Personal blog of Yzmir Ramirez

Quantum Machines, an Israeli startup that is building the classical hardware and software infrastructure to help run quantum machines, announced a $50 million Series B investment today.

Today’s round was led by Red Dot Capital Partners with help from Exor, Claridge Israel, Samsung NEXT, Valor Equity Partners, Atreides Management, LP, as well as TLV Partners, Battery Ventures, 2i Ventures and other existing investors. The company has now raised approximately $83 million, according to Crunchbase data.

While quantum computing in general is in its early days, Quantum Machines has developed a nice niche by building a hardware and software system, what they call The Quantum Orchestration Platform, that helps run the burgeoning quantum machines, leaving it plenty of room to grow as the industry develops.

Certainly Quantum Machines co-founder and CEO Itamar Sivan, who has been working in quantum his entire career, sees the vast potential of this technology. “Quantum computers have the promise of potentially speeding up very substantially computations that are impossible to complete in reasonable time with classical computers, and this is at the highest level the interest in the field right now. Our vision specifically at Quantum Machines is to make quantum computers ubiquitous and disruptive across all industries,” he said.

To achieve that, the company has created a system that relies on classical computers to power quantum computers as they develop. While the company has designed its own silicon for this purpose, it is important to note that it is not building quantum chips. As Sivan explains, the classical computer has a software and hardware layer, but quantum machines have three layers: “The quantum hardware, which is the heart, and on top of that you have classical hardware […] and then on top of that you have software,” he said.

“We focus on the two latter layers. So classical hardware and the software that drives it. Now at the heart of our hardware is in fact a classical processor. So this is I think one of the most interesting parts of the quantum stack,” he explained.

He says that this interaction between classical computing and quantum computing is one that is fundamental to the technology, and it’s a mix that will last well into the future, possibly forever. What Quantum Machines is building is essentially the classical cloud infrastructure required to run quantum computers.

Quantum Machines founding team: Itamar Sivan, Nissim Ofek, Yonatan Cohen. Photo Credit: Quantum Machines

So far the approach has been working quite well, as Sivan reports that governments, researchers, universities and the hyper scaler operators (which could include companies like Amazon, Netflix and Google, although the company has not said they are customers) are all interested in QM’s technology. While it isn’t discussing specific metrics, the company has customers in 15 countries at the moment and is working with some large entities that it couldn’t name.

The money from this round helps validate what the company is doing, enabling it to continue building out the solution, while also investing heavily in research and development, which is essential as the industry is still in early development and much will change over time.

They have been able to create this solution to this point with just 60 employees, and with the new funding should be able to build out the team in a substantial way in the coming years. He says that when it comes to diversity, he comes from an academic background where this is the norm and he has carried this forth to his company as he hires new people. What’s more, the pandemic has allowed him to hire from anywhere and he says that the company has taken advantage of this opportunity.

“First of all, we’re not hiring just in Israel, we’re hiring globally, and we’re not limited to hiring in specific geographies. We have people [from a number of countries],” he said. He adds, “Diversity for me personally means involving as many people as possible in hiring processes. That is the only way to ensure that there is diversity.”

Even throughout the pandemic, the hardware team has been meeting in person in the office with necessary precautions when it has been allowed, but most employees have continued to work from home, and that is an approach he will continue to take even when it’s safe to return to the office on a regular basis.

“Of course, work in a post-COVID era will include a substantial amount of remote work. […] So even in [our] headquarters, we anticipate allowing people to work remotely [if they wish].

Cisco announced on Friday that it’s acquiring Israeli applications-monitoring startup Epsagon at a price pegged at $500 million. The purchase gives Cisco a more modern microservices-focused component for its growing applications-monitoring portfolio.

The Israeli business publication Globes reported it had gotten confirmation from Cisco that the deal was for $500 million, but Cisco would not confirm that price with TechCrunch.

The acquisition comes on top of a couple of other high-profile app-monitoring deals, including AppDynamics, which the company bought in 2018 for $3.7 billion, and ThousandEyes, which it nabbed last year for $1 billion.

With Epsagon, the company is getting a way to monitor more modern applications built with containers and Kubernetes. Epsagon’s value proposition is a solution built from the ground up to monitor these kinds of workloads, giving users tracing and metrics, something that’s not always easy to do given the ephemeral nature of containers.

As Cisco’s Liz Centoni wrote in a blog post announcing the deal, Epsagon adds to the company’s concept of a full-stack offering in their applications-monitoring portfolio. Instead of having a bunch of different applications monitoring tools for different tasks, the company envisions one that works together.

“Cisco’s approach to full-stack observability gives our customers the ability to move beyond just monitoring to a paradigm that delivers shared context across teams and enables our customers to deliver exceptional digital experiences, optimize for cost, security and performance and maximize digital business revenue,” Centoni wrote.

