Filevine CEO: Nothing Is Sacred - How We Became AI Native

How Filevine Transformed From SaaS to AI-Native

This session starts at 7:00 in the SaaStr AI London GTM Stage recording.

Ryan Anderson's presentation is a masterclass in what it actually takes for a successful SaaS company to go AI-native. Filevine, a legal tech platform with $200M+ ARR growing at 50-60%, has made a remarkable transition where AI products now generate more new revenue than their core SaaS offering.

The "Bridge Over River Kwai" analogy is striking: Anderson warns leaders not to become like the general who built a beautiful bridge for the enemy and then committed treason to protect it from being destroyed. Your teams have built incredible things and are justifiably proud - but some of that code, those architectures, will have to be torn down. "Nothing is sacred."

His 4x4 matrix for deciding what to tear down versus keep is practical: plot your systems by competitive advantage and whether they slow you down. Upper right (high advantage, doesn't slow you) - fortify it. Lower left (no advantage, slows you down) - tear it down, even if emotionally hard. The middle cases require judgment.

The architectural insight is crucial: you cannot "sprinkle AI on top." ML engineers need to own their data layer and tune it daily. They can't be going to traditional engineering asking to modify APIs. The AI data layer must sit alongside the AI application layer, not on top of legacy infrastructure.

On pricing strategy, Anderson is refreshingly aggressive: "Price to dominate." SaaS companies have high gross margins. AI-only competitors struggle with LLM costs. Use your blended gross margin advantage to undercut competitors and gain market share. Be "Latte Larry" from Curb Your Enthusiasm - set up shop next door and drive prices down until they come to you on bended knee.

4 Insights From Filevine's AI Transformation

• Your SaaS data is the advantage - but shift from thinking about "content" (what's stored) to "context" (what AI needs to take action)
• AI natives want to work where there's rich data and distribution - sell them on your system of record, not your legacy brand
• The "tie goes to the runner" - customers don't want to leave their system of record, so you win in a tie against AI-only competitors
• Obsess over usage metrics: DAU, WAU, MAU, audit trails. If you don't know exactly who's using AI features and how, you can't iterate fast enough