Crosschq Announces New Round of Investment from Tiger Global and Rocketship.vc

 Crosschq, pioneers of a new software category for the recruiting industry called Human Intelligence Hiring™, announced today a new round of financing that includes investment from Tiger Global Management and Rocketship.vc. This latest round comes immediately following a strategic financing from Slack and SAP.iO in June which also included re-investment from GGV Capital and Bessemer Ventures.

“We are proud to be partnering with these two great firms as we enter the next phase of our growth,” said Mike Fitzsimmons, CEO of Crosschq. “If we have learned anything from the last several months, it is that the future of work is ripe for disruption. Our use of human intelligence is becoming a foundational element of modern company building.”

Crosschq brings speed, efficiency, accuracy, transparency and accountability to the obsolete, manual process of vetting new job candidates. The new investment comes as Crosschq crosses the 100 customer milestone with customers including Dish, NBA, Upwork, Snowflake, NerdWallet and Glassdoor using the platform to enhance recruiting and make better hires.

“SAP strongly believes that the future of work is inclusive and diverse, and that starts with removing biases in the candidate experience,” said Ram Jambunathan, SAP senior vice president at and managing director of SAP.iO. “Crosschq will bring increased objectivity and consistency to the candidate reference checking process, thereby improving outcomes for both candidates and SAP customers.”

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SAP.iO Supports Employee Experience Management Tech Solutions

SAP.iO recently announced its investment in workforce optimization software company Andjaro. The company, based in Paris and founded in 2015, provides a unique marketplace dedicated to helping organizations post staffing needs directly on its real-time workforce optimization platform. The solution—available for purchase at the SAP App Center—allows businesses to reallocate available and voluntary internal staff from other locations within the organization. This not only minimizes HR costs but more importantly, improves the employee experience by offering them the chance to work at other parts of the organization and get compensated for a temporary relocation resulting in a more interconnected and happy workforce.

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Investing in Female Founders — Lessons from Behavioral Finance, Gender Research and Real Life Experiences

A story of a conversation between an academic researcher, VC investor, CVC investor and an entrepreneur

2019 brought more female-founded unicorns than ever before, and more new female partners at VC firms. Despite this progress, VC remains one of the most gender-skewed industries in the US. Last year, approx. 87.8% of the VC funding was raised by all male founder teams. We also see an emerging evidence that the disruption caused by COVID-19 is bound to disproportionately affect women. As reported by Pitchbook, Q1 2020 already showed a decline in share of deals with startups founded by women.

Wait… but why?

I am a nerd. I studied Finance & Accounting, I studied Psychology, and then I got an MBA. I have always been fascinated by behavioral economics and academic research proving that we are irrational in a systematic way when making decisions under uncertainty. If you haven’t read yet — Thinking, Fast and Slow by Daniel Kahneman is a good place to start. Yes, he is that psychologist who was awarded the Nobel Memorial Prize in Economic Sciences.

Now, why it matters in VC. Mixed gender or women-led startups are not performing worse than male-led — actually it’s quite the opposite. So isn’t it rational to invest in them? From behavioral economics, we know that decisions under uncertainty are influenced by the actual framing and context. Biases and heuristics come into play when it comes to VC investing — it is no different than thinking about weighing potential gains and losses under uncertainty. So what can we actually do to help scale investments in female founders if we can’t change how we’re all wired? Let’s look at it from three different perspectives represented by (#1) a researcher, (#2) two investors, and (#3) an entrepreneur.

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Le fonds de SAP investit dans Andjaro

La filiale d’investissement de SAP dans les startups, SAP.iO Fund, a investi dans la seconde phase de financement d’Andjaro.

SAP.io a mis au pot pour un tour B d’Andjaro, une société basée à Paris qui permet l’optimisation des effectifs en temps réel et aide les entreprises à assurer la gestion et le recrutement des collaborateurs à distance.

La série B de 13,4 millions d’euros a été menée par Idinvest Partners et comprend l’investisseur actuel, Balderton Capital. Andjaro s’intègre aux solutions cloud de gestion de ressources humains SAP SuccessFactors. SAP collabore avec Andjaro pour fournir à ses clients une vue d’ensemble en temps réel des besoins en personnel, des compétences disponibles à proximité afin de proposer un redéploiement volontaire sur une courte période. SAP.iO Fund avait déjà investi, en 2018, dans la série A, menée par Balderton.

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SAP.iO Fund Invests in Andjaro, an Internal HR Staffing Marketplace Connected to SAP SuccessFactors Solutions

SAP SE (NYSE: SAP) today announced that its investment arm, SAP.iO Fund, has invested in second round funding of Andjaro, a Paris-based company that provides real-time workforce optimization and helps manage and staff remote workers. The €13.4 million Series B round was led by Idinvest Partners and includes existing investor Balderton Capital.

Andjaro helps companies redeploy employees internally and works with SAP SuccessFactors solutions. SAP works with Andjaro to provide SAP customers with a real-time overview on staffing gaps, employee skills, availability and proximity to propose voluntary redeployment for a short period of time. SAP.iO Fund previously invested in the Balderton-led 2018 Series A round.

