Hi – I’m joining a one person startup as a co-founder. What would be my best route to proceed with health insurance for me and my family? Should I get a private plan to cover us? Or should I negotiate for our startup to develop an insurance plan that I can use for my coverage? And what are some good resources for either option? Just not sure where to start other than Googling away really. Thanks!
When a system outage happens, chaos can ensue as the team tries to figure out what’s happening and how to fix it. StackPulse, a new startup that wants to help developers manage these crisis situations more efficiently, emerged from stealth today with a $ 28 million investment.
The round actually breaks down to a previously unannounced $ 8 million seed investment and a new $ 20 million Series A. GGV led the A round, while Bessemer Venture Partners led the seed and also participated in the A. Glenn Solomon at GGV and Amit Karp at Bessemer will join the StackPulse board.
Nobody is immune to these outages. We’ve seen incidents from companies as varied as Amazon and Slack in recent months. The biggest companies like Google, Facebook and Amazon employ site reliability engineers and build customized platforms to help remediate these kinds of situations. StackPulse hopes to put this kind of capability within reach of companies, whose only defense is the on-call developers.
Company co-founder and CEO Ofer Smadari says that in the midst of a crisis with signals coming at you from Slack and PagerDuty and other sources, it’s hard to figure out what’s happening. StackPulse is designed to help sort out the details to get you back to equilibrium as quickly as possible.
First off, it helps identify the severity of the incident. Is it a false alarm or something that requires your team’s immediate attention or something that can be put off for a later maintenance cycle. If there is something going wrong that needs to be fixed right now, StackPulse can not only identify the source of the problem, but also help fix it automatically, Smadari explained.
After the incident has been resolved, it can also help with a post mortem to figure out what exactly went wrong by pulling in all of the alert communications and incident data into the platform.
As the company emerges from stealth, it has some early customers and 35 employees based in Portland, Oregon and Tel Aviv. Smadari says that he hopes to have 100 employees by the end of this year. As he builds the organization, he is thinking about how to build a diverse team for a diverse customer base. He believes that people with diverse backgrounds build a better product. He adds that diversity is a top level goal for the company, which already has an HR leader in place to help.
Glenn Solomon from GGV, who will be joining the company board, saw a strong founding team solving a big problem for companies and wanted to invest. “When they described the vision for the product they wanted to build, it made sense to us,” he said.
Customers are impatient with down time and Solomon sees developers on the front line trying to solve these issues. “Performance is more important than ever. When there is downtime, it’s damaging to companies,” he said. He believes StackPulse can help.
LatticeFlow, an AI startup that was spun out of ETH Zurich in 2020, today announced that it has raised a $ 2.8 million seed funding round led by Swiss deep-tech fund btov and Global Founders Capital, which previously backed the likes of Revolut, Slack and Zalando.
The general idea behind LatticeFlow is to build tools that help AI teams build and deploy AI models that are safe, reliable and trustworthy. The problem today, the team argues, is that models get very good at finding the right statistical patterns to hit a given benchmark. That makes them inflexible, though, since these models were optimized for accuracy in a lab setting, not for robustness in the real world.
“One of the most commonly used paradigms for evaluating machine learning models is just aggregate metrics, like accuracy. And, of course, this is a super coarse representation of how good a model really is,” Pavol Bielik, the company’s CTO explained. “What we want to do is, we provide systematic ways of monitoring models, assessing their reliability across different relevant data slices and then also provide tools for improving these models.”
Building these kinds of models that are more flexible yet still provide robust results will take a new arsenal of tools, though, as well as the right team with deep expertise in these areas. Clearly, though, this is a founding team with the right background. In addition to CTO Bielik, the founding team includes Petar Tsankov, the company’s CEO and former senior researcher and lecturer at ETH Zurich, as well as ETH professors Martin Vechev, who leads the Secure, Reliable and Intelligence Systems lab at ETH, and Andreas Krause, who leads ETH’s Learning & Adaptive Systems lab. Tsankov’s last startup, DeepCode, was acquired by cybersecurity firm Snyk in 2020.
It’s also worth noting that Vechev, who previously co-founded ETH spin-off ChainSecurity, and his group at ETH previously developed ERAN, a verifier for large deep learning models with millions of parameters, that last year won the first competition for certifying deep neural networks. While the team was already looking at creating a company before winning this competition, Vechev noted that gave the team the confirmation that it was on the right path.
“We want to solve the main AI problem, which is making AI usable. This is the overarching goal,” Vechev told me. “[…] I don’t think you can actually found the company just purely based on the certification work. I think the kinds of skills that people have in the company, my group, Andreas [Krause]’s group, they all complement each other and cover a huge space, which I think is very, very unique. I don’t know of other companies who have covered this range of skills in these pressing points and have done groundbreaking work before.”
LatticeWorks already has a set of pilot customers who are trialing its tools. These include Swiss railways (SBB), which is using it to build a tool for automatic rail inspections, Germany’s Federal Cyber Security Bureau and the U.S. Army. The team is also working with other large enterprises that are using its tools to improve their computer vision models.
“Machine Learning (ML) is one of the core topics at SBB, as we see a huge potential in its application for an improved, intelligent and automated monitoring of our railway infrastructure,” said Dr. Ilir Fetai and Andre Roger, the leads of SBB’s AI team. “The project on robust and reliable AI with LatticeFlow, ETH, and Siemens has a crucial role in enabling us to fully exploit the advantages of using ML.”
For now, LatticeFlow remains in early access. The team plans to use the funding to accelerate its product development and bring on new customers. The team also plans to build out a presence in the U.S. in the near future.
