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.
Leveraging AI for Leaders and the New Digital Workforce
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:
- SAP
- Qualtrics, an SAP-owned company and leader in XM technology
- McKesson Corporation, a global leader in pharmaceuticals and health information technology
- BASF, the largest chemical producer in the world
- PwC, considered one of the Big Four accounting firms
- SamsungNEXT, a ventures and innovation group within Samsung
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.
Adverity, a leading marketing data intelligence platform, has ranked number one in the Momentum Grid Report for Big Data Integration in the G2 Winter 2021 Report. It also continues to be recognised as a momentum leader across four other categories – Marketing Analytics Software, Data Visualization Software, E-commerce Data Integration and ETL Tools.
Top for product satisfaction in the Big Data Integration category with a score of 96%, Adverity also holds second place in the ETL Tools category; boasting a higher product satisfaction score than the category leader.
It maintains third position in the E-commerce Data Integration category, while solidifying its status in the top five Data Visualizations products and remaining in the top ten Marketing Analytics Software products.
G2 rankings are based on data provided by verified users that share their experiences and feedback on software. The platform has more than one million independent user reviews and is read by over four million users each month. Every quarter, G2 Crowd publishes its Grid report, ranking software by extracting data from multiple online sources to determine market presence, satisfaction scores from customers, and market leadership.
The latest recognition follows a positive year for Adverity where it was previously named a Momentum Leader for ETL tools in the G2 Summer 2020 and Fall 2020 reports respectively. During this period it also moved into, and remained, in the Grid Report for Marketing Analytics top ten.
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.
Gtmhub, a multinational startup that builds software to help other companies manage their corporate planning, announced that it has raised a $30 million Series B. The round was led by Insight, and included both participation from new investor Singular and prior investors LauncHub and CRV.
Gtmhub raised capital around 13 months ago, a $9 million Series A. At the time, the new capital was larger than the aggregate of its preceding funding efforts. The startup’s new funding round, like its 2019 Series A, towers above its prior fundraising totals in a similar manner.
How has Gtmhub managed to raise so much money? In a word, growth.
TechCrunch reported at the time of its Series A that Gtmhub had managed 400% growth in annual recurring revenue (ARR) heading into the round, on a year-over-year basis. Similar levels of topline expansion have continued, with Gtmhub COO Seth Elliott telling TechCrunch that the company grew its ARR by a multiple of three last year (measured December 2019 through December 2020).
Around the time Gtmhub raised in 2019, a number of other startups focused on the same software market raised as well, leading to TechCrunch asking “why is everyone making OKR software?“
The acronym OKR translates to “objectives and key results,” a planning method that has become popular among American technology firms, and, according to Elliott, is becoming more popular internationally and among non-technology companies.
The startup executive also told TechCrunch that he sees Gtmhub growing alongside two business trends. The first, the rise of OKRs themselves, is a wave that his company is riding, he told TechCrunch. The second, one that he thinks his startup is leading, deals with large companies pursuing corporate transformations to boost their agility; those firms are adopting Gtmhub, he said, which can help them execute their digital transformation, or similar efforts, successfully.
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.”
Sustainability Is the Perfect Fit for Online Shopping
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.”
Digital Insights for Sustainable Results
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.”
Paradox, the leading conversational AI platform helping global talent acquisition teams automate recruiting tasks like screening, interview scheduling, and candidate communications, announced today the acquisition of Spetz.io, an Israeli startup helping clients like EY and Sodastream modernize candidate communications.
Founded in Tel Aviv in 2017, Spetz has quickly developed a reputation as a product-led, client-centric startup in Israel — a country with a rich history of building world-class AI and machine learning technologies.
The acquisition highlights Paradox’s strategic investment in global innovation and world-class client services, said Paradox founder and CEO Aaron Matos. But it wasn’t just about creating another R&D center. Just as important, Matos said the Spetz team’s vision, mission, and values closely aligned with Paradox.
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.
Cogniac Q&A
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….
An explosion of data should not scare us. It is an explosion of data processing that might be our doom. MANTA’s CEO Tomas Kratky explains how to deal with growing complexity of our data pipelines in 2021.
Not Knowing Costs Lives and Money
But that somehow seems irrelevant when we look back at 2020. It was definitely not an easy year for anyone. We, both as a community and as individuals, were tested in many different and challenging ways. Many lives were lost and even more lives were drastically impacted by COVID-19. We had to live (and we still live) with a lot of uncertainty all around us. We did not know how dangerous the virus would be, if there would be any long-term effects on our health, if / how easily we could get sick multiple times, and the list goes on. And that kind of “not knowing” sucks. Many of us decided to stay at home, limit our social interactions, and have our groceries delivered for many months to protect ourselves and the ones we love.
’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.
WALLDORF — SAP SE (NYSE: SAP) today announced it has been recognized with a Corporate Startup Stars Award as one of the Top 25 most active companies to encourage open innovation with startups.
SAP also received a Corporate Startup Accelerator Award for its acceleration efforts and identifying worldwide best practices in corporate-startup collaboration. The announcement was made at the digital award ceremony hosted by open innovation advisory firm Mind the Bridge and the International Chamber of Commerce, on December 15.
Engaging with early stage startups is an important aspect of SAP’s holistic open innovation approach to remain agile and resilient in today’s global marketplace. This includes dedicated programs within SAP’s early stage venture arm SAP.iO to scout and accelerate new ideas and talent inside and outside of the company.
