Has anyone partnered with N47 and what has been your experience so far? https://www.n47.com/

Hi folks, I’m curious to know, for those of you who are limited partner partners in top-tier VCs, how are you able to invest in them? And what is the minimum you invested?

I am an LP in one tier 1 venture capital firm, but that’s it. It was based on an introduction to the GP through a mutual friend. I’d love to diversify my investments across venture. Thx

I’m curious what VC firms are still actively investing in digital infrastructure companies that are NOT hyper-scale?

I’ve talked with more than I can count and it’s either “we focus on software” or “we only focus on hyper-scale”.

We’re mature, with revenue and profit and a model that works. But it seems like a lot of brick walls.

Hey everyone! My brother and I launched Lately in Print at the end of July, and it’s been really cool to see people connect with the idea.

Lately takes the photos sitting in your camera roll and turns them into printed, editorial-style magazines. I come from a design and architecture background, and my brother is a swe, so we wanted to bring those two worlds together to make keeping your memories feel a little more intentional.

Our design team handles the layouts and composition, so you don’t have to design the magazine yourself. You just upload your photos, and we turn them into something you can actually hold onto.

We’ve grown our community organically since launching, and now we’re working on making the product even better. I’d genuinely love to hear what people think whether it’s the concept, the design, the experience, or anything that feels confusing or could be improved.

If you’re interested, you can check it out at

https://latelyinprint.com

IG: Latelyinprint

Thanks guys!!

I’m expecting a term sheet next week, but I’m not fully convinced it’s the right fit. I also have a few other investor calls lined up.

I’m building in consumer AI and would love to connect with partners at Sequoia, a16z, Lightspeed, or similar firms before making a decision.

What’s the best way to get on their radar? Open to introductions or direct conversations.

Why I built it
Funding data for private companies is mostly locked behind PitchBook (five figures a year) or Crunchbase (increasingly paywalled) based on my research. A lot of the underlying data is public anyway, from SEC Form D filings, press releases, and Reg CF offerings, but it's scattered and annoying to piece together. I wanted somewhere you could look up a company's rounds and investors without a sales call.

What it is
capbase.fyi has companies, rounds, investors, funds and people, built from SEC filings and public records. Every fact has a source attached. Code is AGPL on GitHub; data is CC BY-NC.

The catch (being upfront)
Anyone can browse, but profiles show a preview. If you contribute a fact (a round, an investor, a correction, with a source) and it's accepted after moderation, everything unlocks for 30 days. This is similar to how levels.fyi works which helps with the contribution of the community, I used levels.fyi a lot and mainly got the idea from here.

Why it's free
Hosting costs me about $40/month and I'm covering it myself.

Where it's weak right now
Coverage is skewed toward US companies that file Form D, so real estate funds are overrepresented and a lot of late-stage rounds show as undisclosed. Non-US coverage is thin.

What I'd actually like from you

• Is the contribute-to-unlock model reasonable, or would it put you off?
• What data would you need for this to replace even part of your PitchBook/Crunchbase use? I might also be out of touch since i've never had subscription to both

Been working on it for years and its still an original franchise able concept.

In 1993 I drew up a business plan and took it to my banker brother-in-law. Result not viable.

Concept was guided cycle tours in beautiful New Zealand. There are now literally 100's of cycling companies in NZ. I was to early and no capital.

Concept 2: luxury ice cream in a country ( NZ ) that only had two ice cream manufacturers in 1991. I nievely talked to a businessman in confidence and within 2 months he had a company up and running supplying a national airline.

Today I've got another idea, but im to old and lack the expertise to make it work. I want someone to take it, build it and give me a clip along the way. Seriously, its yours if you want it.

I’m currently setting up a new early-stage fund with a greenfield opportunity to design our operational tech stack from scratch.

Which CRM are you currently using?

What key connectors (to your Tech Stack) workflow automations, and MCPs are indispensable for you?

What are the biggest pain points or technical limitations you wish you could eliminate?

Would appreciate any insights!

This can be for folks in ops, portfolio, finance, or for investment.

What do you need agents the most for?

I was thinking about agents for CRM, a memo building agent, secondary research that pulls data from semrush, sensor tower, linkedin, prequin, inven for target scanning, HgI, G2.

What are some of the sites that you need monitored or portfolio documents that you need analyzed.

This will be deployed in your virtual private cloud. I am collecting information on what is the most important use case that you need.

Hi hi! I'm curious to know what your go-to networking tactic (digital or non-digital) is in instances where you want to connect with someone at an event. Particularly:

1. Some people share physical business cards. What is the most common thing that happens to the cards post-event?
2. Some people use digital business card apps or NFCs - what's the most frustrating thing about using these types of applications or in what what do you find them to be ineffective

I run and operate a manufacturing/ welding company located in Kansas City, Mo that has created a new form factor for distributed Compute across the midwest.