That experience point is particularly important because when an application isn’t working, it isn’t happening in a vacuum. It has a cascading impact across the company, possibly affecting the core business itself and certainly causing customer distress, which could put pressure on customer service to field complaints, and the site reliability team to fix it. In the worst case, it could result in customer loss and an injured reputation.

If the application-monitoring system can act as an early warning system, it could help prevent the site or application from going down in the first place, and when it does go down, help track the root cause to get it up and running more quickly.

The challenge here for Cisco is incorporating Epsagon into the existing components of the application-monitoring portfolio and delivering that unified monitoring experience without making it feel like a Frankenstein’s monster of a solution globbed together from the various pieces.

Epsagon launched in 2018 and has raised $30 million. According to a report in the Israeli publication, Calcalist, the company was on the verge of a big Series B round with a valuation in the range of $200 million when it accepted this offer. It certainly seems to have given its early investors a good return. The deal is expected to close later this year.

Engineering teams face steep challenges when it comes to staying on schedule, and keeping to those schedules can have an impact on the entire organization. Acumen, an Israeli engineering operations startup, announced a $7 million seed investment today to help tackle this problem.

Hetz, 10D, Crescendo and Jibe participated in the round, designed to give the startup the funding to continue building out the product and bring it to market. The company, which has been working with beta customers for almost a year, also announced it was emerging from stealth today.

As an experienced startup founder, Acumen CEO and co-founder Nevo Alva has seen engineering teams struggle as they grow due to a lack of data and insight into how the teams are performing. He and his co-founders launched Acumen to give companies that missing visibility.

“As engineering teams scale, they face challenges due to a lack of visibility into what’s going on in the team. Suddenly prioritizing our tasks becomes much harder. We experience interdependencies [that have an impact on the schedule] every day,” Alva explained.

He says this manifests itself in a decrease in productivity and velocity and ultimately missed deadlines that have an impact across the whole company. What Acumen does is collect data from a variety of planning and communications tools that the engineering teams are using to organize their various projects. It then uses machine learning to identify potential problems that could have an impact on the schedule and presents this information in a customizable dashboard.

The tool is aimed at engineering team leaders, who are charged with getting their various projects completed on time with the goal of helping them understand possible bottlenecks. The software’s machine learning algorithms will learn over time which situations cause problems, and offer suggestions on how to prevent them from becoming major issues.

The company was founded in July 2019 and the founders spent the first 10 months working with a dozen design partners building out the first version of the product, making sure it could pass muster with various standards bodies like SOC-2. It has been in closed private beta since last year and is launching publicly this week.

Acumen currently has 20 employees with plans to add 10 more by the end of this year. After working remotely for most of 2020, Alva says that location is no longer really important when it comes to hiring. “It definitely becomes less and less important where they are. I think time zones are still a consideration when speaking of remote,” he said. In fact, they have people in Israel, the U.S. and eastern Europe at the moment among their 20 employees.

He recognizes that employees can feel isolated working alone, so the company has video meetings every day during which they spend the first part just chatting about non-work stuff as a way to stay connected. Starting today, Acumen will begin its go to market effort in earnest. While Alva recognizes there are competing products out there like Harness and Pinpoint, he thinks his company’s use of data and machine learning really helps differentiate it.

There’s a lot of complexity around managing data lakes in the cloud that often requires expensive engineering expertise. Upsolver, an early-stage startup, wants to simplify all of that, so that a database administrator could handle it. Today the startup announced a $13 million Series A.

Vertex Ventures US was lead investor, with participation from Wing Venture Capital and Jerusalem Venture Partners. Today’s investment brings the total raised to $17 million, according to the company.

Co-founder and CEO Ori Rafael says that as companies move data to the cloud and store it in data lakes, it becomes increasingly difficult to manage. The goal of Upsolver is to abstract away a lot of those management tasks and allow users to query the data using SQL, making it a lot more accessible.

“The main criticism of data lakes over the years is they become data swamps. It’s very easy to store data there very cheaply, but making it [easy to query] and valuable is hard. For that you need a lot of engineering, which turns the lake into a swamp. So we take the data that you put into a lake and make it easier to query, and we take the biggest disadvantage of using a lake, which is the complexity of doing that process, and we make that process easy,” Rafael explained.

Investor In Sik Rhee, who is general partner and co-founder at Vertex Ventures US, sees a company that’s creating a cloud-native standard for data lake computing. “Upsolver succeeded in abstracting away the engineering complexity of data pipeline management so that enterprise customers can quickly solve their modern data challenges in real time and at any scale without having to build another silo of expertise within the organization,” he said in a statement.

The company currently has 22 employees spread out between San Francisco, New York and Israel. Rafael says they hope to expand to 50 employees by the end of next year, including adding new engineers for their R&D center in Israel and building sales and customer success teams in the U.S.

Rafael says he and his co-founder sat down early on and wrote down the company’s core values, and they see a responsibility of running a diverse company as part of that, as they search for these new hires. Certainly the pandemic has shown them that they can hire from anywhere and that can help contribute to a more diverse workforce as they grow.

