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Fiberplane nabs €7.5M seed to bring Google Docs-like collaboration to incident response
Fiberplane, an Amsterdam-based early-stage startup that is building collaborative notebooks for SREs (site reliability engineers) to collaborate around an incident in a similar manner to group editing in a Google Doc, announced a €7.5 million (approximately $8.8 million USD) seed round today.
The round was co-led by Crane Venture Partners and Notion Capital, with participation from Northzone, System.One and Basecase Capital.
Micha Hernandez van Leuffen (known as Mies) is founder and CEO at Fiberplane. When his previous startup, Werker, was sold to Oracle in 2017, Hernandez van Leuffen became part of a much larger company where he saw people struggling to deal with outages (which happen at every company).
“We were always going back and forth between metrics, logs and traces, what I always call this sort of treasure hunt, and figuring out what was the underlying root cause of an outage or downtime,” Hernandez van Leuffen told me.
He said that this experience led to a couple of key insights about incident response: First, you needed a centralized place to pull all the incident data together, and secondly that as a distributed team managing a distributed system you needed to collaborate in real time, often across different time zones.
When he left Oracle in August 2020, he began thinking about the idea of giving DevOps teams and SREs the same kind of group editing capabilities that other teams inside an organization have with tools like Google Docs or Notion and an idea for his new company began to take shape.
What he created with Fiberplane is a collaborative notebook for SRE’s to pull in the various data types and begin to work together to resolve the incident, while having a natural audit trail of what happened and how they resolved the issue. Different people can participate in this notebook, just as multiple people can edit a Google Doc, fulfilling that original vision.
Fiberplane collaborative notebook example with multiple people involved. Image Credit: Fiberplane
He doesn’t plan to stop there though. The longer-term vision is an operational platform for SREs and DevOps teams to deal with every aspect of an outage. “This is our starting point, but we are planning to expand from there as more I would say an SRE workbench, where you’re also able to command and control your infrastructure,” he said.
Today the company has 13 employees and is growing, and as they do, they are exploring ways to make sure they are building a diverse company, looking at concrete strategies to find more diverse candidates.
“To hire diversely, we’re re-examining our top of the funnel processes. Our efforts include posting our jobs in communities of underrepresented people, running our job descriptions through a gender decoder and facilitating a larger time frame for jobs to remain open,” Elena Boroda, marketing manager at Fiberplane said.
While Hernandez van Leuffen is based in Amsterdam, the company has been hiring people in the U.K., Berlin, Copenhagen and the U.S., he said. The plan is to have Amsterdam as a central hub when offices reopen as the majority of employees are located there.
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Adyen alumni raise €2.6M seed to launch Silverflow, a ‘cloud-native’ card payments processor
Silverflow, a Dutch startup founded by Adyen alumni, is breaking cover and announcing seed funding.
The pre-launch company has spent the last two years building what it describes as a “cloud-native” online card processor that directly connects to card networks. The aim is to offer a modern replacement for the 20 to 40-year-old payments card processing tech that is mostly in use today.
Backing Silverflow’s €2.6 million seed round is U.K.-based VC Crane Venture Partners, with participation from Inkef Capital and unnamed angel investors and industry leaders from Pay.On, First Data, Booking.com and Adyen. It brings the fintech startup’s total funding to date to ~€3 million.
Bootstrapped while in development and launching in 2021, Silverflow’s founders are CEO Anne-Willem de Vries (who was focused on card acquiring and processing at Adyen), CBDO Robert Kraal (former Adyen COO and EVP global card acquiring & processing of Adyen) and CTO Paul Buying (founder of acquired translation startup Livewords).
“The payments tech stack needs an upgrade,” Kraal tells me. “Today’s card payment infrastructure based on 30 to 40-year-old technology is still in use across the global payment landscape. This legacy infrastructure is costing everyone time and money: consumers, merchants, payment-service-providers and banks. The legacy platforms require a lengthy on-boarding process and are expensive to maintain, [and] they also aren’t fit for purpose today because they don’t support data use”.
