Javier Rojas

Hey Javier — similar path (banking → growth equity). been thinking a lot about proprietary origination in B2B SaaS lately. would be good to connect.

Hey Javier, similar banking-to-growth-equity path, though I was in London at Greenhill not advising on SaaS exits out of the Bay Area like you. origination was always the same story for me — clear thesis, decent relationships, but no proprietary system of record tying anything together. the people, tools and ideas were never really connected. every deal virtually sourced from scratch, nothing compounding over time. curious if that's still how most funds operate or if I'm behind the times? — Russ

Hey Javier, looks like we came up through a similar path — banking into growth equity — though I was in London at CS & Greenhill doing M&A not in SF building a platform around founder-led SaaS like you've done with Savant. the pattern I keep seeing with most funds is weirdly consistent — strong thesis, solid network, but no proprietary system of record. the people, tools and ideas are never really connected, so every deal is virtually sourced from scratch. nothing compounds on itself. curious if that resonates or if you've built something different at Savant? — Russ

hey Javier — no worries if the timing's off. most funds I talk to have tried some version of building origination in-house — analyst pulling from Pitchbook or Grata, maybe using ChatGPT to help qualify, dumping it into a spreadsheet. each piece kind of works, but there's no system of record tying it together. the people, tools and ideas stay disconnected, so there's tonnes of wasted energy. been helping a few funds like Noble Rock work through that. curious if you've run into the same thing at Savant? — Russ

totally get it if origination infrastructure isn't top of mind right now — most funds have 10 things ahead of it on the priority list. the funds I've seen crack it early just tend to compound deal flow in a way that's hard to replicate later. if it ever moves up the list, I'm easy to find. — Russ

Javier – Saw we share nearly identical paths: both did Econ at top liberal arts schools (you at Williams, me also at Williams – triple major with History and English), both moved through NYC/international banking before landing in growth equity – although you've been far more prolific building Savant Growth to $500M. Been building proprietary (and custom) deal flow systems for growth investors like you: Axiom Equity in the UK (they do £60m+ equity tickets in B2B SaaS) and Noble Rock Software here in the US. Savant surfaced as a strong fit given your focus on capital-efficient SaaS, $10-40M checks, and a partner-led team managing active portfolios like Qount and IntelePeer. It's not fancy, but it handles the whole process: finds founder-led B2B SaaS companies matching your 3-15M ARR thesis, scores them, gets CEO/founder contacts, drafts personalized outreach, manages follow-ups, books the meetings. Figured with you and the team actively managing portfolio companies while also sourcing differentiated deal flow in Applied AI and automation, you might be in the same boat I was at Treis. Worth a quick call to see if it fits? Russ

Javier – Most PE associates spend 80% of their time on work that can be 95% automated. The workflow: Export companies from PitchBook → Open websites one by one → Copy info → Score deals → Hunt for contacts → Draft outreach → Track everything in Excel. That's a $200K-$300K employee doing data entry. At a $500M fund with 3-4 investment professionals, you can't afford to have your best evaluators hunting for email addresses instead of evaluating deals. The analysis quality stays identical. It just happens 25x faster when you automate the manual parts. Associates should be on calls with founders in your Applied AI pipeline, not copying website content into spreadsheets. Worth discussing how this plays out at your fund size? Russ

Javier – PitchBook tracks funding rounds, employee count, basic financials. What actually determines if a B2B SaaS company at 3-15M ARR is worth your time: – Pricing models that suggest margin expansion or compression – Customer benefit claims that indicate real switching costs vs. nice-to-have features – Implementation timelines (2 days vs. 6 months tells you everything) – Compliance depth in vertical software plays Databases are great for finding companies. Terrible at evaluating them. When you're looking at capital-efficient SaaS businesses for $10-40M checks, you need to know what's happening in the business model, not just what happened in the last funding round. We built automation that reads websites like a senior associate reads them – looking for actual competitive moats and margin stories – just 1000x faster. Makes sense for a fund actively managing portfolios like Qount while sourcing new Applied AI deals? Russ

Javier – Here's the structural problem: Your associates can manually evaluate maybe 50-75 companies per quarter. They spend most of their time on the mechanical parts – website research, contact hunting, data entry. That means hundreds of founder-led B2B SaaS companies in your exact thesis never get looked at. Not because they're bad fits. Because there aren't enough hours. The $200K employee problem isn't just about efficiency. It's about all the differentiated deal flow that falls through the cracks while your team is doing manual work. At a partner-led fund writing $10-40M checks into enterprise software, you can't afford to miss the companies that aren't obvious in PitchBook but perfect for your strategy. Probably worth a conversation at this point, even if just to compare notes on how you're handling this. Russ

Javier – Timing might not be right. Get it. If sourcing bandwidth ever becomes the constraint, we solve the associate time problem. Russ