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Time of India
15-05-2025
- Business
- Time of India
Deeptech startups snagged $324 million in first four months of the year
ETtech Live Events The R&D-focused and innovation-anchored deeptech ecosystem, contrary to perception, is lately drawing more money—and deals. Venture Intelligence data showed investments in deeptech doubled in the first four months of 2025 to $324 million across 35 deals, compared with $156 million in the same period last year that saw 21 such of the biggest deeptech deals in 2025 included a $90 million investment in Netradyne , an AI-based fleet management platform, by Qualcomm Ventures, Point72 Ventures and others; $54 million in SpotDraft, an AI-based contract management firm, from Trident Capital and others; $35 million investment in predictive maintenance service platform Infinite Uptime by Tiger Global, GSR Ventures and $21 million in Tonbo Imaging, which offers imaging and sensor systems to military, by Florintree and broadly refers to technology-based innovation that hinges on advanced scientific and engineering research, which require significant expertise, capital and union minister Piyush Goyal 's comment on the lack of a deeptech ecosystem certainly triggered the conversation, deeptech ecosystem has been seeing increasing interest for a while Natarajan, managing partner, Mela Ventures, said that unlike a few years ago, deeptech is seeing more commercial use cases making the sector Subramaniam, managing partner, Yali Capital, which has Intel CEO Lip-Bu Tan as an advisor, said that there are more companies that are being created in deeptech now than before. This is formed by people from premier institutions and executives from multinational companies, who are choosing to stay back in the Shankar, co-founder, Java Capital, a deeptech fund, said that recent times have seen several government initiatives that attempt to grow the deeptech ecosystem in the country such as Rs 10,000 crore fund of funds to invest in deeptech and other initiatives that support semiconductors, space, and these are resulting in increased competition for deeptech deals in India.A partner from a deeptech fund told ET that they are now competing with larger players in early stage deeptech deals and are closing more as well. 'This year alone we have closed 4-5 deals at a higher valuation. We used to do 7-8 per year,' the investor Capital's Shankar said that initial investment for deeptech companies is now upwards of $4-5 million now, compared to $2-3 million a couple of years is also gaining momentum. For instance, Mela Ventures has invested along with Blume in Optimized ElectroTech, a defence technology Natarajan said that, unlike consumer technology startups, the model of investment for deeptech needs to be different as it takes a longer time to commercialise. 'If it is a 3–5-year horizon for consumer technology startups, in deeptech it requires 8-10 years. They also need intense involvement, hand-holding and mentoring to help them through the process,' he addition, one of the key challenges is also market creation. Natarajan explained that in many cases these startups are catering to the market that either does not exist or require firms to adopt a newer way. While funds like them are helping companies to reach the commercialisation stage, there is a need for intervention to drive market adoption. 'Like how the government offered subsidies for EVs (electric vehicles) there must be some incentives for customers to adopt deeptech solutions,' he added.
Time of India
15-05-2025
- Business
- Time of India
Deeptech startups raked in $324 million in first four months of this year
The R&D-focused and innovation-anchored deeptech ecosystem, contrary to perception, is lately drawing more money—and deals. Venture Intelligence data showed investments in deeptech doubled in the first four months of 2025 to $324 million across 35 deals, compared with $156 million in the same period last year that saw 21 such commitments. Some of the biggest deeptech deals in 2025 included a $90 million investment in Netradyne , an AI-based fleet management platform, by Qualcomm Ventures, Point72 Ventures and others; $54 million in SpotDraft, an AI-based contract management firm, from Trident Capital and others; $35 million investment in predictive maintenance service platform Infinite Uptime by Tiger Global, GSR Ventures and $21 million in Tonbo Imaging, which offers imaging and sensor systems to military, by Florintree and others. Deeptech broadly refers to technology-based innovation that hinges on advanced scientific and engineering research, which require significant expertise, capital and time. While union minister Piyush Goyal 's comment on the lack of a deeptech ecosystem certainly triggered the conversation, deeptech ecosystem has been seeing increasing interest for a while now. ETtech Live Events More interest Discover the stories of your interest Blockchain 5 Stories Cyber-safety 7 Stories Fintech 9 Stories E-comm 9 Stories ML 8 Stories Edtech 6 Stories Krishnakumar Natarajan, managing partner, Mela Ventures, said that unlike a few years ago, deeptech is seeing more commercial use cases making the sector attractive. Ganapathy Subramaniam, managing partner, Yali Capital, which has Intel CEO Lip-Bu Tan as an advisor, said that there are more companies that are being created in deeptech now than before. This is formed by people from premier institutions and executives from multinational companies, who are choosing to stay back in the country. Vinod Shankar, co-founder, Java Capital, a deeptech fund, said that recent times have seen several government initiatives that attempt to grow the deeptech ecosystem in the country such as Rs 10,000 crore fund of funds to invest in deeptech and other initiatives that support semiconductors, space, and biotech. All these are resulting in increased competition for deeptech deals in India. Rising competition A partner from a deeptech fund told ET that they are now competing with larger players in early stage deeptech deals and are closing more as well. 'This year alone we have closed 4-5 deals at a higher valuation. We used to do 7-8 per year,' the investor said. Java Capital's Shankar said that initial investment for deeptech companies is now upwards of $4-5 million now, compared to $2-3 million a couple of years ago. Co-investing is also gaining momentum. For instance, Mela Ventures has invested along with Blume in Optimized ElectroTech, a defence technology startup. Challenges Persist Mela's Natarajan said that, unlike consumer technology startups, the model of investment for deeptech needs to be different as it takes a longer time to commercialise. 'If it is a 3–5-year horizon for consumer technology startups, in deeptech it requires 8-10 years. They also need intense involvement, hand-holding and mentoring to help them through the process,' he explained. In addition, one of the key challenges is also market creation. Natarajan explained that in many cases these startups are catering to the market that either does not exist or require firms to adopt a newer way. While funds like them are helping companies to reach the commercialisation stage, there is a need for intervention to drive market adoption. 'Like how the government offered subsidies for EVs (electric vehicles) there must be some incentives for customers to adopt deeptech solutions,' he added.