To minimise the spread of COVID-19, many schools, across the world, have shut down and remote learning has become the only solution to move forward. Many edtech startups have stepped up their game to help teachers, students, and parents to navigate the “new normal” of teaching. The same is just as true in the corporate world, with companies not only having to transition to remote work, but also to figure out how to coach and upskill their workforce. This is where Sweden-based Sana Labs wants to make the difference.
Sana Labs raises €14.9M
In a recent development, the Stockholm-based Sana Labs, a startup that uses artificial intelligence (AI) to personalise training courses for professionals, has raised $ 18M (approx €14.9M) in its series A round of funding.
With this round, the startup has raised a total of $ 23M (approx €19M) in funding, to date.
Investors in this round
The round was led by EQT Ventures. Joel Hellermark, founder of Sana Labs says, “I first met EQT Venture partner Ted Persson when I was interning at Great Works back in 2010. A pioneer in technology, product design, and branding, Ted has been a hero ever since. Thus, I couldn’t be more excited to partner with Ted, former Spotify VP of Analytics Henrik Landgren, former founder Sandra Malmberg, and the rest of the EQT team.”
Use of the raised capital
The Sweden-based company says it will use the funds to boost headcount and sales-focused marketing. In addition, the funds will also be invested in R&D for its platform, which uses machine learning to personalise programmes to a person’s individual learning style and ability.
About Sana Labs
Founded in 2016 by Joel Hellermark, Sana Labs have developed a personalised, adaptive learning platform that enables organisations to accelerate training across the workplace.
The company applies machine-learning to tailor reskilling and upskilling, with the aim of accelerating time to mastery, improving engagement, and delivering rich learning analytics.
It claims to partner with Fortune 500 organisations to bring the benefits of AI to millions of learners. Its team consists of researchers and engineers with backgrounds ranging from Google AI and Spotify to BCG Gamma and Imperial College.
“We believe in educational empowerment”
According to the company, the global learning industry is vast, valued at over $ 6T in 2018, and is undergoing a sea-change with the move to digital and online instruction, materials, and modalities. The shift to digital and online resources is enabling what many educators consider to be the holy grail of learning – personalised, adaptive instruction and assessment.
With the Sana platform, the company aims to be the engine that drives this change forward – fundamentally improving the entire industry’s capability to educate and directly impacting millions of peoples’ lives every day.
The company also mentioned in its website that about 2,000 hospitals have adopted the Sana platform to provide efficient skill development to more than 80,000 healthcare professionals in the treatment and prevention of COVID-19. This was done by analysing each nurse’s knowledge gap and personalised the learning path accordingly.
Besides, the platform is also used by some of the world’s major companies including Novartis, Amgen, Mount Sinai and PepsiCo for upskilling and reskilling.
Angel investors and venture capitalists are looking for startups with real products and a proven business model, ready to scale. Yet I still get too many business plans that clearly are looking for money to do research and development (R&D) on a new and unproven technology. If you need funding for these early stage activities, I have some suggestions on better strategies to follow.
The first is to be more precise in your definition and understanding of where you are, and how the money will be spent. If this is your first foray into the entrepreneurial arena, with no track record in business or technology, your best and perhaps only supporters will be that class of investors known in the trade as friends, family and fools (FFF). They believe in you above all else.
Beyond these believers, you need to match your credentials and interests with the multitude of public, academic and government organizations that proclaim to foster research and early development, to satisfy the long-term needs of the people or organizations they support. In this context, there are at least six stages often included in the scope of R&D to narrow your focus:
- Search for new technologies. This early stage is often called basic research, well before any specific commercially viable products might be envisioned. Here your options are limited primarily to large organizations with deep pockets, including government grants, universities and large enterprise sponsors searching for disruptive technologies.
- Technology pilots. This is the transition stage from basic research to applied research. Applied research is still primarily scientific study, seeking to solve practical problems, but doesn’t yet focus on a commercial product. Funding sources for this stage extend from grants to large private fund incubators, such as the IBM Watson initiative a while back.
- Commercial product prototypes. Funding for commercial product prototypes is still R&D in the eyes of venture capital investors, but in business areas with large opportunities, this activity will catch the eyes of specialized angel investors. It’s still considered high risk for investment, since manufacturing and quality issues are likely.
- Product verification and clinical trials. These days, almost every new product is not deemed scalable until it has been certified as meeting a multitude of quality and agency standards, including the Environmental Protection Agency (EPA), Food & Drug Administration (FDA) and Underwriters Lab (UL). Specialized VCs start to jump in at this stage.
- Business commercialization. Product development at this stage is the process of scaling up for manufacturing and marketing rollout. The technology is now embodied in a solution that can be replicated to reliably solve a real customer problem. Your fundability with investors now depends primarily on the execution capability of your team.
- Expanding the product line. Even for mature startups, there is always a need for further product development and research to compete and diversify the business, and investors understand this. But to prevent confusion with basic R&D, these costs should never be called out the major category in your use of funds statement to investors.
While all forms of technology research and development will always be required, entrepreneurs need to understand that the funding for these efforts comes from many different sources, depending on the stage. Business equity investors are buying a portion of your business, so they are looking to fund a specific business with a specific offering, not a generic technology.
Don’t waste your time and energy talking to angels and VCs about technology funding when you could be focused more productively on grants, private funds and future business partners. Business investors and customers want to hear about solutions, and tend to back away from technology, until it is proven.
Fortunately, in many attractive business domains, including mobile software, Internet apps and ecommerce, the cost of product development is at an all-time low. Developers are using powerful technology tools to build mobile apps and websites for a few thousand, rather than millions of dollars. Thus the best entrepreneur strategy for funding is to build solutions, not technology.