2020 witnessed a plethora of changes, particularly with tech companies cementing their place on the market. I expect more of the same as I head into 2021. Before discussing the 15 companies to look for in 2021, you ought to be aware of four major industries that have drastically affected online presence, leads, and revenue generation. These four industries are Email Marketing, eCommerce, CyberSecurity, and Customer Experience.
Procurement software company Archlet offering an AI-based strategic sourcing platform, today announces that it has completed a $2.8 million oversubscribed seed round led by Munich-based Senovo and Berlin-based La Famiglia. The funds will fuel growth and allow the startup to democratize data-based decision making in strategic sourcing.
Alongside Senovo and La Famiglia are further investors including Nicolaus Schefenacker, David Nothacker and Julius Köhler, the founders of unicorn start-up sennder. Existing investors Wingman Ventures, Flavio Pfaffhauser (Founder of Beekeeper) and Karin Hagen-Gierer (Chief Procurement Officer at Ardagh Group) also participated in the round.
The capital will enable Archlet to address supply chain challenges as companies are under increasing pressure to create bottom-line savings through their procurement departments while also incorporating non-price parameters in order to diversify risks, increase sustainability and improve supplier diversity. This pressure was greater than ever in 2020 when global supply chains were put under unprecedented stress due to the global pandemic crisis. Existing sourcing software solutions are mainly focused on simple price analysis, and they are complicated to use, making sourcing a tedious experience for company buyers.
The combination of artificial intelligence (AI) and internet of things (IoT) technology may be the biggest disruption to the industrial refrigeration industry since the invention of the first commercial ice-making machine two centuries ago.
In this second year of a modern pandemic, startup Youtiligent has developed an AIoT-based technology to help companies keep vaccines cold across complex distribution supply chains. Moving far beyond sensor-based temperature monitoring, Youtiligent’s promise is to securely capture real-time electric power anomalies in onsite commercial refrigerators, allowing distributors to take action before vaccine spoilage.
“Sensors that capture when a product’s temperature has decreased below the acceptable degree range are not effective when it comes to distributing something like the coronavirus vaccine,” said Avichai Belitsky, co-founder of Youtiligent. “We combined AI with IoT technology to deliver real-time alerts for cost-effective predictive and preventive maintenance. Organizations can act faster in making data-driven business decisions based on what’s happening in real-time, such as sending in a repair technician, before it’s too late.”
EKG for cooling appliances
Based in Israel, Youtiligent is piloting its offering with healthcare organizations in that country. Belitsky also expected high interest from refrigeration manufacturers and pharmaceutical companies, as well as medical and other institutions with clinics, pharmacies, and research labs, such as hospitals and universities. The startup continues to serve customers in its original target markets that include the food and beverage and retail industries.
“This is what we call ‘EKG for appliances,’ tracking electric current across compressors, engines, and pumps that power any cooling machine, whether it’s making ice cream to be sold the next week, or cooling expensive chemicals that researchers safely store and use over many years,” said Belitsky. “Every machine action has a unique fingerprint, and being able to track each one with algorithms yields valuable, actionable insights.”
In episode 50, you’ll hear insights on top skills needed in the tech world, what’s driving leadership in global supply chains, the common threads of success in scaling innovation, and how to leverage the SDGs in your partnerships and hiring practices.
Listen as Sallie Jian shares why she decided to lead the SAP.iO NY foundry.
Shippeo, the European leader in real-time transportation visibility (RTTV), today announces a $32 million investment. This new round is co-led by Battery Ventures, a global, technology focused investment firm and existing investors (NGP Capital, ETF Partners, Partech and Bpifrance Digital Venture). Shippeo will use the investment to strengthen its market-leading position and continue delivering on product innovation.
The Covid-19 crisis has highlighted the need for supply-chain visibility, with major shippers across industries needing enhanced transparency more than ever before. With many countries in lockdown and with unpredictable border closures, companies with advanced visibility solutions managed to mitigate transport delays and the associated operational inefficiencies. Beyond tracking shipments, visibility platforms now give supply chains the data-driven transparency to meet varying customer demands in uncertain and challenging market conditions.
