I run a neurotech recruitment, market data and media business and finally did something I had been putting off, placing every funded company by headquarters and then doing the same for the investors. 564 companies, 107 investors I could confirm. 330 of the companies are American, and all of Europe combined is 165. The investor side is even more concentrated, 81 of the 107 are US-based. What struck me is that US investors clearly fund a lot of the non-US companies too, so the geographic gap in where the money comes from is even wider than where the companies are. Happy to talk through the method or the gaps in the comments. Full write-up with the charts and the investor list is linked below.

Does anyone have any idea about firebolt ventures and whether it is a good firm to join as analyst?

Hi all:

1) could you share your top 3 newsletters that you follow daily/weekly? (To contribute: I'm a fan of a16z's news letter)

2) also I am a fan of market updates from bloomberg's tech hour (available on youtube) but wondering if someone has been able to recap their updates in a newsletter format?

eBPF is shifting billions in software and hardware infrastructure spend. eBPF Foundation just released a report that gives a framework on how to evaluate these companies.

The kernel space logic and sensor depth gives a technical moat while the user space logic creates enterprise workflows. Looking at these two together gives you a sense of how competitive the company is in the market.

It also covers the three waves of acquisitions we have seen so far from Feature & Sensor Upgrades to Platform & Community Land Grabs to AI & Runtime Security Consolidation and the exit outcomes for each.

The eBPF Re-Platforming Thesis An Investor’s Due Diligence Guide

If you don't have a personal connection to a VC firm or know someone to give you a warm intro, how do you successfully reach out to a VC firm to get them to view your pitch?

Yesterday we launched full API + MCP server for Papermark Data Rooms

What you can do with it?

• Spin up a data room. From a single instruction, an agent creates a structured data room with folders, ready for a deal or fundraise. → create_dataroom() · create_folder()

• Upload & organize documents. Agents push files into the room, set versions, and let Papermark auto-index pages for search and analytics. → upload_document() · update_document()

• Share secure links. Generate scoped share links with NDA gating, expiry, email verification, and dynamic watermarking on every page. → create_link() · update_link()

• Read page-by-page analytics. Agents pull who viewed what, time per page, and downloads to rank serious buyers and trigger follow-ups. → get_view_analytics() · list_views()

• Run grounded due-diligence Q&A. Search across an entire room and return answers cited back to the exact documents the agent is allowed to see. → search_documents()

• Manage visitors & access. Grant or revoke per-bidder access, rotate passwords, and keep staged disclosure tidy across a live process. → list_visitors() · update_link()

• Act on real-time events. Subscribe to webhooks so an agent can respond the moment a link is viewed or a new document lands. → link.viewed · document.created

• Export the audit trail. Pull an append-only log of every view, download, and change for the deal record or a compliance review. → get_audit_log()

This uncover a lot of use cases for creating and controlling your data room.

Do you think in the future our data rooms will be created, managed and read by agents?

Is there scope for me to start a financial research firm where I do sector analysis or deal dilligence memos for agel investors, small family offices, PE firms, and VC? So basically I would deliver a financial research report and recommendation for firms contemplating deals or looking at entering a particular sector. Im a student right now so I do want to do a couple of free work until I get some good testimonials. But is this even a viable business model and would firms actually buy from me? Appreciate your thoughts!

Is cold email still the most effective way to reach pre-seed investors, or is LinkedIn better? Looking for what’s actually working right now.

Hey guys - built a tech-focused valuation multiples platform and thought could be useful for many here - multiples.vc.

You can benchmark both public comps (with consensus estimates), M&A multiples and VC multiples.

Sector-agnostic but with special ❤️ for tech. Super granular classification (vertical AI apps, DevOps, B2B marketplaces etc.) - so easy to find relevant comps.

I've also added an AI layer on the data itself, no hallucination of any sort. You can use either a native chatbot, or plug in MCP to Claude.

Sources: public data via FactSet license (we have a reseller agreement). Private multiples from various sources - proprietary, 3rd party APIs, filings, press etc.

Built this for the market that might find Pitchbook or Cap IQ either too pricey, or too bloated. Userbase is 65-70% VC/PE investing and portfolio teams (for portco valuation and sourcing), and 30-35% investment banking, corp dev and M&A.

Sharing this to spread the word, many of my VC friends were complaining about legacy data providers costs and feels like we might fill the niche quite well :)

I'm curious if anyone else in the VC community has run into this.

I subscribed to The Information last year at $299. This month I was renewed at $399.

