Pamir Ventures

One of the biggest lies in venture capital: “Software is capital efficient. Deep tech is CapX intensive.” I’ve backed both. Here is the reality that most investors get completely wrong. Let’s talk about what SaaS actually costs. Because nobody does. SaaS companies spend 30–60% of their revenue on sales and marketing. Before they’re profitable, some spend more on S&M than they make in total revenue. The average B2B SaaS company spends $1,200 to acquire a single customer. Enterprise deals? $3,750 per customer with an 18–24 month payback period. Enterprise sales cycles run 6 to 18 months. That means you’re paying AEs, SDRs, and sales engineers full salaries for over a year before you see a dollar from that deal. There are 30,000+ SaaS companies in the world right now. 1,500 new ones launch every month. Only 0.4% ever reach $10M ARR. And the worst part? Your feature gets cloned in weeks. Your moat is your sales team, not your product. Yes, deep tech often has upfront costs. Hardware. Lab equipment. Longer R&D cycles. But what do you get for it? Patents. Regulatory moats. Specialized knowledge that takes years to replicate. Hardware that can’t be copy-pasted by a competitor over a weekend. The data backs it up. BCG and Hello Tomorrow found that hardware-focused deep tech startups deliver a 27% gross IRR. Software? 13%. McKinsey confirmed that deep tech funds deliver higher average net IRR than traditional tech funds. Deep tech’s upfront capital buys you something SaaS never can: 𝗱𝗲𝗳𝗲𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆. I'm not saying one is better than the other. I back both. I believe in both. What I'm saying is they're both capital intensive. Just in different ways. SaaS spends on acquisition. Deep tech spends on creation. Neither is cheap. Neither is easy. The investors who dismiss deep tech as "too expensive" while writing checks to their 15th CRM tool aren't being honest about where the money actually goes. Stop comparing them on cost. Start comparing them on what that cost builds. #VentureCapital #DeepTech #Startups #Founders #SaaS

The full video from my HLTH Inc. 2025 panel just dropped. Most people think AI in drug development is about speed. Run the same experiments faster. Screen more compounds. Cut timelines. That's the surface. The real shift is deeper than that. 𝗔𝗜 𝗶𝘀 𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝘄𝗲 𝗰𝗮𝗻 𝘀𝗲𝗲. Massive, diverse human datasets are letting us unlock layers of biology we couldn't access before. We're not just developing drugs faster. We're finding the right treatments for the right patients including complex and rare diseases that were previously untouchable. 𝗧𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗵𝗶𝗻𝗴𝗲 𝗺𝗼𝗺𝗲𝗻𝘁. Not faster pipelines. Better biology. Better precision. Better outcomes. I got to explore this on the opening day stage at HLTH USA in Las Vegas. If you're building in biotech, health, or life sciences, this is the conversation that matters right now. Full talk here: https://lnkd.in/gm4SB5k2 What's the most underrated way AI is changing healthcare that no one's talking about? #PrecisionMedicine #AIinHealthcare #DrugDevelopment #HLTH2025 #Biotech #Founders #LifeSciences

I've interviewed hundreds of people. Most people hire wrong. They hire friends. They hire pedigree. After doing this long enough, I look for three things that aren't discussed enough: 𝗢𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗶𝗻𝘀𝘁𝗶𝗻𝗰𝘁. They treat the company like it's theirs even when it's not. How I test it: "Tell me about something you fixed that wasn't your job." A-players have multiple examples and get energized talking about it. B-players struggle to find one. 𝗗𝗲𝗽𝘁𝗵 𝗼𝘃𝗲𝗿 𝗽𝗼𝗹𝗶𝘀𝗵. You can only simplify what you truly own. How I test it: I ask them to explain something they're world-class at. Not on their resume. Something they've mastered. If they can translate complexity into clarity in two minutes, they've earned that knowledge. If they hide behind jargon, they borrowed it. 𝗖𝗵𝗮𝗿𝗮𝗰𝘁𝗲𝗿 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆. Who they are when no one important is watching. How I test it: Take them to dinner. Watch how they treat the server. The best hires don't perform in interviews. They reveal. What's a trait you look for that most people miss? #Hiring #Founders #Startups #Leadership

