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49% of VC firms say tool overload is one of their biggest barriers to AI adoption. That includes many of the same firms investing in AI companies and evaluating the space every day. The problem is not that firms are ignoring AI. It is that they are adopting it in pieces. The firms seeing the strongest results are not the ones with the most tools. They are the ones building toward a connected data foundation. We wrote about what that looks like in practice, including data from our AI Sentiment Report and a conversation with Justin Hilliard of Rebel Fund on how they think about their stack.

The VC firms most confident AI will transform their operations are the same ones that built zero new workflows in the last 90 days. That's one of the findings that stuck with us most from our first AI Sentiment Report. Teams know AI matters. They're just not sure where to start, what will stick, or how to build on something that changes every month. So they wait. Meanwhile, the firms actually pulling ahead aren't the ones moving fastest. They're the ones who got specific about the problem first. We surveyed VC teams across the industry to find out where the hype ends and the signal begins. Volume 1 of the Visible AI Sentiment Report is live. Download the full report here: https://lnkd.in/d-s7bMCv

Jenny Fielding of Everywhere Ventures said something on the Thrive Through Connection podcast that stuck with us: "I don't know why investors go out publicly and say 'we're investing all the time.' No, you're not. You're not investing over the summer." Fundraising slows down in the summer. That's not a bad thing. It's an opportunity to get your head down, focus on building, and come up for air in a stronger position when fundraising heats up again. But the founders who move fastest when the window reopens aren't starting from scratch in September. They've already done the work. Helix Earth, a NASA spin-out that closed a $12M oversubscribed Seed 2 round this year, learned this lesson the hard way. In earlier rounds, there was no central tracking, no defined process, and multiple people working on the raise without clear ownership. The result was wasted time and conversations that went nowhere. Going into Seed 2, everything was built and organized before the first investor meeting. As Rawand Rasheed, PhD put it, the biggest mistakes from before were "having no process, not getting investors on the same timeline, and giving too much time to funds that were never going to invest." Use the summer to get three things in order: — Your Pipeline: A researched, prioritized list of target investors with a plan for warm intros. — Your Data Room: Built and ready to drip before anyone asks for it. — Your Investor Updates: Founders who've been sending consistent updates show up to the fall with warm relationships already in place. When the timing is right, whether that's September or sooner, you'll be able to flip the switch and pick up fundraising momentum.

Most founders wing the first raise. The best ones turn those lessons into a repeatable process. Helix Earth closed a $12M oversubscribed Seed 2 by doing exactly that. They scrapped the Google Sheets, scattered emails, and reactive follow-ups, and built a 5-stage fundraising playbook: → Prep: data room and investor list ready 6 months before kickoff → Screen: qualify investors fast, assess fit early → Diligence: organized data room + pre-built FAQ = less back-and-forth → Urgency: deliberate competitive dynamics to drive toward term sheets → Close Follow-ups were triggered by real engagement signals, not a generic cadence. Investors noticed the difference. "It turned what used to be a scattered, reactive process into something more structured and intentional." — Rawand Rasheed, PhD, Co-founder, Helix Earth Full breakdown here: https://lnkd.in/gjn7iQ_P

Most venture funds don't think of themselves as technology companies. But the best ones are starting to. We sat down with Justin Hilliard of Rebel Fund to break down how they think about build vs. buy across their entire tech stack, and the lessons any fund can apply today. Full article below:

Most portfolio benchmarking happens too late. By the time you've pulled exports and cross-referenced by stage and sector, the decision is already made. Visible's MCP server changes that. Your portfolio companies are already submitting metrics through Visible, so you can query all of it in seconds, whether you're monitoring existing investments or evaluating a new deal. In our latest video + blog, we walk through 4 prompts: → Rank every portfolio company by ARR growth and flag underperformers → Surface capital efficiency risks across burn, margin, and runway → Compare a new deal against your own portfolio at a similar stage → Stack a prospect side-by-side against adjacent companies you've already backed The benchmarks you need are already in Visible. Watch the video and read the full breakdown: https://lnkd.in/gRmPHNYe

At 20 or 30 portfolio companies, manual processes might work. At 150+, they collapse. Haatch, one of the UK's most operationally active pre-seed and seed investors, hit that wall. Data scattered across tools. No way to quickly surface which companies need attention. They needed a way to proactively support their companies at scale while keeping the personal touch. Here's how they rebuilt for scale with Visible, and what they found when the data started talking: ✅ Monthly structured data from every portfolio company ✅ Fund performance tracked across 40+ SEIS/EIS vehicles ✅ A Graduation Report built from years of real cohort data Shoutout to Aini Hashim and Sophie Weavers-Wright for sharing how they made it work Check out the full case study: https://lnkd.in/gcMheweH

How does a venture firm build their tech stack to enable better decision making? We sat down with Justin Hilliard of Rebel Fund to find out. He walked us through how they built a data-first tech stack to source, monitor, and report on 250+ companies, including their build vs. buy philosophy, LP reporting automation, and where AI is actually moving the needle. Watch the full recording here: https://lnkd.in/gSqfrqBn

We are going live with Justin in just over an hour! There is still time to save your spot here: https://lnkd.in/gey-frPc Even if you can't make it, register anyway! We'll sending the recording to anyone who registers.

Every VC firm we surveyed for the AI Sentiment Report is using AI for ops. 100% adoption. And yet only 14% say their operational efficiency has drastically improved. The gap between those two numbers has a clear explanation in the data. 41% of VC firms cite data quality as a top barrier to deeper AI adoption. Not the tools. Not the models. The foundation underneath them. It shows up in where AI is actually being used. Internal ops leads at 57%. LP reporting sits at 16%. Benchmarking portfolio performance at 8%. The lowest-utilized use cases are the ones that require your firm's data. The highest-utilized ones run on the model's existing knowledge. That is not a coincidence. It is the pattern the data reveals. Learn more below: