software development, artificial intelligence, Internet of Things, and XR design [F6S, September 2017]. On its own website, the company frames its IoT work around machine design, product development, sensor intelligence, supply-chain logistics, asset management, and patient-care applications, while its AI/ML page lists customized data-science, data-engineering, ETL, predictive, and operational solutions for sectors including automotive, supply chain, healthcare, pharmaceutical, biomedical, and data services [IoTHyAI, retrieved 2024].
The milestone trail visible in public sources is still short, which is typical for a company incorporated in 2024. The earliest operating signal in the materials provided is the company's web and directory presence describing a cross-functional AI, IoT, and XR services platform [F6S, September 2017] [IoTHyAI, retrieved 2024]. A later ecosystem marker is its listing in AIC T-Hub SpaceTech Program Cohort 2 on F6S, although that should be read as program participation rather than confirmed equity funding [F6S, September 2017].
Company-stated, unverified -- This section relies on one company-data source for legal status and capital, plus company-controlled profile pages for business description and milestones [TheCompanyCheck, September 2026 update] [F6S, September 2017] [IoTHyAI, retrieved 2024].
Product and Technology
MIXED Product and Technology
IoTHyAI’s public product story is still better read as a services stack than as a clearly defined software SKU. On its F6S profile, the company says it combines AI, IoT, and XR across software development, artificial intelligence, Internet of Things, and XR design services [F6S, September 2017]. The company website narrows that into two visible operating buckets: IoT systems and AI/ML solutions, with use cases spanning machine design, product development, sensor intelligence, supply-chain logistics, asset management, and patient-care applications [IoTHyAI, retrieved 2024].
The AI/ML materials point to customized data science, data engineering, ETL, predictive, and operational solutions, aimed at automotive, supply-chain, healthcare, pharmaceutical, biomedical, and data-services customers [IoTHyAI, retrieved 2024]. The evidence supports a cross-functional integration pitch, but it does not yet establish a named flagship product, a verified demo, or a customer deployment disclosed on the public record [IoTHyAI, retrieved 2024] [F6S, September 2017]. That matters because the technical differentiation, at least from public sources, appears to rest on implementation breadth across connected hardware, analytics, and immersive interfaces rather than on one plainly packaged platform.
A limited XR thread is visible through founder background rather than through a published product spec. Abeneth S. Ramachandran’s founder profile says he managed augmented- and virtual-reality technical teams across Europe, the Middle East, and Asia [F6S]. Separately, a LinkedIn profile references his work in immersive plant layout and industrial design using virtual reality, which is directionally consistent with the company’s XR positioning but remains indirect evidence of current company productization [LinkedIn, retrieved 2026].
Company-stated, unverified -- Core product descriptions rely primarily on company-controlled sources, with only partial contextual support from third-party profiles.
Where the Demand Sits
PUBLIC The market matters now because IoTHyAI is positioning across three budgets that remain active even in a cautious spending environment: industrial digitization, enterprise AI software, and sector-specific engineering services, especially where customers are trying to connect physical operations with data-driven decision tools [IoTHyAI, retrieved 2024] [F6S, September 2017].
The first point to keep straight is that no third-party market size specific to IoTHyAI's exact category was provided in the source set. Public materials describe a services-led mix of AI, IoT, and XR aimed at automotive, supply chain, medical, pharmaceutical, biomedical, and data-services users, but they do not tie that positioning to a defined procurement segment or a cited TAM/SAM/SOM framework [IoTHyAI, retrieved 2024] [F6S, September 2017]. In practice, that means the addressable market is best understood as a composite of adjacent enterprise technology budgets rather than a single clean category.
That composite matters because the company is not presenting as a single-product vendor. Its public pages point to custom data science, ETL, predictive workflows, sensor intelligence, asset management, patient-care applications, and XR design work, which suggests exposure to project-based transformation spend as much as to recurring software budgets [IoTHyAI, retrieved 2024]. For investors, the implication is straightforward: market breadth is real, but near-term sales comparability is harder because demand can come from consulting-style mandates, prototype programs, or embedded technology integrations rather than one standard software line item [IoTHyAI, retrieved 2024] [F6S, September 2017].