Despite the unprecedented global economic impact of Covid-19, Shippeo has more than doubled its subscription revenues year on year, while successfully increasing its customer base in 2020 with major industrial brands and fourth-party logistics providers such as Kuehne+Nagel, Total, Hager or Krone. Last October, Shippeo acquired the French company oPhone, bringing major customers in the retail and manufacturing sectors into its community. Finally, Shippeo’s total workforce has more than doubled in the last 12 months, now totaling 160 employees, of which 45% work in R&D.
UNICEPTA and Ubermetrics will in future drive forward their technological development based on a joint strategic mission. Both companies will team up and further expand one of the best AI-based intelligence platforms for communication and marketing on the international market.
In episode six of the Ascent podcast, Andrew Tarvin speaks with Vanessa Liu, Vice President of SAP.iO Foundries North America. They discuss topics including diversity and inclusion in the start-up community, habits of successful entrepreneurs, and Vanessa’s experience working with founders at SAP’s accelerator. Andrew and Vanessa also discuss thoughts on their outlook for 2021 and the changing nature of the start-up community.
Josephine Monberg interviews Tobias Buxhoidt, Founder and CEO at parcelLab and Max Kissel, Founder and CEO at Soley.
COVID-19 has caused disruption across the global economy, forcing companies to alter tried-and-true business processes and meet customers where they are.
With in-person interactions no longer the default option, companies are investing in digital commerce sites for business and consumer transactions.
SAP Commerce Cloud is aiming to make it easier for businesses to open these digital storefronts and customer engagement platforms to support B2B, B2C and direct-to-consumer sites all on a single platform, said Paula Hansen, senior vice president and chief revenue officer for SAP Customer Experience.
Cultivate was initially founded through Samsung NEXT’s ‘Entrepreneur in Residence’ accelerator program. In 2019, SAP’s early-stage venture arm, SAP.iO, participated in the AI company’s Series A funding where it raised $8 million to grow its go-to-market team and product offerings. Since then, Cultivate has accumulated a total of $10 million in venture capital and partnered with multiple leading academic institutions to further its mission of a digital leadership platform.
Cultivate was founded with the vision of empowering next-generation leaders through an AI-based leadership development platform that supports them in improving their teams’ employee experience. The platform uses the latest techniques in Machine Learning (ML) and Neuro-linguistic programming (NLP) to derive social insights from digital channels to help leaders realise their full potential.
According to Joe Freed, co-founder and CEO of Cultivate, the company aims to address a leadership development gap to help managers self-evaluate their digital communications with insights on their own behaviours. He comments:
“Managers are overloaded with email and chat, but they still have to be managers of people. When it comes to things like well-being, burnout, inclusion, and engagement, a lot of how you can influence your team can be through digital communication. But we don’t have a lot of tools to help us with this.”
Enterprise leaders who opt-in to the AI coaching platform get access to a digital coach that scans and analyses the words and the metadata collected from various digital communication channels such as Office 365, Google Suite, Teams and Slack. The Cultivate AI for leaders then delivers personalised, continuous and easy-to-execute actionable leadership insights to managers themselves, helping them strengthen their workplace relationships and ultimately improve the employee experience.
According to Cultivate, a manager using the digital leadership coaching platform can also give feedback to the Cultivate AI to adjust the feedbacks being generated based on the context of their relationships with their team members.
Companies using the Cultivate AI for leaders include:
At SAP, the Cultivate platform was deployed at an initial small pilot. After confirming that the AI’s feedbacks were highly beneficial, the SAP team did a larger roll-out to approximately 250 sales managers, where 79% of those eligible to participate chose to do so.
Today, SAP has deployed Cultivate to over 500 managers. The German multinational company reports that 96% of managers have remained engaged with Cultivate since the initial roll-out.
SAP.iO Foundry Paris lance un nouvel appel à candidatures pour son programme d’accélération de startups orientées agri-business. Cette 6ème promotion de l’accélérateur de startups de SAP retiendra 6 à 10 pépites tech et Agtech pour son programme de 10 semaines débutant en avril 2021. Les startups françaises mais aussi européennes peuvent candidater dès aujourd’hui jusqu’au 31 janvier 2021. Un autre appel à candidature est ouvert aux startups Greentech Françaises pour ses programmes de Berlin et Munich.
