u/schneida_vie

Hey all, quick one 👋

A fast-growing Vienna startup is hiring a *Head of Growth* and I'm helping them find the right person.

• AI product for SMBs, 10,000+ customers
• $1M → $10M ARR in under 12 months, €20M raised
• 7-figure monthly budget, owns the engine behind ~90% of revenue
• Performance, SEO, CRO, lifecycle + product growth (pricing, onboarding)
• Builds the team from scratch, reports to the CEO
• Up to €250k + significant equity, Vienna based, relocation covered

Profile: someone who has scaled paid acquisition on a low-ACV, high-velocity motion in more than one market. B2C and D2C backgrounds very welcome, this is not a classic enterprise demand-gen role.

If that's you or someone you know, DM me and I'll share the details and make the intro.

Hey all, quick one 👋

A fast-growing Vienna startup is hiring a *Head of Growth* and I'm helping them find the right person.

• AI product for SMBs, 10,000+ customers
• $1M → $10M ARR in under 12 months, €20M raised
• 7-figure monthly budget, owns the engine behind ~90% of revenue
• Performance, SEO, CRO, lifecycle + product growth (pricing, onboarding)
• Builds the team from scratch, reports to the CEO
• Up to €250k + significant equity, Vienna based, relocation covered

Profile: someone who has scaled paid acquisition on a low-ACV, high-velocity motion in more than one market. B2C and D2C backgrounds very welcome, this is not a classic enterprise demand-gen role.

If that's you or someone you know, DM me and I'll share the details and make the intro.

Kevin Jiang worked on Comet at Perplexity, one of the first AI browsers that people actually opened daily. He left, co-founded Polar with two other MIT people, and just raised $5.7M led by Madrona.

The wedge did not come from a market map. It came from watching a specific thing break from the inside: agents that could describe a plan convincingly but could not reliably finish it. Their framing was that the best agents could not reliably add a calendar event, but with newer models their prototypes ran for hours.

That is the actual insight I want to argue for here. Competitive research gives you feature gaps. Working inside the incumbent gives you failure modes. Feature gaps get closed in a sprint. Failure modes are architectural and take the incumbent two years to fix, which is your entire window.

Practical version of the pattern for anyone sitting inside a big AI company right now:

• Write down every time the product embarrasses you in front of a user. That list is your roadmap.
• The best wedge is usually the thing your current employer has decided is an acceptable loss.
• Your ex-colleagues become your first angels and your first reference calls. Vishaal Ram's time at Modal is why Modal's CEO is on the cap table, and his public GitHub contributions to Modal's repos back the tie up.

Two things worth being clear eyed about. First, the legal surface: leaving to build a direct competitor to the exact product you shipped is a real IP and non-compete conversation, and "I only took the insight" is a defense you would rather not test. Second, most people who try this build a slightly better version of the incumbent instead of a differently shaped one, and slightly better loses.

Anyone here made this jump? How did you handle the non-compete question with investors?

Most seed rounds run this order: raise on a story, then spend the money finding out if anyone actually wants the thing.

Polar (agentic browser, SF) inverted it. Three MIT founders shipped for seven months first. No fundraising process, no ads, no outbound. Word of mouth only. By the time they talked to investors, the product had executed 4.5 million actions across the open web for real teams.

Then Madrona led a $5.7M seed.

What that sequencing actually bought them, in practical founder terms:

**•**	The diligence question was never “will people use this.” It was answered before the first call, so the negotiation was about price, not belief.  
**•**	They had leverage on the angel list. You do not get GitHub’s former CEO writing a personal check on a deck.  
**•**	Every month of organic usage is the one asset a competitor cannot fake and an investor cannot talk themselves out of.

The honest counterargument: this is a fundable-by-default team. Ex-Perplexity, ex-Modal, ex-Jane Street, MIT across the board. They could afford to wait because they had savings, optionality, and warm networks. If you are burning runway on a solo founder salary in a non-hub city, “just wait seven months” is a luxury purchase, not a strategy.

