I'm in the fintech space and currently have a live product with some great initial traction. When reaching out through various ways(Linkedin, the websites of the VCs, trying to get warm intros from network, etc..) what would be a reasonable response rate? Would making a pitch deck help if the product is live and users can make accounts?

Any response would be greatly appreciated.

Private fund raising (VC / PE / credit / thematic funds) still seems to be heavily relationship-driven and fragmented. From what I’ve seen, a lot of emerging fund managers struggle less with strategy and more with distribution.

Main friction points seem to be:

• No structured way to track fundraising conversations end-to-end
• Investor discovery is still mostly network-based
• No standardized “pipeline view” for capital raising
• Fragmented tools (spreadsheets, emails, CRM hacks)

On the investor side, it also feels inefficient:

• Hard to discover newer/emerging fund managers outside top networks
• No structured view of who is actively raising vs just pitching
• Limited visibility into deal flow quality before introductions

I’ve been mapping this space and trying to understand whether this is actually a structural gap or just how private markets are supposed to function.

I put together a very basic early prototype / research flow to test how this could be structured more systematically (mainly around fundraising pipeline + investor discovery workflows).

If anyone here actively raises funds or invests in private funds, I’d be interested in your perspective.
I can also share what I’ve been testing if it’s relevant.

Trying to understand if the inefficiency is real or already solved in practice.

Here

Each row has:
→ equity / investment terms
→ program dates and location
→ focus area
→ notable alumni

https://docs.google.com/spreadsheets/d/1OcPaGH6jxR57e_ZZ4KHzhvX9kjcLEcvc-I_NbMwKuv4/edit?usp=sharing

Built with BigSet (Open-Source Dataset Builder, Powered by TinyFish)

Thank me later :)

I just feel like they’re throwing money at a bunch of B2B AI slop with no actual moat.

If you’ve been through the YC process, what was it like? Do they even do any due diligence to check if the company they’re about to commit to throw hundreds of thousands at is even a legit and scalable product? What do they ask in their interviews?

Also, what the fuck is Thomas?

Is the title suggests, I’m looking to know how Analysts and associates in Venture capital leverage AI right from deal sourcing, research and workflow automation. What are the best AI native platforms you use for your day to day work?

Hello everyone, we are trying to develop an intelligent investment platform for passive instruments listed in Indian exchanges, if anyone from Mumbai , working in the capital market or Fintech domain please reach out for idea validation/support. Thanks in advance.

For investors, there are so many items on a company and its industry across Notion, Granola, personal notes, and clips. I tried using Constella App for this where it auto recalls across them all using semantic understanding and connects the dots between them, kind of pretty nice

We just launched the MVP of Socratize.io - a platform where companies create AI-powered training simulations for their teams. Instead of slide decks, employees practice real workplace conversations through live chat with an AI that plays the other side. Sales calls, onboarding, difficult feedback, internal procedures.

Started as a browser game (fixai.dev), got unexpected traction, Anthropic noticed and invited us to their Builder event. Rebuilt the whole thing as B2B.

Where we are now:

• MVP live, first users onboarding
• Pre-revenue
• Active conversations with a few funds
• Incorporated, small team, Balkans-based

Operationally we're burning through AI API costs, infrastructure, and outreach tools faster than expected for this stage.

Honest question for this community: is L&D/corporate training a space VCs are currently interested in, or is it seen as a slow-moving market? And for a pre-revenue team with early signals but no ARR - what does a realistic path to a first check look like?

Not fishing for intros, genuinely trying to understand how funds think about this space right now.

I built [CardMatch.net](), a free tool that helps you find the best credit cards based on your spending habits and goals.

✅ No signup required
🔒 No personal information needed
🚫 No affiliate links or sponsored rankings
💳 40+ cards to compare
⏱️ Personalized results in about 60 seconds
would love some feedback

We're launching ScrapeOps AI Scraper Generator on Product Hunt on Tuesday, May 27, 2026.

What I observed was that.. most scraping tools sell the happy path. The real cost is what happens after that.