Eid Mubarak! My family finally found a way to get me off my laptop. 🤣 Thank you for all the kind messages on LinkedIn, text, and even strangers coming up and saying “Eid Mubarak!” Spending the day with family. No emails. No Slack. No deal memos. Sometimes the best investment advice is: put the laptop away and be present. Bittersweet, though, knowing there's so much conflict in the world right now. I'm grateful to be able to spend time with the people I love. Hope everyone has a meaningful day with the people who matter most! 😊 #eidmubarak2026 #eidmubarak

Condor just raised $24M Series A led by Insight Partners. Pamir Ventures was an early investor. Anand, Roger, and I doubled down. Good science is getting killed in budget meetings. Not because the drug doesn't work. Because no one can see where the money is going. I was introduced to the founder by a trusted investor with whom I had previously scaled a company. My background in biotech R&D combined with Roger and Anand's expertise in finance systems and CFO workflows gave us the the perfect combination to evaluate Condor. We called CFOs and finance leaders at pharma companies we have known for years. Every conversation confirmed the same thing: this problem was real, painful, and unsolved. We saw what made Condor different. Condor's AI layer handles data ingestion, predictive benchmarking, and a Copilot that automates the manual work that used to bury finance teams. Jennifer Kyle built the accounting workflows pharma actually uses. Then she left to fix what was broken. She understood the problem from the inside. Condor now manages over $19B in R&D spend. Customers report 90% forecast accuracy and 70% faster month-end close. We came to conviction fast. Because of the founder and the problem. We participated in the earlier round, helped Jen build the foundation for Series A, and watched her execute a financing round with multiple term sheets. Jen is building the financial infrastructure life sciences has needed for decades. The kind of company where the technology becomes invisible and the value becomes obvious. Proud to be alongside Insight Partners, Felicis, SNR, and the rest of the investors. The future of R&D finance runs on Condor. #Biotech #VentureCapital #LifeSciences #Startups

Condor just raised $24M Series A led by Insight Partners. Pamir Ventures was an early investor. Anand, Roger, and I doubled down. Good science is getting killed in budget meetings. Not because the drug doesn't work. Because no one can see where the money is going. I was introduced to the founder by a trusted investor with whom I had previously scaled a company. My background in biotech R&D combined with Roger and Anand's expertise in finance systems and CFO workflows gave us the the perfect combination to evaluate Condor. We called CFOs and finance leaders at pharma companies we have known for years. Every conversation confirmed the same thing: this problem was real, painful, and unsolved. We saw what made Condor different. Condor's AI layer handles data ingestion, predictive benchmarking, and a Copilot that automates the manual work that used to bury finance teams. Jennifer Kyle built the accounting workflows pharma actually uses. Then she left to fix what was broken. She understood the problem from the inside. Condor now manages over $19B in R&D spend. Customers report 90% forecast accuracy and 70% faster month-end close. We came to conviction fast. Because of the founder and the problem. We participated in the earlier round, helped Jen build the foundation for Series A, and watched her execute a financing round with multiple term sheets. Jen is building the financial infrastructure life sciences has needed for decades. The kind of company where the technology becomes invisible and the value becomes obvious. Proud to be alongside Insight Partners, Felicis, SNR, and the rest of the investors. The future of R&D finance runs on Condor. #Biotech #VentureCapital #LifeSciences #Startups

