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VentureInsights.ai offers AI-powered investment and fundraising solutions, connecting startups and investors with deep insights. Explore our services today.

How 8vdx can help you:

Streamlines deal pipeline management.
Generates investment reports and synthesizes investment updates.
Offers benchmarking tools for your portfolio.
Facilitates Co-invest opportunities for LPs.

Why choose 8vdx: Key features

AI Powered Deal Pipeline Management and Co-Invest.
Yardstick for industry-leading insights and investment decisions.
Smart Investor Updates with standardized snapshots and historical graphs.
Comprehensive Fund and LP Management.

Who should choose 8vdx:

Angel Investors and VCs looking for streamlined investment management.
Startup founders seeking fundraising and benchmarking solutions.
Investment professionals desiring in-depth market insights and portfolio management tools.

About 8vdx

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https://www.8vdx.com/ventureinsights

Release Date

March 2024

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Three US Banks Power Research and Oversight With DiligenceVault Across Active ETFs, Private Markets, and Digital Assets

DiligenceVault chosen for its trusted data collection capabilities, AI-powered workflows, and flexibility to support research, oversight, and compliance at scale. NEW YORK, September 4, 2025 (Newswire.com) - DiligenceVault, the AI-powered manager selection and oversight platform, today announced that three major US banking institutions collectively managing nearly $700 billion in assets under management have adopted its due diligence solution. These banks alone represent approximately 20% of assets managed by US regional banks, highlighting DiligenceVault's accelerating adoption across banking and insurance sectors. The platform addresses three critical market dynamics: rapid growth in private markets, expansion of wealth management networks, and increasingly complex oversight requirements across diverse investment vehicles. By integrating AI-powered workflows with a data collection network of 17,000+ asset managers, DiligenceVault enables institutions to maintain rigorous standards while efficiently managing hundreds of managers. Modern Oversight for Wealth Management The banks selected DiligenceVault's centralized platform to modernize manager evaluation and ongoing oversight across manager research, ODD, ESG, and regulatory compliance teams. The platform helps them identify risk patterns, surface investment opportunities, and address compliance issues, enabling delivery of more sophisticated solutions and differentiated offerings to high-net-worth clients through expanding private bank and advisor networks. With automated data collection from managers, AI-powered document extraction and analysis, and customized reporting and workflows, DiligenceVault streamlines and elevates the due diligence process. "The rapid expansion of private markets and the scale of today's wealth management networks create oversight challenges that traditional processes cannot handle. These banking partnerships highlight how institutions are adopting technology not only for efficiency, but as a foundation for building resilient and forward-looking investment programs," said Bill Elcock, Head of Due Diligence and Monitoring Sales at DiligenceVault. Supporting New Structures and Market Trends The DiligenceVault platform provides comprehensive due diligence across private equity, private credit, real estate, active ETFs, evergreen funds, and digital assets, with robust monitoring to ensure adherence to fiduciary standards. This enables banks to scale advisor networks, diversify offerings, and centralize regulatory documentation, while maintaining institutional-grade oversight. "Clients choose DiligenceVault because it delivers the depth and quality of data they need, combined with the flexibility to support the entire investment office at scale. By integrating trust and AI innovation into one platform, we help banks and insurers expand fund lineups confidently while strengthening oversight for their clients," said Monel Amin, Founder & CEO at DiligenceVault. Continued Innovation, Expanding Possibilities Recent innovations at DiligenceVault include AI Autofill and extraction, the DV Assist use case that accelerates due diligence workflows; Blaze, a standard data layer; and embedded Power BI dashboards, enabling real-time oversight and analytics. These tools, combined with the platform's manager network, ensure that clients are equipped with the intelligence and scalability required to meet the next decade of investing challenges. About DiligenceVault Designed for the investment ecosystem, DiligenceVault simplifies the due diligence workflows for investors and managers worldwide. Founded in 2014, the company serves over 70,000 users in more than 150 countries. Its AI-powered platform empowers investors, asset managers, and service providers streamline due diligence, RFPs, and content workflows. Headquartered in New York, DiligenceVault has teams in Boston, Toronto, London, Melbourne, and India, combining local knowledge with a truly global platform.

