Databricks Co-Founder Shares Enterprise Sales Secrets
Arsalan Tavakoli-Shiraji, co-founder of Databricks, shares key strategies for landing large enterprise customers and lessons from early startup days.
Stock photo for illustration only, not from the actual event
- Startups often mistakenly believe their great tech will sell itself.
- Databricks now serves over 70% of Fortune 500 companies as customers.
- One major tactic is selling products under a larger tech company's umbrella.
- AI agents now help disrupt expensive legacy systems that enterprises feel stuck with.
Startups have never faced more intense pressure to grow rapidly. To achieve this, many must secure large enterprises—the deep pockets of the IT world—as paying customers. However, any company selling B2B enterprise software will tell you that winning these lucrative contracts is far from easy.
Arsalan Tavakoli-Shiraji, co-founder and senior vice president of field engineering at Databricks, which helps businesses store and analyze massive volumes of data, notes that a critical mistake younger startups make is assuming their technology will practically sell itself.
Stock photo for illustration only, not from the actual event
Yes, the underlying tech must function properly, but that alone is insufficient, he warns. Today, Databricks stands as an AI and big data storage giant valued at $190 billion, boasting more than 70% of the Fortune 500 as customers. Yet, it was once a modest startup, and Tavakoli-Shiraji was personally tasked with helping secure its very first major enterprise deals.
From an analytical standpoint, breaking into large enterprises typically requires overcoming stringent trust and data security barriers that early-stage startups often lack. Leveraging established enterprise partners serves as a crucial shortcut. Furthermore, tackling legacy systems remains a massive hurdle since organizations have heavily invested in existing setups. The ability of AI to parse and modernize ancient code significantly reduces friction in technology adoption.
To accelerate growth, Tavakoli-Shiraji recommends selling products underneath a larger technology company's established umbrella. Today, Databricks has evolved into that large enterprise partner, collaborating with startups and selling their offerings under its own terms and robust cybersecurity setup. Notable examples include Hightouch, an AI-powered marketing and customer-data tool provider backed by Databricks, Addepar, which delivers data solutions for financial professionals, and Tecton, a machine learning startup subsequently acquired by Databricks.
He further emphasizes choice as the freedom to switch between AI models rather than remaining locked into a single provider. Cost management focuses on regulating operational expenses for AI products, while control involves implementing safeguards to govern AI behavior and protect sensitive data assets.
Stock photo for illustration only, not from the actual event
When addressing the expensive legacy systems that enterprises believe they are trapped within, Tavakoli-Shiraji lightheartedly asks chief information officers where they stand with AI adoption on a scale from one to five. Level one indicates employees merely have access to ChatGPT, whereas level five signifies full integration of new AI capabilities that fundamentally transform business operations.
However, modern AI agents can now actively inspect and decompose what legacy code actually performs. He explains that this capability opens the door for products that execute everything from adding contemporary interfaces to obsolete systems to replacing them completely.
Source: TechCrunch
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