Databricks co-founder shares his secrets for winning big enterprises customers

Startups can now more easily land enterprise deals by leveraging larger tech partners for access and credibility.

Databricks co-founder Arsalan Tavakoli-Shiraji shared strategies for startups aiming to secure large enterprise clients at TechCrunch Disrupt. He emphasized that while strong technology is essential, it's insufficient on its own. Tavakoli-Shiraji highlighted that "people and processes matter the most," recounting early struggles where competitors' established relationships and a lack of preparation for enterprise-level legal and security requirements hindered deals. Databricks, now a $190 billion company with over 70% of the Fortune 500 as clients, found success by partnering with larger tech firms like Microsoft. This provided access, distribution, and credibility, enabling Databricks' sales to be advocates. He also outlined four key enterprise concerns for AI adoption: context, choice, cost, and control. Finally, Tavakoli-Shiraji pointed to modernizing expensive, legacy systems like AS/400s and mainframes as a significant opportunity for startups, leveraging AI to understand and decompose old code, thereby creating new interfaces or replacements.

Tavakoli-Shiraji's advice on partnering with established tech giants like Microsoft offers a viable pathway for smaller companies to penetrate the enterprise market. By operating under the umbrella of a trusted vendor, startups can bypass initial trust barriers and gain introductions to potential clients that would otherwise be inaccessible. This strategy allows startups to focus on their core technology while benefiting from the sales infrastructure and customer relationships of their larger partners, accelerating their own growth and market adoption.

The emphasis on addressing the "four Cs"—context, choice, cost, and control—for AI adoption provides a framework for startups to tailor their product messaging and development to meet specific enterprise needs. Furthermore, the identified opportunity to modernize legacy systems using AI agents speaks to a potential new wave of enterprise software solutions. Startups that can effectively demonstrate how AI can deconstruct and revitalize outdated infrastructure may find a significant market gap to fill, offering high value by tackling long-standing IT challenges that enterprises have been reluctant or unable to address themselves.