Forbes
07-05-2025
- Business
- Forbes
The Evolution Of In-House Counsel In An AI-Driven World
Shashank Bijapur is the CEO and co-founder of SpotDraft, an AI-driven Contract Lifecycle Management Platform. getty There's something oddly humbling about spending hours reviewing a contract. I once spent six hours debating whether to use "shall" or "will." It was 3 a.m., my coffee was cold, and I thought, "This cannot be the pinnacle of legal work." At the same time, technology was transforming entire industries. I watched Elon Musk talk about autonomous vehicles—not as a possibility, but as an inevitability. It raised an obvious question: "If AI could navigate highways, detect risks in real time and make split-second decisions, why couldn't it handle legal workflows with the same intelligence?" Reclaiming Legal's Strategic Seat No lawyer dreams of becoming a human spell-checker. Yet, much of the job has become just that—measured by workload, not value. In fact, about 40% to 60% of their time is spent drafting legal documents and reviewing contracts. It wasn't the lawyers who were the problem, but the system—one overloaded with low-value, repetitive tasks that barely required legal expertise. This realization led me to find ways to help legal teams get back their time, influence and rightful place in shaping business culture. Because legal shouldn't always be catching up. It should be the one setting the pace. Changing Legal's Role I've worked with several legal teams to automate their workflows and bring efficiency to their contract lifecycles. I find that most organizations are still in the early stages of using technology to optimize contracting. They've taken the first step—adopting tools that improve efficiency—but they haven't yet transformed how legal operates within the business. Put simply: Technology is making legal teams faster, but not necessarily more influential. Data exists, but it isn't used to shape strategy. Risks are flagged, but they aren't predicted in advance. Contracts get reviewed, but they don't get structured to drive better business outcomes. That's the gap. If legal teams are going to move beyond being the last stop in a business process, they need more than just speed; they need foresight. How AI Can Give Legal A Seat At The Table I don't see AI as a tool for automation. I see it as a tool for augmentation. There's a difference. While automation speeds things up, augmentation makes them smarter. Having worked with close to 400 in-house legal teams, here are three ways I think AI can help you change the narrative: 1. Remove Bottlenecks One of the fastest ways to unlock business velocity is by automating low-risk, high-volume legal tasks. Two kinds of contracts often stand out: non-disclosure agreements (NDAs) and standard vendor agreements. These types of agreements are repetitive, template-driven and rarely require nuanced negotiation. Automating their review and approval can remove a significant chunk of the daily backlog without introducing risk. But if you want AI to actually empower your team rather than merely clearing your inbox, you need structure; you need a risk matrix that spells out when a contract can go through on its own, and when it needs a human set of eyes. You need clear escalation rules for edge cases. And most of all, you need systems that keep legal in the loop through audit trails, dashboards and the ability to intervene whenever needed. The goal is to make sure your team is steering the ship, even when you're not the ones rowing every oar. That's when the real shift begins—when legal teams stop being the people who clean up risks, and start being the people who predict, shape and guide decisions before they happen. 2. Provide Data That Legal Teams Can Use There's a paradox in legal. Legal teams are often among the leanest and most overworked in a company, yet when budgets are on the line, they're still the hardest to defend. Because legal work is invisible until something goes wrong. That's where the right use of AI makes a difference. It generates data that legal can use to help executives see and understand the true value of the function. When I help legal teams track metrics, I start simple. Focus on things like hours saved through automation, time-to-contract close before versus after intervention and the volume of routine matters handled without escalation Executives also want to see how legal is accelerating sales, mitigating risks early and helping the business move faster and smarter. For example, demonstrate how speeding up NDA approvals reduced the average sales cycle and the impact on revenue recognition. Or how early legal input on supplier contracts reduced dispute escalations by a certain percentage. When legal can frame its work in those terms, the conversation at the leadership table changes completely. 3. Create Standardized Playbooks To Streamline Future Negotiations Every extra day spent negotiating a contract is a day where revenue is stuck in limbo. I've seen deals stall for weeks—not because the terms were complex, but because both sides were caught in the cycle of redlines, approvals and legal back-and-forth. AI doesn't solve this by speeding up clicks. It solves it by surfacing patterns, such as where negotiations tend to get stuck, which fallback positions work, which terms lead to the most pushback. One of the most impactful things I've seen legal teams do is use AI to analyze historical contracts. When you can see that the majority of vendor master services agreements (MSAs) end up with the same indemnity clause, or that certain redlines never actually get negotiated, you can start building playbooks that pre-empt the friction. As a result, sales and procurement teams can move faster with legal-approved templates. Legal can then focus on high-risk exceptions instead of spending the same amount of time on every single deal. Giving Legal Teams The Chance To Rewrite AI The ones who see AI as an opportunity will work smarter, with more impact and more influence. Less time buried in approvals, more time shaping strategy. Less reacting, more anticipating. A decade ago, I sat there, exhausted, wondering if things could be different. Today, I know they can. And if a lawyer running on cold coffee at 3 a.m. can see that future, so can you. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