"We use AI" is not a moat. It's a countdown timer. Botkeeper raised $90m and learned this the hard way. They built AI for bookkeeping before most people trusted AI with a spreadsheet. Claimed 98% accuracy. Was weeks away from launching new products. Last month, they shut down. Botkeeper was a pioneer. They were one of the earliest AI-focused tools in accounting. For years, "we use AI" was their moat. Then Sage added AI. QuickBooks added AI. A wave of new startups launched with AI baked in from day one. Suddenly, their differentiator became table stakes. The founder admitted a hard truth: "We did not reach a level of product-market fit strong enough to withstand rapid industry shifts. The market moved faster than our capital could keep up." $90 million wasn't enough runway to outrun commoditization. 𝗔𝗜 𝗶𝘀 𝗮 𝘁𝗼𝗼𝗹, 𝗻𝗼𝘁 𝗮 𝗺𝗼𝗮𝘁. If your only defensibility is "we use AI," you don't have defensibility. You have a feature that every competitor will copy within 12 months. 𝗪𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗯𝘂𝗶𝗹𝗱𝘀 𝗮 𝗺𝗼𝗮𝘁: • Proprietary data that improves your model and no one else can access • Deep workflow integration that makes switching painful • Network effects where more users = more value • Regulatory expertise or compliance barriers • Distribution advantages that can't be replicated The companies that survive the AI hype cycle won't be the ones who used AI first. They'll be the ones who built something defensible around it. Technology is never the moat. What you do with it is. #AI #Startups #VentureCapital #Founders #Fundraising

A founder raised $8M a year ago without a deck. Lots of hype. Fast forward, now he needs an emergency bridge. Struggling. Stuck. Silent investors. Last year, he was a hot AI deal. Multiple term sheets. He took the biggest check at the highest valuation. No deep dives. No hard questions. He reached out last week. We talked for two hours. Hype got him the check. It didn't build the company. He skipped the fundamentals. Now he's learning them under pressure. Here's the bigger problem: One of the most dangerous trends in our industry right now is founders bragging about how fast they raised and that they didn't need a pitch deck. It's not inspiring. It's misleading. It makes other founders feel like they're doing something wrong if their raise takes time. Or if investors ask hard questions. Or if they need materials to tell their story. But here's the thing. It's fixable. And the founders who figure this out early have a massive advantage. 𝗧𝗼 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀 𝗿𝗮𝗶𝘀𝗶𝗻𝗴 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄: • Don't confuse a fast round with a good round • Investors who skip diligence will skip you when it's hard • Build the deck even if no one asks for it • Know your numbers cold: CAC, LTV, retention, runway • The deck isn't for investors. It's for you. It forces clarity. 𝗧𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀 𝘄𝗵𝗼 𝘄𝗶𝗻 𝗹𝗼𝗻𝗴-𝘁𝗲𝗿𝗺 𝗮𝗿𝗲𝗻'𝘁 𝘁𝗵𝗲 𝗼𝗻𝗲𝘀 𝘄𝗵𝗼 𝗿𝗮𝗶𝘀𝗲𝗱 𝘁𝗵𝗲 𝗳𝗮𝘀𝘁𝗲𝘀𝘁. They're the ones who understood their business the deepest. Hype opens doors. Fundamentals keep them open. #VentureCapital #Founders #Startups #Fundraising #AI

My team and I just published a comprehensive analysis comparing the US, China, India, and the EU in the race to dominate the Bio-Industrial Technology Stack (BITS) through 2050. We can design the cures. We just can't make them at scale. China is executing a state-led bioeconomy strategy across all three layers. India is leveraging its generics dominance to climb the entire stack. Meanwhile, the US is fragmented. Bifurcated data privacy laws across states. No comprehensive federal framework. Re-shoring efforts that will take decades to catch up. This is the geopolitical tipping point. The nation that controls the "Sovereign Flywheel" — where manufacturing data feeds back into AI models in a closed loop — will control who has access to the cures of the future. This isn't about innovation anymore. It's about infrastructure. It's about sovereignty. Companies like Alloy Therapeutics, Inc. and Revalia Bio are keeping the US competitive. Building the validation and execution layers that actually matter. Proud of my team for putting this together. A framework that I hope shapes how we think about biotech as national security. Read the full publication here: https://lnkd.in/gJcdkkF4 Jason Novak Ebony C. Nathanael Green, PhD, #Biotech #NationalSecurity #AI #LifeSciences #VentureCapital