Adjacent market evidence
Because no direct third-party TAM for IoTHyAI was supplied, the most defensible public view is through analogous markets that overlap its stated product surfaces and end sectors.
| Analogous market | Public relevance to IoTHyAI | Cited evidence |
|---|---|---|
| Automotive technology and analytics | The company explicitly targets automotive use cases in both its IoT and AI/ML materials, and one founder's public background is concentrated in automotive analytics and compliance [IoTHyAI, retrieved 2024] [Bloomberg, December 2020] | IHS Markit projected 83.4 million global light vehicle sales in 2021, a data point that reflects the scale of the automotive operating environment rather than IoTHyAI's market share opportunity [Bloomberg, December 2020] |
| Supply chain and operations analytics | The company cites supply-chain logistics, operational solutions, and asset-management applications, placing it near enterprise operations software and industrial digitization budgets [IoTHyAI, retrieved 2024] | Vijay Subramanian was profiled by Forbes in connection with building the operational analytics stack at Rent the Runway, which is relevant to this adjacent demand area [Forbes, August 2014] |
| Space and applied research programs | The AIC T-Hub SpaceTech cohort listing and a 2025 conference appearance suggest at least some adjacency to research-led and aerospace-linked innovation programs rather than only commercial enterprise IT spend [F6S, September 2017] [Utah State University Digital Commons, August 2025] | The Utah State University conference record places Abeneth Ramachandran in a 2025 Small Satellite Conference context, which is evidence of thematic adjacency, not a revenue market estimate [Utah State University Digital Commons, August 2025] |
The small set of public signals points to a market thesis built around convergence. Enterprises in automotive, logistics, and healthcare increasingly buy combinations of sensors, analytics, workflow software, and visualization tools, particularly when the buying problem is operational rather than purely IT-led [IoTHyAI, retrieved 2024]. That is consistent with IoTHyAI's own language, but it remains a company-stated positioning claim until customer budgets or deployments are independently visible [IoTHyAI, retrieved 2024].
The clearest demand drivers in the record come from operational complexity and regulatory pressure. On the automotive side, public commentary tied to Vijay Subramanian's prior work at IHS Markit centered on fuel economy compliance and the industry's need for a substantial shift toward battery and plug-in hybrid vehicles, which underscores why automakers and suppliers continue to invest in data, forecasting, and systems integration tools [Forbes, August 2018] [Bloomberg, December 2020]. On the supply-chain side, the company's own emphasis on logistics, asset management, and predictive workflows aligns with a broader enterprise need to make physical operations more measurable and responsive, though the sources here do not provide a quantified sector growth rate [IoTHyAI, retrieved 2024].
There are also adjacent and substitute markets that cut both ways. A customer looking at IoTHyAI's offering could allocate spend to traditional IT services firms, industrial automation vendors, specialist analytics consultancies, or internal engineering teams instead of a cross-domain startup. The company's public framing suggests that its appeal would rest on integrating AI, IoT, and XR in one engagement rather than competing solely on a lowest-cost software-development mandate [IoTHyAI, retrieved 2024] [F6S, September 2017]. That can widen the opportunity set, but it also means the company may face procurement comparisons across several categories at once.
From a regulatory and macro perspective, the public evidence is strongest in automotive and weakest elsewhere. Automotive compliance, emissions, and efficiency requirements have historically supported spending on analytics and systems planning, as reflected in Subramanian's cited industry commentary and IHS Markit's market outlook through Bloomberg [Forbes, August 2018] [Bloomberg, December 2020]. In healthcare and biomedical settings, the company's claimed relevance is plausible given its references to patient care and biomedical applications, but the source set does not include regulatory clearances, hospital deployments, or medical-device partnerships, so those verticals should be treated as target markets rather than established beachheads [IoTHyAI, retrieved 2024].
The main analytical takeaway from the table is that IoTHyAI appears to sit at the intersection of several real spending pools, but the public record still does not anchor that intersection to a measurable served market. That is not unusual for a 2024-incorporated company, though it does mean market attractiveness is easier to argue than present-day capture.