In addition, Kraal says that adding new functionality is a lengthy and expensive process, requiring the effort of specialised engineers which ultimately slows down innovation “for the whole card payments system”.
“Finally, every acquirer provides its customer with a different processing platform, which for a typical payment service provider (PSP) means they have to deal with multiple legacy platforms — and all the costs and specialised support each entails,” adds de Vries.
To solve this, Silverflow claims it has built the first payments processor with a “cloud-native platform” built for today’s technology stack. This includes offering simple APIs and “streamlined data flows” directly integrated into the card networks.
Continues de Vries: “Instead of managing a complex network of acquirers across markets with dozens of bank and card network connections to maintain, Silverflow provides card-acquiring processing as a service that connects to card networks directly through a simple API”.
Target customers are PSPs, acquirers and “global top-market merchants” that are seeing €500 million to 10 billion in annual transactions.
“As a managed service, Silverflow provides the maintenance for connections and new product innovation that users have typically had to support in-house or work on long-term product road maps with suppliers,” explains Kraal. “Based in the cloud, Silverflow is infinitely scalable for peak flows and also provides robust data insights that users haven’t previously been able to access”.
With regards to competitors, Kraal says there are no other companies at the moment doing something similar, “as far as we are aware”. Currently, acquirers use traditional third-party processors, such as SIA, Omnipay, Cybersource or MIGS. Some companies, like Adyen, have built their own in-house processing platform.
So, why hasn’t a cloud-native card processing platform like Silverflow been done before and why now? A lack of awareness of the problem might be one reason, says de Vries.
“Unless you have built several integrations to acquirers during your career, you are not aware that the 30 to 40-years-old infrastructure is still in use. This is not typically a problem some bright college graduates would tackle,” he posits.
“Second, to build this successfully, you need to have prior knowledge of the card payments industry to navigate all the legal, regulatory and technical requirements.
“Thirdly, any large corporate currently active in card payment processing will be aware of the problem and have the relevant industry knowledge. However, building a new processing platform would require them to allocate their most talented staff to this project for two-three years, taking away resources from their existing projects. In addition, they would also need to manage a complex migration project to move their existing customers from their current system to the new one and risk losing some of the customers along the way”.
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Data startup Axiom secures $4M from Crane Venture Partners, emerges from stealth
Axiom, a startup that helps companies deal with their internal data, has secured a new $4 million seed round led by U.K.-based Crane Venture Partners, with participation from LocalGlobe, Fly VC and Mango Capital. Notable angel investors include former Xamarin founder and current GitHub CEO Nat Friedman and Heroku co-founder Adam Wiggins. The company is also emerging from a relative stealth mode to reveal that is has now raised $7 million in funding since it was founded in 2017.
The company says it is also launching with an enterprise-grade solution to manage and analyze machine data “at any scale, across any type of infrastructure.” Axiom gives DevOps teams a cloud-native, enterprise-grade solution to store and query their data all the time in one interface — without the overhead of maintaining and scaling data infrastructure.
DevOps teams have spent a great deal of time and money managing their infrastructure, but often without being able to own and analyze their machine data. Despite all the tools at hand, managing and analyzing critical data has been difficult, slow and resource-intensive, taking up far too much money and time for organizations. This is what Axiom is addressing with its platform to manage machine data and surface insights, more cheaply, they say, than other solutions.
Co-founder and CEO Neil Jagdish Patel told TechCrunch: “DevOps teams are stuck under the pressure of that, because it’s up to them to deliver a solution to that problem. And the solutions that existed are quite, well, they’re very complex. They’re very expensive to run and time-consuming. So with Axiom, our goal is to try and reduce the time to solve data problems, but also allow businesses to store more data to query at whenever they want.”
Why did they work with Crane? “We needed to figure out how enterprise sales work and how to take this product to market in a way that makes sense for the people who need it. We spoke to different investors, but when I sat down with Crane they just understood where we were. They have this razor-sharp focus on how they get you to market and how you make sure your sales process and marketing is a success. It’s been beneficial to us as were three engineers, so you need that,” said Patel.