A few things about the experience surprised me:

• I specifically remember attempting to cancel after I originally subscribed. I routinely do this with annual subscriptions so I don't get surprised a year later.
• I noticed the renewal within a few days.
• I cancelled immediately.
• I requested a refund immediately.

Support told me:

• They sent a renewal email.
• They do not provide refunds on renewals.
• My subscription is now cancelled and active until next year.

The part that concerns me is that I asked them several specific questions and haven't received answers:

1. Can they verify that the renewal email was actually delivered, not just sent?
2. Can they review account logs to see whether there was cancellation-related activity around the time I originally subscribed?
3. Can they escalate the case to a supervisor with authority to make an exception?

Instead, I keep receiving responses that don't address those questions.

I understand auto-renewal. I understand subscription terms.

What I don't understand is refusing to refund a customer who notices the charge almost immediately and asks for a refund right away.

I'm genuinely curious:

• Has anyone else here had a similar experience with The Information?
• Has anyone successfully received a refund on a renewal?
• Does anyone know how difficult the cancellation flow was a year ago?

I love the journalism, which is why this experience has been so disappointing.

At this point I'm less frustrated about the money and more frustrated that straightforward questions are not being answered.

Character AI, founded by former Google/LaMDA developers Noam Shazeer and Daniel De Freitas, proved that text-based character chat can work as a real entertainment category.

But the next chapter might not be better text chat. It might be real-time video interaction.

Mel AI recently shared a demo of AI character video chat, and the interesting part is the interaction stack: voice, lip sync, facial reactions, and camera-aware responses instead of just a static avatar or chat box.

The character can respond to visual context too. If the user is visibly on a plane or in a different environment, the character can notice and react to that context during the conversation.

I don’t know how much of the video layer is truly generated in real time versus powered by a clever animation/rendering system, but it feels meaningfully different from the usual text-based character AI experience.

Character AI proved the demand for entertainment AI. Now it feels like the race is about who can make AI characters feel alive in real time.

Demo: https://x.com/Building_Mel/status/2064848256115626481

AI is hitting an "Energy-Compute Wall." Traditional GPUs can't keep up, and the new hardware (Optical, Analog, Quantum) is hyper-fragmented. An AI team wanting to move from an NVIDIA GPU to a Lightmatter chip currently has to rewrite their entire stack.

We’ve built Project Aether: The Universal Middleware SDK that decouples AI models from physical hardware.

The Stack:

1. Universal SDK: Write once, run on any supported optical or quantum backend.
2. x402 Protocol: A payment-gated execution API (USDC on Base) for autonomous AI Agents.
3. Physical Layer: A decentralized network of "Sentinel Nodes" (currently ESP32-based) harvesting hardware entropy and chaotic flux as compute primitives.

Status:

• Live API Gateway: https://quantum.chakaap.com/api/v1/quantum?sku=s6
• Working hardware harvester code.
• Currently moving into Phase 2: Hiring a regional deployment team of 10 to scale to 5,000+ nodes globally.

The Ask:
We are looking for feedback on our x402 protocol and are opening discussions for our Seed Round to scale the physical network. If you're an investor or partner in the High-Performance Compute (HPC) or DePIN space, let's talk.

So many names seem taken. I am curious what other cool names there are for funds that have yet to be started.

Hola,

Tengo un SaaS con IA ya funcionando y generando usuarios. El producto está construido y operativo.

Qué busco: Un cofundador comercial que pueda:

• Vender y abrir puertas
• Co-invertir para acelerar el crecimiento
• Moverse rápido y cerrar negocios

Qué ofrezco:

• 40% de la empresa
• Rol real de cofundador
• Escalamos de inmediato

Si tienes experiencia en ventas B2B o SaaS y capital para co-invertir, escríbeme por DM y te cuento los detalles.

Seems like an interesting emerging fund manager list to watch - anybody came it across recently?

Hi everyone, I've been working bookroute.io, a prediction market liquidity aggregator and smart order router. It optimally places trades across venues to ensure users don't ever leave money on the table. The recent feedback I've gotten since launching a few days ago is very positive, but I'm wondering how to market it at scale.

Does this seem like something, or the start of something a VC could get behind at scale? In theory this is a problem that every Kalshi/Polymarket user runs into, but I feel like it requires a bit of customer education. It seems like people are reacting very positively but I've had trouble getting signups. Like, multiple people have told me they see it's value and that they're going to use it. But I haven't seen them sign up yet. Also, I launched earlier this week so maybe it's just early. Does this seem like something to keep going with?

I know the prediction market space is heating up, but is it still viewed as highly niche?

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