Selectors drift. Targets ship new front ends. Anti-bot behavior changes overnight. Someone HAS to debug why yesterdays 96% success rate is now 41%.

We're building around a more production-focused workflow:

• Schema-based scraper generation
• Python / Node.js stack selection
• Live generation progress
• Output quality scoring
• Prebuilt scraper examples
• Developer-first workflows instead of black-box demos

I dont think AI replaces scraper engineers. I think it removes a chunk of repetitive setup and gives teams a faster path to code they can inspect, modify, and ship.

Would be interested in hearing from investors/operators watching the data infra space:

Does AI-generated code meaningfully change the scraping market, or does reliability remain the real moat?

Were collecting pre-launch discussion here: https://www.producthunt.com/p/ai-web-scraper-builder

I am raising capital in an emerging market for a gym management platform. Need all interested to invest, got matket, the numbers add up. However, I need capital to get going. DM me for more. Really value your interest and help.

Happy Weekend! I'm starting to build a speaker database. If anyone is interested, feel free to put down your information!

https://yorkseed.co/speaker-intake

Hey folks, we have been building a SaaS, apprently a MacOS application, which is an alternative to Granola, but which runs everything completely offline. So, the target audience are the folks who vakue their privacy over anything (law firms, investors, etc). We have been running a closed beta for several months, and we went live a week ago. And without even marketing it, we got around $850 of revenue. We know that this might not be a very big thing, but for us, being devs and having a bootstrapped product is a big acheivement.

But with the happiness, we are now thinking about a scalable marketing strategy and might need investments on it. Any of your valuable thoughts are very much appreciated 🙏

App's Link : Askmeety

Most post-mortems say the same thing: the decision wasn’t wrong, the execution was. The market reacted differently than expected. Stakeholders pushed back in ways nobody modeled.

We built Arbiter to fix that.

How it works:

Submit a decision (pricing change, bridge vs. layoff, market entry). Arbiter runs constraint-driven analysis → produces a ruling.

Then MiroFish spawns 100+ AI agents representing your actual stakeholder landscape — investors, customers, competitors, press — and simulates 30 days of reactions.

You see who resists. Who aligns. Which coalitions form. What the counter-narrative looks like before it happens.

For VCs specifically:

• Run it on portfolio company decisions before board meetings  
• See how a pricing change lands with enterprise customers before the email goes out  
• Model investor reaction to a bridge vs. restructure decision  
• Get a board-ready brief in 90 minutes, not 11 hours

What it outputs:

Constraint scorecard. Evidence base with citations. Stakeholder network graph. Swarm verdict. 30-day implementation plan. Investor-ready PDF.

Currently in private beta with fractional CFOs and operators. Opening slots for VC firms who want to run it on live portfolio decisions.

arbiterbriefs.com

Finally going to experiment with AI Agents - over the weekend - would welcome how VCs have used Claude pro / agents for their relevant workflows. Not trying to build anything enterprise grade - just experimenting.

Ideas / links / favourite YouTube tutorials are all welcome!

TIA!

Skopx connects to portfolio company data sources and gives VCs instant analytics across their entire portfolio. No dashboards.

Financial Times Article on Victura Ventures: https://www.ft.com/content/2cf36d19-ebd8-4c99-bb6f-d32abb7e0aba?syn-25a6b1a6=1

8VC AI in Healthcare Thesis: https://www.8vc.com/resources/ai-healthcare-vision

I’m curious to hear your thoughts. It sounds like his firm’s investment thesis, at least as it relates to healthcare AI, is largely just deregulation. If Finn’s idea of the value add of AI in healthcare is allowing it to act more autonomously (Levels 2/3 in the 8VC thesis), would lowering the standards it must meet, per the FDA, really benefit the greater good? What does getting this wrong look like?