He said running the company and raising money has been stressful during these times, but the company has continued to grow through all of this, adding new customers while staying relatively lean, and Rafael says that the investors certainly recognized that.

“We had high revenue compared to the low number of employees with [sales] acceleration during COVID — that was our big trio,” he said.

As companies increasingly look to find ways to cut costs, Granulate, an early-stage Israeli startup, has come up with a clever way to optimize infrastructure usage. Today it was rewarded with a tidy $12 million Series A investment.

Insight Partners led the round with participation from TLV Partners and Hetz Ventures. Lonne Jaffe, managing director at Insight Partners, will be joining the Granulate board under the terms of the agreement. Today’s investment brings the total raised to $15.6 million, according to the company.

The startup claims it can cut infrastructure costs, whether on-prem or in the cloud, from between 20% and 80%. This is not insignificant if they can pull this off, especially in the economic maelstrom in which we find ourselves.

Asaf Ezra, co-founder and CEO at Granulate, says the company achieved the efficiency through a lot of studying about how Linux virtual machines work. Over six months of experimentation, they simply moved the bottleneck around until they learned how to take advantage of the way the Linux kernel operates to gain massive efficiencies.

It turns out that Linux has been optimized for resource fairness, but Granulate’s founders wanted to flip this idea on its head and look for repetitiveness, concentrating on one function instead of fair allocation across many functions, some of which might not really need access at any given moment.

“When it comes to production systems, you have a lot of repetitiveness in the machine, and you basically want it to do one thing really well,” he said.

He points out that it doesn’t even have to be a VM. It could also be a container or a pod in Kubernetes. The important thing to remember is that you no longer care about the interactivity and fairness inherent in Linux; instead, you want that the machine to be optimized for certain things.

“You let us know what your utility function for that production system is, then our agents. basically optimize all the decision making for that utility function. That means that you don’t even have to do any code changes to gain the benefit,” Ezra explained.

What’s more, the solution uses machine learning to help understand how the different utility functions work to provide greater optimization to improve performance even more over time.

Insight’s Jaffe certainly recognized the potential of such a solution, especially right now.

“The need to have high-performance digital experiences and lower infrastructure costs has never been more important, and Granulate has a highly differentiated offering powered by machine learning that’s not dependent on configuration management or cloud resource purchasing solutions,” Jaffe said in a statement.

Ezra understands that a product like his could be particularly helpful at the moment. “We’re in a unique position. Our offering right now helps organizations survive the downturn by saving costs without firing people,” he said.

The company was founded in 2018 and currently has 20 employees. They plan to double that by the end of 2020.

Anodot, a startup that helps customers monitor business operations against a set of KPIs, announced a $35 million Series C investment today.

Intel Capital led this round with a lot of help. New investors SoftBank Ventures Asia, Samsung NEXT and La Maison also participated along with existing investors Disruptive Technologies L.P., Aleph Venture Capital and Redline Capital. Today’s investment brings the total raised to $62.5 million, according to the company.

Anodot lets you take any kind of data, whatever your company finds important, and it tracks it automatically and reports on changes that would have an impact on the business, according to David Drai, CEO and co-founder.

“We take any kind of normalized data into our platform and learn all the behavior of the data against normal behavior. When I say normal behavior, it means any time-based data in what is called a time series. And we understand all the trends of that data, and we do this autonomously without any configuration, except defining what is interesting for you,” Drai explained.

That means that the platform will let you know, for example, of any drop in your business, any drop in your conversions, any spike in your costs — and so forth. What you track depends on your vertical and what’s important to your business.

He compares it to applications performance monitoring, but instead of monitoring the company’s technology systems, it’s monitoring the systems that run the business. Just as you don’t want to miss signals that your servers could be going down, neither do you want to let factors that could cost your business money go unnoticed.

This dashboard lets you monitor unusual changes in cloud costs. Image Credit: Anodot

The way it works is you connect to the systems that matter, and Anodot can review those systems, learn what constitutes a level of normal behavior, then identify when anomalies occur. It does this by mapping against your KPIs, and this can involve thousands or even tens of thousands of KPIs based on an individual company.

As Drai points out, an eCommerce company with 1000 products in 50 countries, will have 50,000 KPIs, one for each product in each country, and you can track these in Anodot.

He says that under the current economic conditions, he is taking a two-pronged approach to building his business involving both offense and defense. On defense, he will take a cautious approach to hiring, but he sees his product helping companies understand and control costs, so he will continue to sell the product as a cost-saving device at a time when that is of increasing importance to businesses everywhere.

The company was founded in 2014. It currently has 70 employees and 100 paying customers including Atlassian, T Mobile, Lyft and Pandora.

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 Alooma, an Israeli startup that helps companies process and work with big data in real time delivered as a cloud service, announced an $11.2 million Series A round today led by Lightspeed Venture Partners and Sequoia Capital. The product focuses on the people working with data like data scientists and end users with advanced degrees in mathematics and machine learning, rather than… Read More