Meet the Venture Capitalists · Firm Profile
Sapphire Ventures
States it invests in expansion-stage enterprise software companies, that it looks for businesses past product market fit which it believes can become category leaders, and that it invests with high conviction in a select number of companies.
Criteria: States firmwide assets under management of more than $10 billion as of 30 June 2026. Focus on enterprise AI, with a portfolio spanning data infrastructure, security, customer data platforms, sales and marketing automation, human resources technology, fintech and healthcare applications. Publishes a CEO net promoter score of 82 from its portfolio. Publishes no check sizes.
What this means for your pitchPost product market fit is the gate and they state it plainly, so do not approach before you can evidence it. The published net promoter score is unusual and worth using: ask them to introduce you to the founders who scored them, because a firm willing to publish the number should be comfortable with the reference call.
Check sizes are not published by the firm.
Sapphire VenturesChecked 17 August 2026
From Sapphire Ventures's own site and announcements · checked 26 August 2026 · selective, not comprehensive · verify on the firm's pages
Sapphire announced its participation in Chai Discovery's $400 million Series C. Chai Discovery builds AI models that design new antibody candidates for drug discovery, and the firm states the company has partnerships with Eli Lilly, Pfizer, and Novartis.
Sapphire published a market map on AI in design software, covering creative production, product design, and workflow infrastructure. The firm states it is looking for founders building tools that capture organizational judgment, brand context, and production history rather than competing on output quality alone.
Sapphire published its 2026 Midyear Review, a market memo examining five questions shaping AI at mid-2026, including infrastructure spending, constraints from power and supply chains, and competition among frontier model labs. The firm states that lower-cost open-weight models are improving rapidly and support a multi-model future for AI.