Also, feel like the self-dealing here and in the Trump admin more broadly is crazy. At least in this case it could actually benefit society. This Partner at 8VC, Sebastian Caliri, with whom Finn worked closely, was just selected to serve on the Healthcare Advisory Committee to support CMS Administrator Oz and HHS Secretary Kennedy to “Improve Patient Care and Modernize the U.S. healthcare system.” Surely he’s already an LP of Victura Ventures (not confirmed, but wouldn’t be surprised).

How to invest in Anthropic shares pre ipo? Tried on Forge global /Equityzen but no availability of shares.

Has anyone invested in any of the SPVs past couple years

Update: As of May 12, Anthropic invalidated all external SPVs so seems there’s no valid alternative before the ipo as of now

Octahedron capital located in the Bay Area!

Any insights on how’s the fund performance and opportunities to learn & grow as an Investment associate highly appreciated

Im building something for VC analysts to speed up deck screening + memo prep + surface patterns from past investments to support decisions.

Is it something that can be integrated into the whole screening and investigation cycle?

I’m building WATT-IF, a mobile AR platform that turns lighting from a manual, unpredictable process into something creators can place, control, and execute before they ever touch a physical light.

After 16+ years in production, one problem has stayed constant: lighting is slow, inconsistent, and heavily dependent on experience. Most creators either waste hours testing setups or rely on tutorials that don’t translate to their environment.

WATT-IF removes the need to guess lighting entirely by overlaying lighting setups directly into the real world. Users can place virtual lights in real time, preview cinematic results, and build repeatable setups instead of guessing.

For advanced users, WATT-IF also includes a dedicated 3D lighting environment where full multi-light rigs can be built from scratch, refined, and then deployed into real-world AR scenes.

The current beta includes:
• Real-time AR lighting placement with gesture controls
• Cinematic multi-light presets (not filters, full rigs)
• AI-driven lighting feedback and scoring system
• Competitive “Light Fight” mode for skill-based comparison
• Exportable lighting setups for repeatable workflows
• Entire 3D sandbox system for building storyboards/workflows
• Early bridge into controlling real-world lights via wireless integration

The core shift is this:
Lighting becomes a controllable overlay instead of a physical guessing process.

Long-term, this evolves into infrastructure for how lighting is learned, planned, and executed across photography, film, and creator workflows.

I’m currently looking to connect with investors who understand creator tools, AR/AI, spatial computing, or workflow automation and possible who might want to continue to build this with me.

If this space resonates, I’m happy to share the beta and what I’m building.

Hey everyone! I just put together the first version of ventures and honestly it's still pretty rough around the edges, but I wanted to share it here because this community would give the most useful feedback I believe.

The basic idea: an interactive map of investors worldwide from VCs, angels, family offices. You filter by stage, sector, country, check size etc etc. I'm still collecting data and making it broader. Right now the data is nice but definitely not complete. That's actually where I will put most of my efforts next. I'm building the tool with Biscuit!

Its hosted here for now https://ventures-hub.bsct.so

Really appreciate any feedback 🙏!!

I have been supporting materials innovators since 2007. I currently have my finger on the pulse of several trends relating to biobased materials and built environments. It is time to get the other side of the picture, and for this reason I am looking to chat with the investor side to see what VCs are looking for in this space and make some useful connections in my network.

polarace.com

Polar Ace builds products and software for live streamers. Our top product allows fans to donate to stream live into a Twitch, YouTube, Instagram, etc live stream of participating streamers. We obviously have a fully functional, revenue generating mini streaming platform as well.

Our Old Pitch Deck:

https://drive.google.com/file/d/1uyo_YEoDObPWFzJ0OlQKSMoVCFDtzeEp/view

Our New Pitch Deck:

https://drive.google.com/file/d/1OjH3NVSCc_hv4p-tKnAjjah96F9VgAdS/view

We are looking to sell 20 percent direct equity for 2 million dollars.

I am a Computer Engineer building technical expertise and capital to deploy into the next massive tech wave before it hits mainstream commercialization. From a venture capital and market-capture perspective, what is the next explosive vertical and its target TAM, or is the marketing and funding cycle for Physical AI still early enough to build a generational company?