Commenting, Scott Sage, founder and partner at Crane Venture Partners added: “Neil, Seif and Gord are a proven team that have created successful products that millions of developers use. We are proud to invest in Axiom to allow them to build a business helping DevOps teams turn logging challenges from a resource-intense problem to a business advantage.”
Axiom co-founders Neil Jagdish Patel, Seif Lotfy and Gord Allott previously created Xamarin Insights that enabled developers to monitor and analyse mobile app performance in real time for Xamarin, the open-source cross-platform app development framework. Xamarin was acquired by Microsoft for between $400 and $500 million in 2016. Before working at Xamarin, the co-founders also worked together at Canonical, the private commercial company behind the Ubuntu Project.
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TriggerMesh scores $3M seed from Index and Crane to help enterprises embrace ‘serverless’
TriggerMesh, a startup building on top of the open-source Kubernetes software to help enterprises go “serverless” across apps running in the cloud and traditional data centers, has raised $3 million in seed funding.
The round is led by Index Ventures and Crane Venture Partners. TriggerMesh says the investment will be used to scale the company and grow its development team in order to offer what it bills as the industry’s first “cloud native integration platform for the serverless era.”
Founded by two prominent names in the open-source community — Sebastien Goasguen (CEO) and Mark Hinkle (CMO), based in Geneva and North Carolina, respectively — TriggerMesh’s platform will enable organizations to build enterprise-grade applications that span multiple cloud and data center environments, therefore helping to address what the startup says is a growing pain point as serverless architectures become more prevalent.
TriggerMesh’s platform and serverless cloud bus is said to facilitate “application flow orchestration” to consume events from any data center application or cloud event source and trigger serverless functions.
“As cloud-native applications use a greater number of serverless offerings in the cloud, TriggerMesh provides a declarative API and a set of tools to define event flows and functions that compose modern applications,” explains the company.
One feature TriggerMesh is specifically talking up and very relevant to legacy enterprises is its integration functionality with on-premise software. Via its wares, it says it is easy to connect SaaS, serverless cloud offerings and on-premises applications to provide scalable cloud-native applications at a low cost and quickly.
“There are huge numbers of disconnected applications that are unable to fully benefit from cloud computing and increased network connectivity,” noted Scott Sage, co-founder and partner at Crane Venture Partners, in a statement. “Most companies have some combination of cloud and on-premises applications and with more applications around, often from different vendors, the need for integration has never been greater. We see TriggerMesh’s solution as the ideal fit for this need which made them a compelling investment.”
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Forecast raises $5.5M for its ‘AI-powered’ project management software
Forecast, a Denmark-based startup that has developed “AI-powered” project management software, has raised $5.5 million in new funding.
The round is led by Crane Venture Partners, with participation from existing backers SEED Capital and Heartcore. Forecast has raised $10 million in total funding to date.
Founded in late 2016, Forecast describes itself as an AI-powered project management solution that automates manual project management tasks, and brings extra visibility and predictive capabilities to project management. The idea is to help increase collaboration across teams with a better workflow and to improve planning.
Forecast claims that by using its project management software, customers reduce their administrative tasks by 20-40% and gain much better insights into “project risk, resource management and more.”
“Work is going more project-based… leading to an increased need for project management skills and expertise,” Forecast co-founder and CEO Dennis Kayser tells TechCrunch. “Plus, projects are getting more complex. Project management depends on many manual, ongoing updates to stay on time, on budget and on track. That’s why 66% of all projects fail due to human error.”
In addition, as projects become more complex and the data associated with a project increases exponentially, Kayser says the problem is getting worse, which, of course, is where machine intelligence can help. “We don’t learn from our mistakes because no one can keep track of every influencing factor to make crucial adjustments,” he adds.