Newswire

Thu, 4 Sept, 6:37 PM UTC

How AI is rewriting the playbook for investing

Cem Ötkün, CEO of Bounce Watch, offers his insider view on AI's impact on investing Founders' takes is a new series featuring expert insights from tech leaders transforming industries with artificial intelligence. In this edition, Cem Ötkün, CEO and co-founder of startup scouting platform Bounce Watch, shares his views on how AI is reshaping investing. Venture capital, once built on networks and narratives, is now undergoing a structural shift. AI is no longer a futuristic add-on to the investment process -- it's becoming an operating system. And for those investing in the opaque world of private markets, it's not optional. It's existential. The broken machinery behind the pitch Despite all the capital flowing through venture, much of the machinery remains outdated. Deal flow still relies heavily on intros. Screening is inconsistent. Diligence is time-consuming and subjective. Too often, the loudest signals win -- not the most promising ones. This inefficiency creates three core risks: * Missed opportunities, especially in under-networked geographies. * Biased capital allocation, driven by pattern-matching rather than real traction. * Time dilution, with analysts spending more time gathering data than interpreting it. AI isn't just solving these problems. It's redefining the investment stack entirely. A new architecture for decision-making The modern investment team increasingly resembles a hybrid between a research lab and a software company. Instead of asking "Who do we know?", the question is "What signals are emerging that others haven't seen yet?" AI enables this shift in several ways: * Data orchestration: Tools now unify disparate sources -- talent movement, product launches, market activity -- into coherent, queryable insight. * Micro-pattern detection: Models surface weak signals that precede big movements. Not just trends, but subtle tremors. * Process acceleration: From drafting memos to mapping competitors, AI dramatically compresses workflows. Under the hood, what's actually happening is a full rewire of the investment workflow. LLMs are being fine-tuned on deal memos and partner notes. Vector databases store historical pitch content and internal scoring data. Embeddings allow semantic queries across raw PDFs, Notion docs, and CRM logs. Agents chain these components together -- retrieving, interpreting, and acting autonomously based on firm-level rules. This isn't about replacing analysts; it's about giving them superpowers they didn't know they needed. This is leading to a fundamental redesign of what "conviction" looks like in investing. It's less about volume of meetings, and more about velocity of insight. Real-time instead of retrospective The old cadence of quarterly updates and founder calls is being overtaken by systems that observe founders in motion. Investors are now able to monitor startups as they quietly begin hiring, ship code, register domains, or test demand -- all before a polished pitch emerges. This creates two distinct advantages: Europe, in particular, stands to benefit here. Fragmented ecosystems and hidden gems across the continent are better surfaced through models than word-of-mouth. The next layer: agents and autonomy The future of investing won't be dashboards -- it will be agents. Already, we're seeing early versions of AI "copilots" assisting with research, due diligence, and document creation. But the next leap is autonomy. Agents will begin to act by: * Prioritising leads based on signal strength. * Drafting investment memos tailored to internal thesis frameworks. * Recommending follow-ups, partnerships, or even exits. This isn't science fiction. It's a logical evolution of where automation meets domain knowledge. And the most forward-thinking funds are already testing these capabilities behind the scenes. A word of caution: systems without thinking are just noise Of course, AI isn't infallible. Poorly tuned systems can amplify noise, reinforce existing biases, or produce convincing but inaccurate insights. That's why the winning model isn't machine or human. It's machine-assisted humans with strong internal logic. Teams must treat AI like a colleague: useful, but always subject to challenge. Crucially, the quality of insight still depends on the quality of the data -- and the creativity of the people asking the questions. What distinguishes the leaders? In today's landscape, advantage no longer lies in building every system from scratch. Most investment teams don't need to reinvent the wheel -- they need to integrate smarter. What sets top-performing firms apart is not in-house engineering muscle, but the ability to select, combine, and embed the right tools into their daily routines. Instead of spending months building proprietary infrastructure, they focus on refining workflows, enhancing interpretation, and freeing up time for strategic thinking. It's not about owning every layer -- it's about orchestrating what matters. The firms that excel are those that: * Seamlessly blend external intelligence into internal processes. * Adapt quickly to evolving signals and technologies. * Focus on decision quality rather than tooling pride. They don't try to be tech companies. They simply operate like intelligent investors in a tech-enabled world. The nature of investing hasn't changed. It's still about taking smart bets on uncertain futures. But the inputs -- and the speed at which we interpret them -- have changed beyond recognition. In this new era, edge doesn't come from intuition alone. It comes from infrastructure. And the firms that build it, adopt it, and refine it daily? They won't just win deals. They'll redefine what it means to be an investor.