Company-stated, unverified -- This section relies primarily on company materials and a limited set of adjacent third-party sources; no direct third-party TAM/SAM/SOM for the company's specific category was provided.
Competitive Landscape
MIXED IoTHyAI is positioned less as a single-product vendor than as a cross-domain engineering and services shop, which means its real alternatives are likely to be a mix of industrial integrators, AI consultancies, and XR development firms rather than one direct, named peer in the current public record [F6S, September 2017] [IoTHyAI, retrieved 2024] [TheCompanyCheck, September 2026 update].
The public evidence points to three adjacent competitive lanes. In IoT and industrial systems, the company describes work in machine design, sensor intelligence, asset management, supply-chain logistics, and patient-care applications, which places it near established systems integrators and device-to-software engineering firms that already serve manufacturing, logistics, and healthcare accounts [IoTHyAI, retrieved 2024]. In AI and data work, its stated offerings in data science, data engineering, ETL, predictive, and operational solutions overlap with a crowded field of analytics consultancies and enterprise software service providers [IoTHyAI, retrieved 2024]. In XR, the overlap appears to be with specialist immersive-design studios and industrial visualization vendors, particularly where plant layout, training, or design simulation matter, although the company has not publicly named packaged products in that lane [F6S, September 2017] [LinkedIn, retrieved 2026].
That positioning creates breadth, but it also means the company competes against substitutes with very different sales motions. An automotive or rail customer could buy a full-stack transformation program from a large incumbent integrator, contract a narrower AI team for forecasting or compliance workflows, or use an XR-focused studio for visualization and design tasks. IoTHyAI's public materials suggest it is trying to win where those budgets intersect, especially in industrial and regulated environments, but the current record does not show named customers, production deployments, or channel partners that would establish share in any one lane [IoTHyAI, retrieved 2024] [F6S, September 2017].
The clearest edge visible today is talent adjacency rather than distribution or capital. Vijay Subramanian's public background spans analytics at Rent the Runway, automotive work at IHS Markit, and rail leadership at Titagarh Rail System Ltd., which at minimum suggests exposure to data-intensive operations and industrial end markets [Bloomberg Markets, retrieved 2026] [Bloomberg, December 2020] [Forbes, August 2014] [Forbes, August 2018]. Abeneth S. Ramachandran's profiles point to long experience in product development, project management, IoT and AI implementation, and some XR-related work, which fits the company's stated multi-technology pitch [Abeneth S Ramachandran - LinkedIn, retrieved 2026] [Abeneth S Ramachandran - Topmate, retrieved 2026] [F6S, September 2017]. That edge is real if buyers are selecting for senior operator expertise across analytics, industrial systems, and immersive interfaces. It is also perishable, because services-led differentiation tends to rest on founder time until it hardens into repeatable products, references, or proprietary datasets, none of which are publicly demonstrated here [IoTHyAI, retrieved 2024] [F6S, September 2017].
The company appears most exposed where scale, procurement history, and installed-base access matter more than interdisciplinary skill. A larger systems integrator with existing vendor approval inside automotive, logistics, or healthcare accounts would likely have an advantage in enterprise procurement, implementation depth, and post-deployment support. An AI consultancy with a tighter category focus could also outcompete on specialization if the buyer only wants forecasting, ETL modernization, or decision-support tooling rather than a bundled AI, IoT, and XR engagement [IoTHyAI, retrieved 2024]. The absence of named competitors in the source set limits direct company-by-company benchmarking, but the broader pattern is clear enough: IoTHyAI's challenge is not proving that these markets exist, it is proving that a young, broad-scope firm can compress multiple vendor categories into one credible buying decision [TheCompanyCheck, September 2026 update] [F6S, September 2017].
