Point72 Ventures
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Fylamynt, a new service that helps businesses automate their cloud workflows, today announced both the official launch of its platform as well as a $6.5 million seed round. The funding round was led by Google’s AI-focused Gradient Ventures fund. Mango Capital and Point72 Ventures also participated.
At first glance, the idea behind Fylamynt may sound familiar. Workflow automation has become a pretty competitive space, after all, and the service helps developers connect their various cloud tools to create repeatable workflows. We’re not talking about your standard IFTTT- or Zapier -like integrations between SaaS products, though. The focus of Fylamynt is squarely on building infrastructure workflows. While that may sound familiar, too, with tools like Ansible and Terraform automating a lot of that already, Fylamynt sits on top of those and integrates with them.
“Some time ago, we used to do Bash and scripting — and then [ … ] came Chef and Puppet in 2006, 2007. SaltStack, as well. Then Terraform and Ansible,” Fylamynt co-founder and CEO Pradeep Padala told me. “They have all done an extremely good job of making it easier to simplify infrastructure operations so you don’t have to write low-level code. You can write a slightly higher-level language. We are not replacing that. What we are doing is connecting that code.”
So if you have a Terraform template, an Ansible playbook and maybe a Python script, you can now use Fylamynt to connect those. In the end, Fylamynt becomes the orchestration engine to run all of your infrastructure code — and then allows you to connect all of that to the likes of DataDog, Splunk, PagerDuty Slack and ServiceNow.
The service currently connects to Terraform, Ansible, Datadog, Jira, Slack, Instance, CloudWatch, CloudFormation and your Kubernetes clusters. The company notes that some of the standard use cases for its service are automated remediation, governance and compliance, as well as cost and performance management.
The company is already working with a number of design partners, including Snowflake.
Fylamynt CEO Padala has quite a bit of experience in the infrastructure space. He co-founded ContainerX, an early container-management platform, which later sold to Cisco. Before starting ContainerX, he was at VMWare and DOCOMO Labs. His co-founders, VP of Engineering Xiaoyun Zhu and CTO David Lee, also have deep expertise in building out cloud infrastructure and operating it.
“If you look at any company — any company building a product — let’s say a SaaS product, and they want to run their operations, infrastructure operations very efficiently,” Padala said. “But there are always challenges. You need a lot of people, it takes time. So what is the bottleneck? If you ask that question and dig deeper, you’ll find that there is one bottleneck for automation: that’s code. Someone has to write code to automate. Everything revolves around that.”
Fylamynt aims to take the effort out of that by allowing developers to either write Python and JSON to automate their workflows (think “infrastructure as code” but for workflows) or to use Fylamynt’s visual no-code drag-and-drop tool. As Padala noted, this gives developers a lot of flexibility in how they want to use the service. If you never want to see the Fylamynt UI, you can go about your merry coding ways, but chances are the UI will allow you to get everything done as well.
One area the team is currently focusing on — and will use the new funding for — is building out its analytics capabilities that can help developers debug their workflows. The service already provides log and audit trails, but the plan is to expand its AI capabilities to also recommend the right workflows based on the alerts you are getting.
“The eventual goal is to help people automate any service and connect any code. That’s the holy grail. And AI is an enabler in that,” Padala said.
Gradient Ventures partner Muzzammil “MZ” Zaveri echoed this. “Fylamynt is at the intersection of applied AI and workflow automation,” he said. “We’re excited to support the Fylamynt team in this uniquely positioned product with a deep bench of integrations and a nonprescriptive builder approach. The vision of automating every part of a cloud workflow is just the beginning.”
The team, which now includes about 20 employees, plans to use the new round of funding, which closed in September, to focus on its R&D, build out its product and expand its go-to-market team. On the product side, that specifically means building more connectors.
The company offers both a free plan as well as enterprise pricing and its platform is now generally available.
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Toro’s founders started at Uber helping monitor the data quality in the company’s vast data catalogs, and they wanted to put that experience to work for a more general audience. Today, the company announced a $4 million seed round.
The round was co-led by Costanoa Ventures and Point72 Ventures, with help from a number of individual investors.
Company co-founder and CEO Kyle Kirwan says the startup wanted to bring to data the kind of automated monitoring we have in applications performance monitoring products. Instead of getting an alert when the application is performing poorly, you would get an alert that there is an issue with the data.
“We’re building a monitoring platform that helps data teams find problems in their data content before that gets into dashboards and machine learning models and other places where problems in the data could cause a lot of damage,” Kirwan told TechCrunch.
When it comes to data, there are specific kinds of issues a product like Toro would be looking at. It might be a figure that falls outside of a specific dollar range that could be indicative of fraud, or it could be simply a mistake in how the data was labeled that is different from previous ways that could break a model.
The founders learned the lessons they used to build Toro while working on the data team at Uber. They had helped build tools there to find these kinds of problems, but in a way that was highly specific to Uber. When they started Toro, they needed to build a more general-purpose tool.
The product works by understanding what it’s looking at in terms of data, and what the normal thresholds are for a particular type of data. Anything that falls outside of the threshold for a particular data point would trigger an alert, and the data team would need to go to work to fix the problem.