If the CEO of Presize has his way, clothing returns will be a relic of the past, and online retail brands will not sacrifice business for the sake of the environment.
The startup’s cloud-based app uses artificial intelligence (AI) to calculate clothing sizes for individual online shoppers. Much more than welcome relief for anyone who has ever hesitated to buy clothing online because they were uncertain of their size, the tool reduces size-related product returns by 50% on average.
“Sustainability is core to our mission,” said Leon Szeli, co-founder and CEO. “Every product return we save is a win for the consumer, the brand, and the planet. Every item of clothing that consumers scan using our app means fewer returns. This contributes to a lower carbon footprint for the planet, less time wasted for shoppers, and greater cost-savings for retail brands.”
Based in Germany, Presize serves well-known clothing apparel brands in that country and throughout Western Europe. Its online sizing tool has provided half a million recommendations to delighted consumers. Instead of second-guessing ambiguous size charts, shoppers simply click on the “find my size” button, answer basic questions that include their height, weight, and gender, upload a video of themselves if they choose, and then the algorithm provides their best size for that product. Behind the scenes, AI-fueled algorithms learn from dynamic data analyses.
“We constantly train the algorithm using data from hundreds of thousands of human shapes and other variables, plus stock-keeping units (SKUs) from clothing manufacturers, and layer that with product return information,” Szeli said. “Once someone saves their size ID, it can be applied to any brand that uses the Presize app, making shopping much easier. Shoppers can even share their size information with family and friends.”
According to Szeli, online retailers that use the Presize app on their website have increased conversion rates, meaning consumer sales, by up to 25%. As with any AI-based tool, user adoption is critical for calculation accuracy. Szeli said that approximately 10% of shoppers use the tool when it is available on a brand’s site.
“A big part of sizing uncertainty is the diversity between brands, Szeli explained. “Every product is different, and we want to help consumers regardless of what brand of clothing they buy.”
Presize is the culmination of Szeli’s two major career passions: conducting research and having a positive impact on the world. As a university student in the U.S. and the UK, he focused on human trust in AI-based technology. However, he quickly realized that he wanted to accomplish much more than producing papers for niche audiences. When he met his co-founders, who were working with computer vision and AI, they embarked on a journey to literally change the world – beginning with online shopping.
“I wanted to do something entrepreneurial that would have a much wider impact and change people’s lives for the better,” Szeli said. “I saw the problem of product returns as a sustainability issue that wasted environmental resources, as well as time and money for businesses and their customers.”
Rheaply’s VP of External Affairs, Tom Fecarotta, met with Vahan Tchakerian of Cogniac to discuss their organization’s mission and involvement in the SAP.iO Foundry Cohort.
This is Part 1 of 3 in Rheaply’s discussions with other SAP.iO cohort members. Stay tuned for future Q&A’s with Wise Systems and Ivaldi.
Tom: I’m going to steal this first question from an investor who asked us this. Give me the high school version of the boilerplate and the version for a college student who maybe knows a little bit about AI.
Vahan: I always try to simplify things down. So we know our business, right, but when we introduce it to a new set of people, it’s always like, “what is AI?” Because AI is so universally used — everything is about AI today. For our purposes, we offer an AI platform — a software platform — where we’re working with a combination of neural networks and a deep learning component to automate visual inspection tasks. So anybody doing any sort of inspection is a candidate to use our solution. What’s really beneficial about what we do and how we do it is we’re offering a superhuman level of accuracy in work. In today’s world, inspections and products are super complex — at this rate, humans are missing stuff. We’re not only able to catch these things but catch them quickly, so we are really preventing any sort of downstream failures, etc. — that’s one of the benefits, along with more efficiency.
Tom: James, anything to add to that?
James: No, as Vahan mentioned, it’s going above and beyond what a human is currently capable of — that superhuman aspect is one that we tend to focus on. It’s a game-changer in the visual inspection world because it’s doing so much more at such a high level and operating at such a high degree of accuracy that it’s going to fundamentally change visual inspection and the AI industry within the manufacturing verticals we work in.