Over the next 18 months, the most plausible competitive scenario is bifurcation. If customers increasingly prefer integrated pilot programs that combine sensors, analytics, and visualization under one technical lead, IoTHyAI could win small to mid-sized project work on speed and founder-led execution, with Vijay Subramanian the most visible public signal for enterprise credibility in data-heavy sectors [Bloomberg Markets, retrieved 2026] [Forbes, August 2014]. If, instead, enterprise buyers continue to unbundle these budgets and route them through incumbent procurement frameworks, the likely loser is the broad service bundle itself, because each workstream can be picked off by a more established specialist with references in that exact function. On the present evidence, the company's competitive position is interesting but still formative, and the durability question remains open until public proof points move beyond capability descriptions into customer adoption [IoTHyAI, retrieved 2024] [F6S, September 2017] [Utah State University Digital Commons, August 2025].
Company-stated, unverified -- This section relies heavily on company-described capabilities from IoTHyAI's public materials and directory profiles, with partial corroboration on founders and corporate status from Bloomberg, LinkedIn-profile sources, and TheCompanyCheck.
Opportunity
PUBLIC
If execution holds, the prize here is not a narrow dev shop outcome but a chance to become a specialist systems integrator for industrial and regulated sectors that need AI, connected devices, and immersive workflows to work together in one deployment stack [IoTHyAI, retrieved 2024] [F6S, September 2017].
The headline opportunity is relatively clear even if the evidence base is still thin. Public materials describe a company spanning AI/ML services, IoT systems, and XR design, with stated focus areas in automotive, supply chain, healthcare, pharmaceutical, and biomedical settings [IoTHyAI, retrieved 2024] [F6S, September 2017]. That matters because many enterprise buyers in those sectors do not buy a single model or sensor in isolation, they buy a workflow that links physical operations, analytics, and operator interfaces. If IoTHyAI can package that multi-layer capability into repeatable deployments, the reachable upside is to become a cross-functional technical partner for a small set of high-value industry use cases rather than a generic software contractor. The background of co-founder Vijay Subramanian in analytics, automotive, and rail operating environments makes that path more reachable than a blank-sheet startup story would suggest [Bloomberg Markets] [Forbes, August 2014] [Bloomberg, December 2020].
The near-to-medium term scale paths are better understood as scenario branches than as a single linear plan. The public record does not yet show customers, revenue, or a flagship product, so the opportunity rests on whether the company can convert broad capability claims into one repeatable commercial wedge [IoTHyAI, retrieved 2024] [F6S, September 2017].
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Industrial workflow wedge | The company wins one or two anchor projects in automotive or supply-chain operations, then standardizes those deployments into a repeatable offering that combines sensors, analytics, and operator interfaces | A category-tipping reference deployment in automotive or logistics, sectors the company already names as targets [IoTHyAI, retrieved 2024] | The public product surface already spans machine design, sensor intelligence, logistics, and predictive or operational AI, which fits a workflow-level sale rather than a single feature sale [IoTHyAI, retrieved 2024] [IoTHyAI, retrieved 2024] |
| Regulated care systems path | The company turns its patient-care, healthcare, pharmaceutical, or biomedical positioning into monitoring or decision-support tools for care and lab environments | A partnership or pilot that validates one healthcare or biomedical use case the company already markets toward [IoTHyAI, retrieved 2024] | Healthcare and biomedical are explicitly named in both the IoT and AI/ML offerings, which at least shows intentional sector targeting rather than a later adjacency claim [IoTHyAI, retrieved 2024] [IoTHyAI, retrieved 2024] |
| Space-tech adjacency platform | The company uses its AIC T-Hub SpaceTech program participation and Abeneth Ramachandran's 2025 conference affiliation to build a differentiated niche around frontier engineering applications | Program-to-partner conversion or a technical collaboration emerging from the space-tech ecosystem [F6S, September 2017] [Utah State University Digital Commons, August 2025] | The evidence does not establish revenue here, but it does show ecosystem access and research-facing credibility that could matter in early deeptech customer acquisition [F6S, September 2017] [Utah State University Digital Commons, August 2025] |
What compounding could look like is straightforward in theory, even if it is not yet visible in operating metrics. A first deployment in a target vertical can create domain data, implementation know-how, and buyer trust that lower the cost of landing the next customer in the same workflow. That dynamic is especially relevant when the company is selling integrated stacks, because each implementation can deepen switching costs across hardware configuration, data pipelines, predictive models, and user experience layers [IoTHyAI, retrieved 2024]. The public signals that this flywheel could form are early but coherent: the company is already presenting itself as multi-disciplinary across AI, IoT, and XR, and it has at least one ecosystem foothold through AIC T-Hub's SpaceTech Program Cohort 2 [F6S, September 2017].