Submera is a cooling hardware that allows for enterprise servers( h100, b200, etc) to be deployed in rugged conditions as long as you can submerge the unit entirely underwater where it lives to be cooled by the surrounding water (pond or lake) that resides on private land (Farmers) where they wouldn't be utilizing the body of water.

-Submera removes the +$100Million dollars in over head cost for concrete building, Raised floors, HVAC, Steel roofs and structures, plumbing, coolers, etc

-No land acquisitions as the landowner retains land in exchange for 12% of monthly revenue while allowing us at submera to never have to speak to the community due to private landownership.

-Each Landowner will be limited to 7-10 units after the probationary period (1yr)

-Submera is small ( briefcase size to house the server) no sound, no moving parts, can be maintained  with removal from water. Each enclosure will have a biofouling coating to limit algae build up and corrosion resistance. 

We have already done the following: Built a prototype that tested our theory, compiled our data, leads on enterprise servers (10 servers), filed non provisional last Nov 2025, Filed our Utility Patent Aug 2026 and have filed 10 documents of the 10 families/individuals that have land and our awaiting deployment on there property.

We need funding/partnership for getting the servers (used) to build the enclosure for the enterprise servers, and built out the sites the will be deployed.

submera

i cannot seem to post images, but Jev Prime is a classifier that can talk. it has no system prompt so it's all emergent.

talk: talktojev.com
paper: zenodo.org/records/22940945
code: github.com/xucian/talktojev

What do you think of the events in general? Worth the time? Is the networking good?

As an intern, Im looking to expand network and learn more about the proceses.

Please add to this list.

The LegalTech Fund: first dedicated legaltech VC. Early-stage law firm, in-house, and consumer legal software. https://www.legaltech.com

Thomson Reuters Ventures: TR’s corporate VC for legal, tax, risk, and compliance tech. https://www.trventures.com

Andreessen Horowitz: one of the most active legal AI backers (Harvey, Eve, others). https://a16z.com

Sequoia Capital: led major Harvey rounds and other legal AI deals. https://www.sequoiacap.com

Coatue: growth investor in Harvey and other legal AI companies. https://www.coatue.com

Y Combinator: highest deal count among legal tech seed investors. https://www.ycombinator.com

Myriad Venture Partners: early-stage AI/enterprise firm active in patent, litigation, and contract tools. https://www.myriadventures.com

Lightspeed Venture Partners: frequent legal AI investor (Eve and related companies). https://lsvp.com

And what do you think makes a good memo?

Lasso is a social app connecting UK country music fans with each other through a community layer for a fast-growing but underserved music vertical.

Traction: 510 waitlist signups in the first 2 weeks, 100% UK-based, zero paid acquisition.

Market context: UK country music streaming up 40%+ since 2020, 2.5M+ active listeners, no dedicated social or community platform. Fans currently scattered across Facebook groups and generic apps.

Pre-seed round open. DM for deck.

I'm helping a friend line up a small seed round, and the drudgery first step is always the list . . . . who actually invests here, at this stage, and how big a check do they write. While doing this, I built a Claude skill that gives you a head start. I pointed it at one city (I ran Austin) to see what came back. I use NFX as the source but you can switch that up to other databases.

How it works:

I describe the round in plain language, something like "seed-stage fintech, firms that invest in Austin," and Claude runs it. Under the hood the skill pulls the public Signal by NFX investor lists and hands back structured rows: firm name, the check-size range (min, target, max) where the firm publishes one, stage, sectors, the geographies they invest in, and a profile link.

It can also return the individual investors, not just the firms.

Turns out, "VCs in my city" is a much shorter list than the raw count suggests. A big share of the firms tagged to a city invest nationally, so they turn up on almost every city's list. Once you strip those out, the genuinely local, stage-matched firms are a smaller group than I thought.

The other hiccup is check size. Only some firms publish one, so if you sort by "who writes the biggest checks" you quietly drop everyone who left it blank. I had Claude keep the blanks in their own bucket instead of throwing them away.

I'm still working on this, but it's open source, so would love your contribution here! It only knows what NFX has on those public lists. A firm that isn't on a list won't show up, and the check sizes are self-reported, so treat them as a starting point and not gospel.

The skill is free to try (MIT, setup is in the repo): https://github.com/johnisanerd/claude-skill-list-vc-firms-by-city

Not talking about OpenAI or Anthropic, those at least have a story where the whole world is the TAM, even though they might flop hard against 1-2T valuations. Im talking about the vertical AI companies for example.. Harvey at 15B on maybe 350M revenue, Clay at 7B, 40-50x sales for companies that are 4-5 years old.

Then you open the public market. Monday is at like ~4B on 1.5B revenue. HubSpot is 12-13B on 3.5B. These are companies with real GTM, thousands of salespeople, etc etc etc, and not that long ago they were growing just as fast or close to it. They're at 3x sales. The private ones are at >50x. I use to work at MNDY, we never raised by such multiples..