The Next Web

Mon, 8 Sept, 6:40 PM UTC

DiligenceSquared uses AI, voice agents to make M&A research affordable

A typical merger-and-acquisition process is time consuming and expensive, even for the largest, well-staffed private equity firms. In addition to spending countless hours meeting with senior executives of potential targets and modeling financial outcomes, these groups spend millions of dollars on external advisers: accountants, lawyers, and management consultants. Since expenses for external advisers are not reimbursed if a deal falls through, PE firms wait until they are certain of their interest before engaging costly specialists such as consultants from McKinsey, BCG, or Bain to perform extensive commercial research on the market and the target company. DiligenceSquared, a startup that was part of YC's fall 2025 cohort, says that with the help of AI, it can provide top-tier consultancy-quality commercial research at a fraction of the traditional cost. The startup's co-founders, Frederik Hansen and Søren Biltoft, possess deep expertise in private equity due diligence. Hansen was formerly a principal at Blackstone, where he commissioned these reports for multiple billion-dollar buyouts. Meanwhile, Biltoft spent seven years in BCG's private equity practice leading these types of diligence efforts. Since launching in October, Hansen's and Biltoft's industry experience has helped DiligenceSquared complete multiple projects for several of the world's largest PE firms and mid-market funds, Hansen tells TechCrunch. That early traction convinced Damir Becirovic, a former Index Ventures partner, to lead DiligenceSquared's $5 million seed round out of his new VC firm, Relentless. Instead of relying on expensive management consultants, the startup uses AI voice agents to conduct interviews with customers of the companies the PE firms are considering buying. DiligenceSquared is applying the same AI-interview model seen in consumer research startups like Keplar, Outset, and ListenLabs, which in January raised $69 million at a $500 million valuation. But Hansen and Biltoft argue that their due diligence process and final outputs are fundamentally different from the consumer research produced by these startups. PE firms can pay $500,000 to $1 million for McKinsey, Bain, or BCG to interview dozens of corporate customers, including C-suite executives, and produce 200-page reports synthesizing those insights with proprietary market data, Hansen said. To ensure the quality of the analysis, DiligenceSquared involves senior human consultants who verify the accuracy and commercial insights of the final output. Since AI is doing a lot of the groundwork, the startup claims it can provide the analysis for just $50,000. "We are taking these great insights that were previously reserved for the very big decisions, and now we make them more accessible," Hansen said. Because of the lower price point, PE firms are now far more willing to engage DiligenceSquared earlier in the process, well before they have high conviction in a deal. DiligenceSquared isn't the only company trying to disrupt the diligence market. Its main competitor, Bridgetown Research, raised a $19 million Series A co-led by Accel and Lightspeed in February 2026. In addition to Hansen and Biltoft, DiligenceSquared was co-founded by Harshil Rastogi, a former Google engineer.

TechCrunch

Fri, 6 Mar, 12:00 AM UTC

Can AI Kill the Venture Capitalist?

Last fall, as venture capitalists were sinking record sums into artificial intelligence, a group of investors gathered to appraise a new startup. The company, Infinity Artificial Intelligence Institute, made software to automatically tune AI models, making them faster and cheaper. The founding team seemed strong, and the market was rapidly expanding. Half of the investors were cautious; the other half saw dollar signs. One of them dubbed the deal an "absolute banger." This startup was real, and so was the $100,000 the VCs invested in its seed round. But the VCs themselves were all AI agents, part of a new platform called ADIN, the Autonomous Deal Investing Network. Launched in 2025, ADIN uses AI to replace the human analysts involved in venture dealmaking. Put in a startup's pitch deck, and out comes a detailed analysis of its business model and founding team, a list of diligence questions and compliance risks, an estimate of the total addressable market, and a suggested valuation. ADIN has about a dozen different agentic investors, each with a distinct persona and investing thesis. The Tech Oracle looks at a startup's underlying technology; the Unit Master evaluates the financial fundamentals; the Monopoly Maker, loosely based on Peter Thiel, looks for market dominance. When the majority of the agents like a startup, they suggest how much ADIN's fund should allocate to the deal. The platform does this in about an hour, compared to the days or weeks that it takes an analyst at a VC firm. "The game of venture doesn't have a high success rate," says Aaron Wright, the cofounder of ADIN's parent company Tribute Labs. The current approach -- a kind of finger-in-the-air, gut intuition about who and what will become the great unicorns of tomorrow -- yields "home runs," where a startup returns 10x or more of the invested capital, only about 1 percent of the time. Three-fourths of venture deals don't even recover the cost of capital. As Wright sees it, AI models could significantly improve those odds. He believes venture capital is entering its moneyball era, where quantitative methods overtake human intuition, and everyone starts to hit more home runs. "Increasingly, these systems will be able to eliminate bad projects, focus on those that are more successful, and also lower the cost of operating some of these enterprises," Wright says. In a matter of years, he believes AI agents could be some of the best venture investors in the world. And when that happens? "There may be no more Sand Hill Road." Few groups of people are more bullish on AI than venture capitalists, who collectively invested more than $200 billion into the AI sector last year. Advancements in AI models have transformed the way investors think about nearly every company, in nearly every industry. Vinod Khosla, the founder of Khosla Ventures, recently predicted that AI will replace 80 percent of job responsibilities by 2030. Yet many venture capitalists seem to underestimate the extent to which AI may impact their own jobs. Marc Andreessen -- the celebrity venture capitalist and cofounder of Andreessen Horowitz -- said on an episode of his podcast, The Ben & Marc Show, that when AI is doing everything else, venture capital may be "one of the last remaining fields that people are still doing." The job is more than just writing checks, he argued; it's also choosing the right ideas, at the right time, with the right people, and then guiding them to success. "That's not science, that's art," Andreessen continued. "If it was a science, you could eventually have somebody who just dials it in and gets 8 out of 10. But in the real world, it's not like that. You're in the fluke business. There's an intangibility to it. There's a taste aspect."