The size of the win cannot be bounded tightly from public evidence because there is no confirmed market sizing, no disclosed revenue, and no clean public comparable tied directly to this exact stack. Even so, the upside case can still be framed concretely. If the industrial workflow wedge scenario plays out, the company could plausibly mature into a niche, high-value engineering software and systems business serving a handful of large sectors it already targets, including automotive and supply chain [IoTHyAI, retrieved 2024]. On a scenario basis, not a forecast, that would support venture-scale value if it develops from custom work into repeatable platforms with reference deployments and recurring contracts. The gap between today's evidence and that outcome remains wide, but the combination of multi-stack technical positioning, relevant operator background, and sector breadth is enough to keep the upside case live [Bloomberg Markets] [IoTHyAI, retrieved 2024] [F6S, September 2017].
Company-stated, unverified -- This section relies heavily on company-described capabilities from IoTHyAI's public materials and F6S, with limited independent corroboration beyond corporate records, founder background references, and a conference listing.
Sources
Public sources
[TheCompanyCheck, September 2026 update] Iothyai Tech Ventures Private Limited | https://www.thecompanycheck.com/company/iothyai-tech-ventures-private-limited/U74909TN2024PTC171030
[F6S, September 2017] ioTHyAi Tech Ventures Pvt. Ltd. | https://www.f6s.com/company/iothyai-tech-ventures-pvt.-ltd
[IoTHyAI, retrieved 2024] IoT Systems | https://www.iothyai.com/services/iot-systems/
[Abeneth S Ramachandran - LinkedIn, retrieved 2026] Abeneth S Ramachandran | LinkedIn
[Abeneth S Ramachandran - Topmate, retrieved 2026] Abeneth S Ramachandran | Topmate
[Bloomberg Markets, retrieved 2026] Vijay Subramanian, Rent The Runway Inc: Profile and Biography | https://www.bloomberg.com/profile/person/17638717
[Forbes, August 2014] How Mixing Data And Fashion Can Make Rent The Runway Tech's Next Billion Dollar Star | https://www.forbes.com/sites/stevenbertoni/2014/08/20/how-mixing-data-and-fashion-can-make-rent-the-runway-techs-next-billion-dollar-star/
[ZoomInfo, retrieved 2026] Yukti Makkar | ZoomInfo
[F6S] F6S founder profile | https://www.f6s.com/member/abeneth-s-ramachandran
[LinkedIn, retrieved 2026] Anishka Nambiar - Alchemy Bureau | LinkedIn | https://www.linkedin.com/in/anishka-nambiar-84931735b/
[Bloomberg, December 2020] Global Auto Sales Expected to Gain Momentum Next Year; 83.4 Million Light Vehicles to Be Sold In 2021, According to IHS Markit | https://www.bloomberg.com/press-releases/2020-12-17/global-auto-sales-expected-to-gain-momentum-next-year-83-4-million-light-vehicles-to-be-sold-in-2021-according-to-ihs-markit
[Utah State University Digital Commons, August 2025] Review of Microgravity Biotechnology for Space Applications … | https://digitalcommons.usu.edu/smallsat/2025/RA-S3-2025/4/
[Forbes, August 2018] Europe Automakers' Fuel Economy Failure Could Cost More Than $16 Billion, Report Claims | https://www.forbes.com/sites/neilwinton/2018/08/06/europe-auto-makers-fuel-economy-failure-could-cost-more-than-16-billion-report-claims/
[Bloomberg Markets] Vijay Subramanian, Titagarh Rail System Ltd: Profile and Biography | https://www.bloomberg.com/profile/person/24492496
Articles about IOTHYAI TECH VENTURES PRIVATE LIMITED
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