Feb
24
2021
--

Acumen nabs $7M seed to keep engineering teams on track

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.

Jun
30
2020
--

Upsolver announces $13M Series A to ease management of cloud data lakes

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.

Apr
22
2020
--

Granulate announces $12M Series A to optimize infrastructure performance

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.

Apr
16
2020
--

Anodot grabs $35M Series C to help monitor business operations

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.

Nov
01
2016
--

Otonomo raises $12 million to make data from connected cars useful

connected-car Even if self-driving cars aren’t part of our daily lives yet, vehicles are becoming internet-connected at a rapid pace. Gartner predicts that one fifth of all autos on the road, and great majority of new vehicles being produced worldwide will have wireless network connectivity by 2020. Yet, few organizations have access to use the data generated by these vehicles today. That’s… Read More

Mar
14
2016
--

Alooma scores $11.2 million Series A to solve data science pain points

Data scientist in front of giant board with mathematical formulas. 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

Powered by WordPress | Theme: Aeros 2.0 by TheBuckmaker.com