Arsalan Tavakoli-Shiraji, co-founder and senior vice president of field engineering at Databricks, shared insights on how startups can successfully land large enterprise customers. Speaking at TechCrunch Disrupt, he emphasized that having strong technology alone is insufficient for winning big contracts. Instead, building relationships and establishing effective processes are critical.

Databricks, now valued at $190 billion and serving over 70% of the Fortune 500, started as a small startup facing challenges in securing its first major deals. Tavakoli-Shiraji recalled early setbacks, including difficulties in gaining meetings with prospects loyal to competitors and being unprepared for legal and security requirements.

One key strategy he highlighted was partnering with established tech companies. Databricks initially struggled to engage UBS, a major Swiss bank, but after becoming an Azure cloud partner with Microsoft, it gained access to Microsoft’s sales channels and credibility. This partnership helped open doors and accelerate growth. Today, Databricks itself supports startups by incorporating their products under its own terms and security frameworks.

When selling AI solutions to enterprises, Tavakoli-Shiraji advises addressing what he calls the “four Cs”: context, choice, cost, and control. Context refers to AI’s ability to learn a company’s specific language and workflows. Choice means allowing enterprises flexibility to switch AI models. Cost involves managing operational expenses, and control focuses on safeguarding AI behavior and sensitive data.

He also identified modernization of legacy systems as a significant opportunity for startups. Many enterprises still rely on outdated infrastructure like IBM AS/400 mainframes, which are difficult to maintain. AI agents can analyze and interpret legacy code, enabling startups to offer modern interfaces or replacements, thereby unlocking value for these organizations.

Tavakoli-Shiraji noted that while many enterprises are experimenting with AI, most remain in early adoption stages. Meaningful deployment of AI to transform business processes will take years. His experience underscores the importance of combining technical innovation with strategic partnerships and understanding enterprise priorities to succeed in the competitive enterprise market.