Casey Aylward, vice president at Costanoa Ventures, likes the pedigree of this team and the problem it’s trying to solve. “Despite its importance, data quality has remained a challenge for many enterprise companies,” she said in a statement. She added, “[The co-founders] deep experience building several of Uber’s internal data tools makes them uniquely qualified to build the best solution.”
The company has been at this for just over a year and has been keeping it lean with four employees, including the two co-founders, but they do have plans to add a couple of data scientists in the coming year as they continue to build out the product.
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Toggle, a Brooklyn-based robotics startup, announced today that it scored $3 million in seed funding. The early-stage round was led by Point72 Ventures’ AI Group, with participation from Mark Cuban and VC Twenty Seven Ventures. The series follows a 2018 pre-seed round of $570,000 from its Urban-X accelerator, Urban Us, Accelerate NY / Empire State Development and Perl Street Capital.
The 15-person startup creates robotics that fabricate and assemble rebar. It’s designed to work in tandem with existing robotics and steel fabrication technologies, while speeding up the process up to 5 times, by the company’s count.
Toggle has already begun a soft launch “for a wide range of projects in New York City and the surrounding area,” according to the company. It expects to ramp up toward commercial production over the course of the next year and a half. CEO Daniel Blank tells TechCrunch that the seed round will be used toward R&D and growing the Toggle team.
“This funding will be used to further develop our technology — both the hardware and software — around assembly and fabrication automation, as well as grow the engineering team that supports this development,” Blank tells TechCrunch. “The funding also provides us with a strong foundation for our manufacturing operation which is already supplying services and materials to customers in New York City and the surrounding region.”
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Financial service companies like banks have seen some of their business cannibalised over the years with the rise of digital-based alternatives — often in the form of apps — that provide lower fees, faster responsiveness and more flexibility to consumers. Today, Toronto-based startup Flybits is announcing $35 million in funding for a platform that it believes can offer these banks a way of continuing to capture their users’ attention and help them pivot into the next generation of services, financial or otherwise.
Today, a typical end product for a customer of Flybits’ services will use insights to upsell a customer by offering financial services; for example, a bank providing an offer of a specific kind of loan or credit card that you are more likely to take; or to offer a loyalty program or rewards for usage. But the longer-term goal, said CEO and co-founder Hossein Rahnama, is to help its customers take on a bigger role as repositories that can be used for more than just money, and used beyond the walls of the bank.
“We don’t think banks will go away, as some do, but we think that they could have a role not just as money vaults, but as data vaults: a place where you can deposit data, which you trust,” he said in an interview. Indeed, some of the funding will be used to put into action some of the AI and machine learning patents the startup has amassed, with the building of a “data” marketplace for banks, fintechs and other data providers to partner and build more services together.
The Series C comes from an interesting group of investors that includes both strategic backers using Flybits’ services, as well as backers of the more non-strategic, financial kind. Led by Point72 Ventures (hedge fund supremo Steve Cohen’s VC fund), the list also includes Mastercard, Citi Ventures and Reinventure (the fund backed by Australia’s Westpac Banking Corporation), Portag3 Ventures, TD Bank and Information Venture Partners. Valuation is not being disclosed, and prior to this the company had raised around $15 million.
Much like another marketing tech company, Near — which today announced $100 million in funding — the premise that underpins Flybits’ technology is that there is a lot of disparate data out there that, if it’s treated correctly, can uncover a lot more insights about consumer behavior, and that by and large many companies are missing this opportunity because they haven’t found the right way of merging the data to unlock insights.
While Near is applying this to location-based data and a range of different verticals, Flybits’ primary target has been banks and the data that they and other financial services providers already possess.
Many smaller startups in the world of financial services have stolen a march on bigger incumbents by building personalization into their products from the ground up. (Indeed, some like Step, aimed at teens, are so personalised that they will actually change their service mix as their customer base grows up and needs new products.) This is something that incumbents might have been more readily able to do in the old days, when people knew their bank managers and tellers and made daily trips into branches to transact. In the digital age they have fallen behind and are now catching up.
Flybits’ investors have spotted that and this in part is why they are banking on technologies like this to help bigger companies catch up, not just in financial services (although with banking alone estimated to be a €6.9 trillion industry, this is clearly a good start).
“Personalization is mission-critical for all D2C businesses in the digital age. Flybits’ integrated platform allows financial services firms to offer contextualized experiences, driving product awareness and adding significant value to the lives of their customers,” said Ramneek Gupta, managing director and co-head of Venture Investing at Citi Ventures, in a statement. “We look forward to partnering with Flybits in its next phase of growth as it continues to set the bar for hyper-personalized customer experiences.”
Indeed, it’s not just banks that are working on upselling, or that have large repositories of data that are not used as well as they could be.
“Mastercard and Flybits share a vision on using data driven insights to enrich consumers’ experiences,” said Francis Hondal, president, Loyalty & Engagement at Mastercard, in a statement. “Our ultimate goal is to develop products and services that engage consumers in a highly contextual manner. Through this collaboration with Flybits, we’ll be able to offer rich, personalized experiences for them throughout their journeys.”
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