I get the early stage VCs, they got in early and care less about the end game as they can make their money on the secondaries, same for the founders who are already rich after round A.
What I dont get is the late stage funds writing 300M checks at these prices. What do they think is going to happen? Harvey is selling to law firms, thats not an infinite TAM, its a big one but you can do the math on it. Do they expect a 50B IPO in 2028? sure they can pivot to more markets but still..

Is all of this purely VC FOMO couple with AI hype? I can already see Late stage VCs telling LPs that the AI vintage of 2025-6 is weaker like they did for the insane covid class of 2021. They are creating a bunch of companies that can never go public or exit at their last round valuation or will need many years to get to sales that justify it.

So can someone explain it to me? These are not stupid people, so Im assuming im missing something.

I’m exploring whether or not it’s worth the trouble working at a VC? I’m in a very niche high demand knowledge domain (not AI), with a good experience working for a very notable scaleup in my field.
I wonder if switching to a VC would be worth it? I don’t know anyone with VC background. Maybe someone here could share their experience?

I'm an organic chemist with industry experience and a strong IP background. I'm not interested in being a GP, but want to know about what kind of support staff roles I might be eligible for. Do biotech VCs have scientific analysts, patent searchers, or other roles I might be eligible for?

A question, because this is the problem I have spent the last year on.

I use ChatGPT for drafting, Claude for long documents and Gemini for anything involving Google files. The result is that my history is in three places, none of them searchable in a useful way, and I regularly know I wrote something without knowing where.

What I ended up building indexes conversations locally in the browser and searches all of them at once, plus folders and export that work the same way on each. It is called AI Toolbox and version 3.0 went live on Product Hunt this morning, which is the only reason I am writing this today rather than any other day.

Mostly I am curious how other people handle this. Multiple browser profiles? Copying everything into Notion? Just accepting the loss?

https://www.producthunt.com/posts/ai-toolbox-3-0

We tracked 358,672 investor views, and had in our data set 24,541 pitch decks.

A few interesting things we found out:

• Median view: 77 seconds. The 4-minute average though which gives hope
• 16% of investors view deck less than 10 seconds
• The biggest drop in the whole deck is slide 1 → 2
• Only 44% reach the last slide.
• 26% of investors reopen a deck on a later day
• Team slide is the most viewed one
• 20% increase of views with traction in first 3 slides

Full report here (free, no gate or anything): https://www.papermark.com/fundraising-report

I have an investor operations / distro role. I came into it after 6 years across product, tech, ops, consulting. I took the role because there is a significant product function as well as distro but fuck has it been hard.

I have 3 partners, all incredibly intelligent with high standards all expecting a lot. I have a million different tasks to work on that I can never get on top of.

The standards are immense. I swear no one is allowed to slip up. I am a junior here and just feel crushing pressure. I still work like 9:00 - 5:30PM and will work a few hours on weekend to set myself up for the week.

We only have $100M under asset and are raising a $120M fund IV.

I feel insane imposter syndrome. I have leant a lot and done a lot in the 3 months without even a proper onboarding and picked up a lot of stuff but it always feels like I am behind and everyone is smarter than me.

Is this normal?

A Dentist with 8 years of experience is looking for initial investment for a Dental clinic in Mumbai, India in a specific location. The clinic will provide all modern dental treatments including implants, aesthetics and all demanding dental services. We have a detailed plan with zero risk. The investment is specifically needed for the dental space buying in a premium locality. If interested please DM, will share all the details. The amount is approx. 3 Cr. (can go up or down depending on the dental space pricing).

Bloomberg is reporting Stripe agreed to buy OpenRouter for more than $7B. The part worth chewing on for this sub is the velocity and what it implies about where AI value is actually accruing.

The facts:

• Seed/growth round valued it at $1.3B roughly 82 days ago
• Sale at $7B+ is about 5x that mark in under three months
• Founded 2023, 8M users, inference volume from $10M annualized in late 2024 to $100M+ by mid-2025
• Backers include Sequoia and a16z, so a very fast, very clean return on the last check

What makes it interesting: OpenRouter trains nothing. It is a routing layer, one API in front of 400+ models from OpenAI, Anthropic, and everyone else. The CEO framed it as "the Stripe of AI," and Stripe, of all buyers, agreed.

The thesis I keep coming back to: in AI, the model layer is commoditizing fast and the durable value is moving to aggregation and settlement. Whoever sits between all the models and controls routing, price discovery, and who gets paid captures the margin, regardless of which lab wins. That is classic aggregation theory, and it is why a payments company paid $7B for a toll booth rather than a foundry.

Two questions for the room:

1. Was the $1.3B round a mispricing, or did Stripe pay a strategic premium (defensive, distribution, IPO narrative) that a financial buyer never would? In other words, is 5x-in-82-days a signal or a one-off?
2. If the routing layer is the moat, what is the next equivalent chokepoint in the stack that is still underpriced today: eval, agent orchestration, inference settlement, something else?

Curious where people land, especially anyone who saw the last round.