The firm Monte Carlo, which aims to assist other businesses in better monitoring their data intakes, said this morning that it has secured a Monte Ai 25m Series Redpoint Ggv B round of funding.
Monte Ai 25m Series Redpoint Ggv
Just a few months have passed since its $15 million September Series A, which was co-led by GGV and Redpoint. Accel oversaw the company’s seed and Series A investments and took part in its Series B.
We were interested in the round not just because of how quickly it was raised after Monte Carlo’s earlier investment, but also because your humble servant had no clue what data observability, the startup’s specialty, actually was.
Therefore, we called Barr Moses, co-founder and CEO of Monte Carlo, to ask her questions about the company’s market and how it was able to swiftly raise so much additional money.
Obtaining More Accurate Data for Businesses: Monte Ai 25m Series Redpoint Ggv
It is crucial that this data be trustworthy as data pipelines get more complicated and businesses consume more and more data. After speaking with hundreds of data teams over the past three years, I was surprised to learn that while businesses were pouring millions of dollars and strategic effort into data, decision-makers and other front-line personnel were unable to utilize it or didn’t trust it. There must be a better approach.
I’m thrilled to report that Monte Carlo has acquired $25 million in Series B investment to lead the developing Data Observability category and assist enterprises in obtaining more trustworthy data, bringing us one step closer to accomplishing this ambition for our clients.
Our total capital as of this announcement, which follows our Series A financing led by Accel in September, exceeds $40 million. Along with Accel, Redpoint Ventures and GGV Capital, investors in Snowflake, Looker, HashiCorp, and Slack, co-led this round. DJ Patil, a former U.S. Chief Data Scientist, has also praised Monte Carlo.
As the first end-to-end solution that enables data engineers and analysts to seamlessly monitor the health and dependencies of their data assets across the entire data stack, from ingestion to analytics all in one collaborative interface Monte Carlo’s Data Observability Platform fills this void by applying the same principles of application observability to data. Monte Carlo simultaneously gives CDOs and other data stakeholders a comprehensive understanding of their organization’s data health and dependability across crucial business use cases.
Monte Ai 25m Series Redpoint Ggv; A Developing Market
The product from Monte Carlo is attractive enough to demand our attention on its own. But, the fact that it integrates seamlessly with the expansion of the broader data area, particularly data tooling that isn’t immediately related to storage, makes it much more worthwhile to take into account.
With an additional $25 million, Monte Carlo can continue to pursue its mid-market and corporate customer targets while growing its 25-person team. See how quickly it can scale and when we can begin pressuring the business for growth figures.
The quick turnaround between the company’s Series A and Series B rounds is an indication of the excitement around Monte Carlo and Data Observability. We managed the dependability of more than 20 petabytes of data for their clients and grew our revenue every quarter of 2020. The only available option for data observability that has received SOC-2 certification is Monte Carlo.
Being the top Data Observability partner for the FinTech, e-commerce, media, B2B software, and retail industries, the business presently collaborates with a number of Fortune 500 organisations. Among its clients are the data teams at Compass, Eventbrite, Mindbody, and Hippo Insurance.
As a standalone layer on top of your current data stack, Monte Carlo is the first firm to apply the tried and tested software engineering concepts of observability and reliability to data. Oren Yunger, investor at GGV Capital, said, “I can’t see a data-driven firm not adopting Monte Carlo to assure trust in their data and the dependability of their whole data ecosystem.