So the transferable version is narrower: do not raise before you have one usage fact a stranger can repeat in a sentence. That fact does not have to be 4.5 million actions. It can be 12 teams using it weekly for four months.

What is the smallest usage proof you would raise on?

(Full breakdown in comments if anyone wants it.)

Polar (agentic browser, SF) inverted it. Three MIT founders shipped for seven months first. No fundraising process, no ads, no outbound. Word of mouth only. By the time they talked to investors, the product had executed 4.5 million actions across the open web for real teams.

Then Madrona led a $5.7M seed.

What that sequencing actually bought them, in practical founder terms:

**•**	The diligence question was never “will people use this.” It was answered before the first call, so the negotiation was about price, not belief.  
**•**	They had leverage on the angel list. You do not get GitHub’s former CEO writing a personal check on a deck.  
**•**	Every month of organic usage is the one asset a competitor cannot fake and an investor cannot talk themselves out of.

The honest counterargument: this is a fundable-by-default team. Ex-Perplexity, ex-Modal, ex-Jane Street, MIT across the board. They could afford to wait because they had savings, optionality, and warm networks. If you are burning runway on a solo founder salary in a non-hub city, “just wait seven months” is a luxury purchase, not a strategy.

So the transferable version is narrower: do not raise before you have one usage fact a stranger can repeat in a sentence. That fact does not have to be 4.5 million actions. It can be 12 teams using it weekly for four months.

What is the smallest usage proof you would raise on?

(Full breakdown in comments if anyone wants it.)

Most VC databases tell you who invested in what. We went a layer deeper — extracting how each GP actually thinks: thesis tags, what they're bullish on, what they bet against the consensus on, and a Founder Dos & Don'ts playbook built from primary research (GP blogs, interviews, LinkedIn).

970+ funds, all raised capital since September 2024. If a fund stopped deploying, it's not on the list.

This week we also shipped an MCP Server — so you can query the entire database from Claude or Cursor in plain language. Ask "Which seed funds in DACH invest in B2B SaaS and are deploying now?" and get a live answer.

Happy to discuss what we learned about VC intelligence gaps, how founders actually use this, or how we built the MCP layer. AMA.

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

Vienna has produced unicorns and scaleups like Bitpanda, GoStudent, Tricentis, waterdrop®, Storebox • Urban Logistics, refurbed, NEOH & PlanRadar 🇦🇹

But the next wave is already being built.

Here are the ones that still have startup energy:

fonio.ai, Howie, mypaperwork.ai, Kickscale, chatlyn, Revo Foods, ContextSDK, Talentir, fynk, OPTIMUSE, nyra health, Flinn.ai, Anyline, Prewave,..

72+ Vienna startups, + all hiring positions, all on the map. Free to explore on StartupMap.

💬 Which Vienna startup is missing from this list?

Huge shoutout to Jan-Willem Denys at StartupMap.one for making Europe's startup ecosystems visible city by city and country by country.

Polsia just closed $30M Series A at a $250M post-money valuation. One founder, Ben Cera. Zero employees. ~$10M ARR five months after launch, 7,600 companies on the platform, 3,627 DAU, 85% month-two retention. It is now the highest valuation any truly solo company has ever crossed.

Every post about this is going to lead with the AI-agents-run-everything angle. That part is real (the agents literally ran his fundraise outreach, diligence, scheduling, and data room, he only joined for term sheet signature calls), but it is also the part you can already infer from the product name.

Anyone tried it so far?

Polsia just closed $30M Series A at a $250M post-money valuation. One founder, Ben Cera. Zero employees. ~$10M ARR five months after launch, 7,600 companies on the platform, 3,627 DAU, 85% month-two retention. It is now the highest valuation any truly solo company has ever crossed.

Every post about this is going to lead with the 'AI agents run everything' angle. That part is real (the agents literally ran his fundraise outreach, diligence, scheduling, and data room, he only joined for term sheet signature calls), but it is also the part you can already infer from the product name.

Anyone tried it so far more exentsively?