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The Bar Has Gone Up: The New Era of HyperFunctional SaaS with Jason Lemkin

SaaStr

Security and compliance are strong, with Wiz turning down billions from Google. And we talked about security compliance. There is no downturn in security compliance. There is no downturn in security compliance. But Zscaler , CrowdStrike, Rubrik , for all of these folks in security compliance, there is no downturn.

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How Dialpad Hit $300M ARR by Building Their Own AI Stack: 5 Key Learnings

SaaStr

Consider a hybrid approach : You can start with third-party APIs while building your data foundation, then gradually move to custom solutions as you scale. Domain Data Is Your Secret Weapon Dialpad’s massive advantage comes from their 8 billion minutes of processed conversations.

AI 255
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Building and Scaling an AI Company in 2025: What Top VCs Really Want to See with Zetta, Glasswing and B Capital

SaaStr

Joselyn Goldfein, Managing Director at Zeta Venture Partners Joselyn is a technologist-turned-investor who leads AI and data infrastructure investments at Zeta Venture Partners, focusing on inception through seed stage startups. The Data Moat Your data strategy needs to go beyond just having a lot of data.

Scale 193
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The Enterprise Journey: 8 Keys to Going Upmarket Successfully with Workiva’s CEO Julie Iskow

SaaStr

Focus on: Building robust security and compliance (SOC 2, ISO 27001) Automating customer onboarding/offboarding Creating enterprise-grade support processes Developing procurement relationship expertise Having clear data handling procedures 5. Master Enterprise-Grade Operations The operational bar is much higher in enterprise.

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The Journey from Freemium to PLG to SLG: Key Learnings from Dropbox, Salesforce and Vimeo

SaaStr

The requirements: Rock-solid customer data systems Sophisticated sales ops and revops Advanced operational data warehousing Modern customer data platforms And here’s the part that might surprise you: This needs to be a CEO-level priority. It’s not just product or sales – it’s operational excellence.

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Clouded Judgement 1.24.25 - The Year of Enterprise AI

Clouded Judgement

While cutting-edge language models have demonstrated remarkable capabilities, most are primarily trained on open internet data. In AI terminology, “generalizing” refers to a model’s ability to apply learned knowledge to new tasks or unseen data. This is what I’m calling “Enterprise AI.”

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Top 10 Trends for Data in 2024

Tom Tunguz

At the IMPACT Summit yesterday, I shared our Top 10 Trends for Data in 2024. LLMs Transform the Stack : Large language models transform data in many ways. First, they have driven an increased demand for data and are causing a complete architecture inside companies. Second, they change the way that we manipulate data.