“At SAP, we know that we can mutually benefit from outside-in perspectives to inspire innovation and drive business impact for our customers,” said Juergen Mueller, chief technology officer and member of the Executive Board of SAP SE. “Since 2017, we have helped scale more than 270 promising startups across all lines of business and industries in nine locations across the globe. Providing them with the access and resources they need to build on SAP solutions complements our portfolio and internal innovation efforts, which enables our customers to gain even more value from their SAP investments.”
For the fifth year, startups have been asked to nominate the companies that are most active and friendly in working with small businesses. Started in 2016 under the European Commission’s Startup Europe Partnership initiative, the Corporate Startup Stars Awards have been scaled to include corporations and startups worldwide through the partnership between Mind the Bridge and the International Chamber of Commerce.
“SAP has consistently proven to be one of the most startup-friendly corporations worldwide by engaging with startups in multiple modes, ranging from acceleration and partnerships to investments and acquisitions,” said Alberto Onetti, chairman, Mind the Bridge. “We appreciate the approach SAP.iO has taken and its recent evolution. The combination of startup and employee-driven innovation and the renewed focus on scaling companies makes SAP.iO a benchmark globally for rethinking and optimizing the corporate accelerator model.”
To learn more about how SAP is helping innovators inside and outside of SAP build products, find customers and change industries, please visit SAP.iO.
Visit the SAP News Center. Follow SAP on Twitter at @SAPNews.
Media Contact:
Lesa Beber, +1 (650) 390-1629, lesa.beber@sap.com, ET
SAP Press Room; press@sap.com
The celebrated Rockefeller Center Christmas Tree arrived in New York recently, ready to take its place as the epicenter of the 2020 holidays. This perennial centerpiece of millions of photos and family memories is a sparkly, over-the-top reminder that while many aspects of our lives are different this year, certain institutions and traditions will not be disrupted. But, where many look at the arrival of the tree and reflect on the pandemic’s impact on beloved holiday traditions, the last-mile delivery industry has a different view.
Last-mile professionals—networks of dispatchers and drivers that get goods and parcels from warehouses and distribution centers to retailers, businesses, and residential doorsteps—make it possible for so many people to stay safely home and receive the goods they need. But, even before the pandemic and the 2020 holiday season, the industry was already struggling to meet its efficiency and customer service goals while using legacy technologies.
Then, virtually overnight, COVID-19 accelerated customers’ willingness to shop online, adding volume to already stressed systems—e-commerce surpassed expectations and grew by over 30% this year. So instead of a measured, steady progression that last-mile teams could gradually absorb, the long-promised changes in customer behavior arrived at lightspeed. This condensed adaptation offered last-mile operations precious little time to match customer behavior or implement more modern, dynamic infrastructure.
Customer behavior has been massively influenced by the pandemic, reducing overall spending and changing purchasing plans. The Deloitte State of the Consumer survey offers a fascinating window into current consumer attitudes and concerns, including shopping intent, with grim implications for the retail sector, which has already seen several notable brands declare bankruptcy. For this year’s holiday shopping, many are expected to forgo Black Friday and crowded malls for the safety and efficiency of their nearest screen. They’ll rely on complex-yet-invisible processes to get purchases from their digital shopping basket to their doorsteps. And retailers are bracing for an expected surge to already high online sales. But exactly how do items get to the customer?
Once an order is complete, items are picked and packed at the local retailer or retailer’s warehouse. From there, packages are sent to a regional distribution center where they’re sorted, routed, and delivered by a driver. That last leg of the relay from the distribution center to the customer’s doorstep—the “last mile”—is an incredibly challenging and fast-moving industry. The logistics industry estimates the last-mile can account for up to 40% of total transportation cost. It’s where things can come together beautifully to deliver on a brand’s promise, or fall apart spectacularly, tarnishing reputations and customers’ goodwill.
So why is last-mile delivery so complicated? Mathematically, it’s one of the most complex problems to solve—how to efficiently route many vehicles with multiple stops and numerous other variables and constraints. In academic circles, it’s known as the Traveling Salesman Problem or TSP. It has applications ranging from logistics to DNA sequencing to chip design. In the real world, it’s a mix of mathematical and human factors.
SAP invests in a lot of promising startups, and it’s sometimes hard to keep track of all of them. E-3 Magazine has selected the most interesting companies to showcase in our SAP Startup Spotlight Series. In this article, we will take a look at Cloverleaf.
Cloverleaf brings team coaching to the entire enterprise. Cloverleaf integrates with the communication and productivity tools employees use every day like Google for Business, Microsoft 365 and Slack. It provides micro-coaching through these tools to improve work relationships that lead to better collaboration, more inclusive teams and improved leadership competency. In this interview, Darrin Murriner, CEO and co-founder of Cloverleaf, talks about what the company has to offer and what’s next for the startup.
E-3 Magazine: How does your solution work?
Darrin Murriner: Everyone starts by taking market recognized assessments like DISC or StrengthsFinder and can then get custom insights about their personal development. Anyone can create a team by inviting their teammates and then get custom insights about their unique roles on the team. Integrating their Cloverleaf account with Microsoft 365, Google Workplace or Slack will then open the door to custom coaching that improves work relationships.
What are the customer-side requirements?
Murriner: Anyone can get started with a web browser, no special client-side hardware is required. It can take as little as ten minutes to create your account and begin receiving custom coaching.
Why did you start Cloverleaf to begin with?
Murriner: Kirsten Moorefield and I worked together at a digital video agency. During our time there we noticed the unique role that team interaction had on the success or failure of project-based work and wanted to bring transparency to the process of team formation and team performance. This started us on a quest to identify the right inputs, data visualizations and coaching opportunities to improve team development.
