When we first met the Sifflet team and led their seed round in 2021, it was immediately apparent to us that this team was special. They checked all the 'boxes'. In particular, two things stood out: They are not only amazing humans and highly ambitious. Everything they were doing and planning evolved around one thing: Product, Product, Product...
Today, we are happy to announce that we have doubled down on this great team in their Series A. We couldn't be more excited to welcome EQT ventures on this journey. I enjoyed my interactions with the team since we first met. Their insights into the data space will further strengthen Sifflet.
Data is eating the world: ‘Ever More Data, Ever More Challenges...'Based in Paris, Sifflet is an end2end data observability platform. What does this mean? In simple words, Sifflet’s core software, nicknamed ‘Barracuda’, enters and screens in real-time your full data stack, meaning all data before entering (data ingestion) and after coming out of the data warehouse (BI/until data is visualized for the end-user). But why now? Data amount and sources are one of, if not, the fastest-growing segment in the tech world... IDC expects growth to be 50x in the next decade alone, reaching figures that dwarf anything we have dealt with until now. Recent developments (see more here) will accelerate this trend even further...
Enterprises can’t afford data to break: Without a working data stack, there is no business. It’s that simple. When it fails, not only does it take days to figure out where the problem is, but also how to solve it. And this is when a company has a solid data science team - and this is rare... Otherwise, it is mission impossible. More importantly: Once a failure is detected, it is probably too late already - the potential (negative) impact on businesses is tremendous. Gartner now estimates that 'bad data quality' causes a business to lose, on average, I repeat, on average, $13m a year. And this pain will grow in the following years if not dealt with...
We are excited to back a solution that truly solves this massive challenge with the first '360 package'.
Sifflet - 5 reasons we invested...1) A large and category-defining Market: 'From DevOps to DataOps'
We have seen these shifts before. Last decade ‘software is eating the world’ was all the rage. Some of the most successful tech businesses of the previous 10 years have been category-defining software-monitoring tools such as Datadog or Splunk. As we are moving from a software to a data-first world, it is no surprise that our team has been searching for the 'obvious', a data-monitoring software.
While still an emerging category, we expect it to develop much quicker than the previous one. Why? Data is growing faster than software adoption did. And data is core to the vast majority of businesses already today. The shortage of data scientists is even more staggering than that of software developers. The market pull Sifflet has experienced since its product launch underlines this growing trend. To illustrate this, the Sifflet co-founder Salma gives two examples here. Every industry is impacted: From retail, pharma, or financial services, to tech companies. In 2016 already, Netflix was down for hours during prime time on a Saturday evening because of data quality issues.
2) A ‘One-Stop Shop’, the full-stack approach
Here is the trick: Monitoring only makes sense if you have a full picture... Data observability solutions work by collecting data from the data stack, leveraging ML, to monitor its quality. Because of the complexity of the topic, most tools (and many great startups we had the pleasure to meet in the past) are focusing (only) on one (or a few) elements of the data stack. And, like most of our medical system today, the major focus is on solving issues post-incidence and on specific data infrastructures. Sifflet has a different approach.
Enterprises need a one-stop shop. Since day 1, Sifflet’s team was obsessed with building a modular product covering the whole value chain and compatible with various infrastructures. Besides creating a strong ML algorithm over time, a particular focus for the team was on prevention, the so-called ‘left shift’ developments: catch and prevent lousy data issues from escalating earlier in the lifecycle, before it can cause any harm downstream.
3) Speed: From 0 to 1M in bookings in 2 quarters...
Building enterprise-grade software (and sales package) takes time. After 20 years in the venture business, the Sifflet team proved to us the impossible possible in the enterprise world. One month out of stealth, they onboarded the first big enterprise accounts. More enterprise clients and fast-growing startups were quickly joining.
More impressive than the number of accounts, was the variety. Every industry is engaged, no matter the data architecture... The flywheel was spinning: more industries, more integrations, more data...
4) Product Excellence:
The idea was born from the founder's frustration working previously with data at world-leading tech and financial organisations. They knew exactly what they wanted to create. I remember well when, a few months after investing, the founders called me up and said: ‘We need one more quarter before we can launch; the product is not good enough, just yet..’. The product vision was clear out of the gate. These founders would never settle for anything less than excellence.
5) A Human Twist:
We love getting early into ventures, often pre-product launches. In the case of Sifflet, the product was in stealth mode in 2021. What made us jump on this opportunity? Besides the vision and team, it was the first product demo with a ‘human touch’ by the founders. Regardless of the complexity, they showed me a product I could have used on the spot. This was special. When I asked them why they were so obsessed with the end-user UX so early, the reply was: ‘Well, data is the core of any business, so any person in a business should be able to check it out anytime and signal potential threats… Only then are we really full-stack’. In other words, no questions should be left unanswered. Here a slide from their very first pitch deck:
You rarely come across these opportunities in venture. When you do, you need to jump on it. Supporting this team in its journey to building a new software category leader is a privilege... Onwards!
Two weeks ago, I had the chance to hang out with the On Running 'gang' in Switzerland. Here is a pic with their first investor Philippe. I love the company's startup story - contrarian in so many ways... Did the world need another sneaker brand? A global consumer success story out of the Alps? Offline first, not an online GTM. A weird but great and strong management structure and culture, etc. More on this later this year.
Life is awesome,
Yannick
Other content I found useful- Our company Enstack closes its Series A. Enstack is on a mission to digitize micro businesses in SEA.
- Have a look at our latest investment, Finmatics in Austria. Finmatics is a B2B SaaS company that aims to automate all accounting processes for accounting firms and enterprise finance departments.
- Excellent thread by Samir on venture debt. Venture debt is by no means 'free' cash. 'This wasn't a big deal most of the last decade as rounds were coming together with no problem. But there will be many tense lender/founder/investor discussions in the next couple of years...' A great complement to our previous post on Safes.
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