To tackle this, Forecast uses AI to help keep projects on track and make project management more efficient. The software integrates with existing tools — such as Trello, Slack, Gdrive, Githum and Salesforce — and uses these various external data-points as key indicators for how well a project is running.
“[It pulls in] data from disparate systems and synthesizes it into something human-readable with powerful AI,” explains Kayser. “Everyone on your team can continue to use the tool they prefer without sacrificing dead-simple scheduling, reporting and collaboration for project managers and senior executives. With better insights and tools, project managers can be more efficient and gain insights from increasingly complex projects.”
The use of AI is proactive, too. This includes matching the best person and role to the task, automation of time registration, forecasting the size and duration of tasks and being alerted before a project is in trouble.
With regards to target customers, Kayser says that Forecast is focused on helping IT & services, marketing and computer software development companies that “rely on capacity being predictable and project delivery being successful.”
Forecast currently has “hundreds of customers” in more than 40 countries. The software has helped customers manage more than 40,000 projects with more than 1,000,000 tasks created.
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Out of stealth, Stratio emerges with predictive AI to stop your bus from breaking down
Remember that future we were promised where our vehicle magically tells us that we’re about to break down? Or actually never does? Or that the pickup truck arrives before the driver even knows something is wrong? That future is arriving. But like many things, the practical reality is that this technology starts to arrive in the fleet management industry before it arrives for consumers.
The market for maintenance of fleets of buses and trucks is worth $200 billion in annual expenditure, so as you can imagine, it’s a juicy sector to get into. In Portugal, a team of entrepreneurs and scientists assembled to look into this and came up with a fascinating startup that is now attracting the attention of investors.
Today, Stratio is emerging from stealth to help OEMs, distributors and fleets benefit from AI-driven predictive intelligence.
The idea is to apply machine learning models that retrieve and analyze millions of data points per vehicle per day to vehicles both in development and on the road. It turns out that if you compare the real versus the expected behaviour of the actual vehicle components themselves, you can improve automated testing and predictive intelligence that can assess the vehicle’s condition. Then you can detect early anomalies and failures. This is exactly what Stratio does.
It does this by putting a sensor box-of-tricks under a vehicle, like a bus. This box connects with existing sensors in the vehicle using the existing API — something crucial for OEMs. Using proprietary machine learning, it can predict when something will break, days ahead of time. Most existing boxes like this only track location, not analytics.
Stratio also works with OEMs during the vehicle testing phase to identify issues and their root cause to get more reliable vehicles to market faster, lower the potential for warranty claim fraud costs and expand the after-sales revenues. It’s a triple whammy in cost savings.
Stratio has now attracted a $3.5 million VC round from London-based Crane VC, with participation from fellow London VC, LocalGlobe.
The round is one of the largest ever seed deals in Portugal and potentially the largest enterprise/deep tech first investment in the country.
It has a proprietary AI engine, Stratio CortexTM, and technology support from the European Space Agency. Ultimately the aim is to apply machine learning models and enable the so-called “zero downtime” future.
Rui Sales and Ricardo Margalho, co-founders of Stratio, say the idea for Stratio came to them when their bus broke down and they missed what could have been a career-changing meeting in New York: “Knowing that today’s existing vehicles produce a massive amount of data, we set out to build a machine learning product suite that analyses high-density vehicle data in real time to predict and prevent vehicles from breaking down.”
Stratio launched in 2017, after receiving technological support from the European Space Agency and earning recognition from the EU Commission.
Alongside the co-founders is Rune Prytz, a former Volvo Trucks research engineer in machine learning and big data, who now leads all of Stratio’s efforts in AI. Stratio now counts MAN, DAF Trucks and VECTIA as customers, among others.
Krishna Visvanathan, partner at Crane Venture Partners, commented, “Stratio Automotive is one of the most exciting companies in our portfolio of data-driven enterprise software businesses. It has the trifecta of a super product, a deep data moat coupled with AI expertise and great customer traction.”
So far, Stratio has attracted customers and operations in more than 10 key markets across Europe, the U.K., U.S., India and Singapore.
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