Tom: Yeah, that’s really interesting. Talk to me a little more about the application itself. Walk me through the use case for an end user and what that experience looks like.
Vahan: Sure. What we’ve tried to do is make the engagement super simple, to the point that there are no data scientists required — it’s literally technician-level work. Let’s say I’m talking to a potential customer — they have a subject matter expert on a given use case, and what the subject matter expert would need to do is label a few images. In traditional machine vision, somebody would be required to label tens of thousands of images, if not hundreds of thousands; in our case, it’s a few hundred images in what we call established ground truth. Everything we do is teaching with examples, right, in the simplest form.
Let’s say we’re looking at a cast part — there’s a good part and a bad part. We have to have enough examples of a good part and a few more of a bad part to establish the ground truth of what that looks like. Then we upload that in our platform and the platform starts to make predictions against that data. So consistent labeling is key, and also key is having enough of a dataset of images where you establish ground truth to get the engine running through what we call AI creating AI. So then we look at these predictions, and the subject matter expert says, “You know what, this is kind of close, this is not close,” and so forth. Then there’s some fine-tuning back and forth between the subject matter expert and our platform, and within a couple weeks you’re looking at 95, 98, 100% model accuracy. So that’s the benefit of getting there really quickly, and if you’ve gone down the wrong path, it’s really easy to re-establish yourself and how you do your labeling.
Tom: Is this set into a maintenance system or some kind of internal system that can tell users about the health of item within a warehouse? What does the integration set look like?
Vahan: When we find something that is outside of the norm or there’s an issue, we would send an alert in any way the customer would want to see. Our platform is cloud-based or can be on-prem. Most of our customers are in the cloud. With a cloud solution in a manufacturing environment where someone needs super fast response, alerts — under a second, for example — then you would incorporate what we call an edge appliance. This edge appliance is basically doing the processing of the application at the edge — and if it finds something that’s outside the norm, it can send an alert to any user in any form that’s needed.
Tom: Wow, that’s really cool. I think we’re similar in the respect of wanting to make the process of finding things and understanding their utility easier, and in your case, you’re also working to determine what is potentially needed to improve a particular asset for people. And I think that’s really interesting.
This is a perfect segue into sustainability. Read More….
’s estimated that the total amount of data is expected to reach 59 zettabytes this year with 90% of that data created in the last two years alone. With such an exponential increase in data, companies are racing to protect the data they maintain and regulatory initiatives like GDPR and the California Consumer Privacy Act are formalizing standards. BigID is the data intelligence platform that leverages advanced machine learning and automation to allow customers to seamlessly protect sensitive data, be compliant will data privacy laws, and ensure compliance with data sharing requirements. The company offers a foundation product that provides companies with visibility of all their data across the data landscape and additional apps provide added intelligence and specialized insight into privacy, protection, and perspective.
AlleyWatch caught up with Cofounder and CEO Dimitri Sirota to learn more about the data protection ecosystem the company has built, its future plans, and recent round of funding, which comes at a $1B valuation and brings the total funding raised to $216.1M for the company founded in 2016.
Who were your investors and how much did you raise?
This was our Series D round. Salesforce Ventures and Tiger Global co-led the round with participation from Glynn Capital and existing investors Bessemer Venture Partners, Scale Venture Partners, and Boldstart Ventures.
Tell us about the product or service that BigID offers.
BigID’s data intelligence platform enables organizations to know their enterprise data and take action for privacy, protection, and perspective. Customers deploy our product to proactively discover, manage, protect, and get more value from their regulated, sensitive, and personal data across their data landscape. Our ML-based data discovery foundation helps organizations know their data across their entire data landscape (from mainframe to cloud to on-prem), and our app framework lets you action that data – we have apps for privacy, security, and governance that range from a data risk app to a data retention app to a data remediation app and more.
The most interesting graduate from the latest cycle of SAP.io – the accelerator from SAP Global – is Trendemon. At Trendemon they have created a platform for companies designed to improve their ability to understand and accelerate the impact of their marketing efforts on sales. Trendemon has developed a platform that maps the customer’s journeys, ranks the impact of the company’s various content on business goals and personalizes the content on the site.
