By Jason Kong, Cack Wilhelm, Karthik Ramakrishnan, Somesh Dash, and Tom Loverro
We're thrilled to announce our investment in data observability company Monte Carlo. We are leading Monte Carlo's $135M Series D financing, joining Accel, Redpoint Ventures, GGV Capital, ICONIQ Growth, Salesforce Ventures, and new investor GIC Singapore. This round of capital will help Monte Carlo continue its record-breaking pace of category creation, customer growth, and product innovation. Each day Monte Carlo gets closer to its goal of helping all organizations reduce data downtime, deliver data reliability, and ultimately become data-driven.
We first met Barr Moses, CEO and co-founder of Monte Carlo, in July 2020, after the company had raised its Series A. Then, the team was a scrappy group of 15 employees who had launched the first version of the Monte Carlo website only a week before. From the outside, that early version of Monte Carlo is unrecognizable to the 120+ strong team Monte Carlo has built today. But even then, two distinctive traits stood out to us:
Barr had done a tremendous amount of market validation and understood the pain point she was solving for, inside and out. Barr previously worked as VP of Operations at Gainsight, the company that created the Customer Success category, and managed its data organization. Time and again, she'd experience data downtime, in other words, periods of time when data was missing, erroneous, or otherwise inaccurate. Executives would Slack her about broken dashboards before important meetings, and customers would lose trust in her team's analytics. Inspired by her experience, Barr and her co-founder and CTO, Lior Gavish, knew there had to be a better way. Before starting Monte Carlo, she spoke to more than 150 data leaders, confirming that the problem of untrustworthy data was universal and costly. That overwhelming desire for a better solution and an end to data downtime inspired Barr and Lior to build Monte Carlo.
Her solution had immediate and deep resonance. On our first call, Barr described Monte Carlo in simple terms - New Relic for data. As the complexity of software stacks rose, we had seen the emergence of software observability vendors which played a crucial role in simplifying the need for containerization and microservices-oriented architectures. At IVP, we had also made investments in a growing number of data companies like AppDynamics, Datadog, and Cribl. Additionally, we were witnessing firsthand the increased complexity and fragmentation of data environments as they moved into the cloud. Some of Monte Carlo's very first customers were companies from IVP's own portfolio like Attentive and Compass, two organizations that felt the acute need to have more assurances around reliable data. Monte Carlo's software felt like a necessity; it was a matter of when to invest in this solution, not if.
Since that first meeting, Monte Carlo has been busy achieving milestone after milestone. Among their many achievements, Monte Carlo has grown its headcount more than 6x in the past six quarters and is still hiring (check out open roles here). They coined the phrase data observability, and created the category around the phrase, cementing their leadership position with acknowledgement by Gartner, Forrester, IDC, and other firms. They are currently busy writing the industry's first book on the topic.
Monte Carlo's vision and relentless drive is validated by its satisfied customers, including JetBlue, Fox, Affirm, Vimeo, and its incredible growth trajectory. The company's revenue doubled every quarter over the past two years from the time of its Series A in mid-2020 to today. Thus far, Monte Carlo achieved an impressive 100% logo retention.
The best for Monte Carlo is yet to come - a fact that we firmly believe at IVP. Cloud data warehouses have made capturing and analyzing tremendous amounts of data more accessible than ever before, fueling a rise of analytics, insights, and data-driven decision making within every business and organization. This is only the first chapter: the pre-eminence of data will continue to grow as it drives predictive decision-making with artificial intelligence and machine learning technologies.
On the near horizon is the opportunity for data access to be democratized and productized by both organizations and end users. Central to these innovations is the maxim: garbage in, garbage out. Breakages and errors are a natural and unavoidable result of the increasing complexity. The only practical solution is to observe, alert, and remediate issues as they arise. As cloud adoption increases and data grows, a data observability platform will become a necessity for every modern data stack. Monte Carlo is the leader in this new category they pioneered, and a standout shaping the modern data stack.
We are excited to partner with Barr, Lior, and the Monte Carlo team to help more organizations turn data-driven decision making from a dream into a reality.
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By Jason Kong, Cack Wilhelm, Karthik Ramakrishnan, Somesh Dash, and Tom Loverro 