Wired

Mon, 9 Mar, 9:33 AM UTC

AI-led wealthtech rising as VCs bet on a fintech disruption

As middle-income Indians increasingly diversify beyond real estate and gold into financial assets, the investment thesis is evolving. New-age startups are leveraging AI to build products at lower cost and with greater efficiency. Venture investors are betting big on artificial intelligence-driven wealth management services, which are emerging as a disruptive segment within India's fintech landscape. As middle-income Indians increasingly diversify beyond real estate and gold into financial assets, the investment thesis is evolving. New-age startups are leveraging AI to build products at lower cost and with greater efficiency. This is enabling investors with smaller asset bases to access quality advisory services that were earlier limited to high-net-worth individuals, in turn attracting venture funds to the startups catering to these so-called mass-affluent investors. "AI can be used to create personalised templates that go beyond generic robo-advisory models. Through digital platforms, these can also be distributed faster," said a partner at a US-based venture capital firm with multiple fintech investments in India. In addition, the India Stack, Aadhaar and account aggregator frameworks have made access to structured financial data cheaper and easier, further powering such offerings. Otto Money has developed an AI-powered chatbot, which helps users analyse mutual fund portfolios and also offers broader wealth management solutions. The company closed a $1.3 million funding round in February and is now exploring its next fundraise. According to two people aware of the matter, it has reached out to investors for a $10 million round to scale business. "Our primary focus remains on executing our roadmap and delivering value to users. We will raise capital at the right time to enable continued growth," said cofounder Apurv Gupta. Gurugram-based daily savings app Bachatt, competing with Jar and Gullak, is in talks to raise $12 million in a round likely to be led by Accel. The startup had raised $4 million in its first institutional funding round in April 2025. Emailed queries to Bachatt and Accel went unanswered. AI-powered credit management startup Oolka is looking to close a $12 million funding round led by Accel, ET reported on March 12. The company aims to use AI to provide customised credit management advice and help users manage indebtedness more effectively. Also Read: As banks tap AI for big tasks, local startups get a prompt What's new While wealth management has attracted investor interest over the past two years, AI is now reshaping the opportunity for early-stage startups. "Cost of serving customers has come down dramatically. This means mass-market consumers can be offered more tailored financial products, opening up a new market," said a venture capital executive. Harshvardhan Lunia, cofounder of Lendingkart, said improvements in AI-led technology have significantly enhanced service quality, enabling fintech firms to operate at lower costs while catering to a larger base. Lunia has stepped back from day-to-day operations at Lendingkart following its acquisition by Fullerton Financial Holdings. "Our engineering team is able to ship 30-40% faster due to AI tools such as Claude and Antigravity. The team is leaner and significantly more efficient," said Gupta of Otto Money. According to another investor, economies of scale are beginning to emerge with AI adoption. Wealth platforms typically earn 1-2% of revenue on assets under management, making the model viable at an AUM of around Rs 10 crore. "The economics did not work for a portfolio of Rs 50 lakh due to servicing costs. With AI, those costs have come down to a level where the model starts to make sense, though this is still evolving," the investor said. Also Read: Fintechs want to bank on agentic commerce Long way to go Despite the opportunity, founders face multiple challenges in scaling wealthtech platforms. "Advisory will not remain a moat for startups and will eventually get commoditised. The key is to drive user stickiness and move customers towards transactions beyond advisory," said a Mumbai-based wealthtech founder. Startups entering the segment will need to invest heavily in building trust and ensuring consistency in service delivery. At the same time, established players such as Groww, Ionic Wealth, Dezerv and 360 One Wealth and Asset Management are investing in AI to enhance the productivity of relationship managers and improve customer engagement. "We are advancing AI-powered pilots across key functions to drive efficiency and better decision-making, and will scale these capabilities as they mature," said Anshuman Maheshwary, chief operating officer at 360 One. Multiple forces are reshaping the wealth management landscape. While newer customer segments are opening up, incumbents are strengthening their technology capabilities. As competition intensifies, early-stage investors are betting that a new set of wealthtech firms will emerge with scalable and sustainable business models.

Mon, 23 Mar, 1:31 AM UTC

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