“SAP customers are continually exploring how to best allocate their most valuable resource — their talent — especially in the current environment,” said Ram Jambunathan, SAP senior vice president and managing director of SAP.iO. “Andjaro’s platform can provide enterprises with new opportunities to redeploy existing human resources efficiently.”

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How AI And “Gaze Control” Will Help Businesses Reopen Safely

Recent projections by the US federal government estimate that there will be 200,000 new coronavirus cases in the US  by June 1. At the same time, governments around the world are grappling with the complexities of safely reopening businesses, schools and other public institutions.

Technology companies are rushing into that gap with software aimed at keeping people safe, while citizens navigate a patchwork approach to easing shelter-in-place orders. One well-known approach is the use of contact-tracing apps on smart phones created by tech and telecom companies. These apps alert people if they’ve been in close proximity to an infected person.

But other technologies can help. When businesses and other institutions open up, they will need to do a lot of things differently. A new technology called “gaze control” allows people to avoid touching surfaces, like ATM display screens or subway-fare vending machine, that may be potentially contaminated with the virus. Stephan Odörfer is founder and managing director of Munich-based 4tiitoo (pronounced “42”), a startup that creates gaze control technology. Put simply, this technology lets people use their eyes to interact with computers, replacing the need to touch a keyboard, mouse or screen.

Moreover, 4tiitoo has combined gaze control with AI to analyze patterns in users’ eye movement and predict what people want to do next within a particular computer screen or application. “Gaze control allows you to do two things. It controls the computer and we can use it to get an understanding of what the user actually wants to do, “said Odörfer. “By understanding intention, we can proactively support him.”

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Marketing data platform Adverity raises $30M Series C led by Sapphire Ventures

In the time many of us live in now, we all know our online media consumption is — to state the obvious — going through the roof. Subsequently, the amount of data pertaining to online marketing is, equally, reaching stratospheric heights and in recent years tech companies like Datorama and Funnel.io, SuperMetrics and Adverity have appeared to give marketeers a data intelligence platform to deal with the welter of spreadsheets and reports necessary to track everything.

Last year, Vienna HQ’d Adverity closed an €11 million Series B funding round for its AI-driven platform to produce actionable insights in real-time for marketers.

Today it’s announcing a Series C financing round of $30 million, bringing the total amount it has raised to $50 million. The latest funding round is led by Valley-based Sapphire Ventures . Also participating is Mangrove Capital Partners, Felix Capital, SAP.iO and aws Gründerfonds who have all re-invested in this latest round. 

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Adverity raises $30 million to collect, prep, and analyze marketing data

Adverity, a data analytics startup targeting applications in media, marketing, and ecommerce, today announced that it raised $30 million in equity financing, bringing its total raised to $50 million.

By accelerating R&D and growth within Adverity’s offices domestic and abroad, the fresh capital could help the company’s customers — among them Ikea, Red Bull, Unilever, MediaCom, and IPG Mediabrands — address the challenges AI and machine learning present with respect to productization. According to Algorithmia, 50% of companies spend between 8 and 90 days deploying a single AI model, with 18% taking longer than 90 days

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SAP.iO Fund Invests in Deepgram for Gleaning New Insights from Speech

SAP.iO Fund, the startup investment arm of SAP SE (NYSE: SAP), has taken a stake in in Deepgram, provider of a high-accuracy automatic speech recognition solution that can be easily trained to understand new language models, accents and speech patterns.

With a new approach to speech recognition, Deepgram’s flexible API architecture enables real-time transcription for customer support, sales engagement and video/phone interviews and makes them searchable. Wing Ventures led the Series A round, which included existing investors Nvidia, Y Combinator and Compound.

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Israeli startup Revuze raises $5 million Series A for customer analysis software

Israeli market research startup Revuze has raised a $5.1 million Series A round led by Maverick Ventures (Israel), with support from existing investor Prytek.

Revuze has built a machine-learning system to analyse customer opinion, providing market insights on a user’s own products and brands, as well as any competitors. Standard reports such as Net Promoter Score (NPS) and consumer satisfaction (CSAT) are also included.

The startup says the software allows business owners to make decisions without the help of specialists such as analysts, data scientists, and information technologists.

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Deepgram Raises $12m in Series A funding

Deepgram, a San Francisco, CA-based speech recognition platform for the enterprise, raised $12m in Series A funding. The company, which has raised $13.9m to date, intends to use the funds to expand operations and its business reach. Founded in 2015 by Scott Stephenson, CEO, Deepgram uses end-to-end deep learning technology built with GPUs to provide companies and individuals with automatic speech recognition (ASR) that is powered by advanced, multi-layered machine learning technology. Its current product, Deepgram Brain provides transcription and audio search capabilities for individuals and enterprises. Since going to market, Deepgram has amassed more than 30 customers across the call center, retail and tech industries.

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Enterprise Speech Recognition Startup Deepgram Raises $12M

Speech recognition technology startup Deepgram has closed a $12 million Series A funding round led by Wing VC along with NVIDIA, Y Combinator, and other investors. The funding comes as the company debuts new features for its enterprise-focused automatic speech transcription and analysis platform.

Deeper Learning

Businesses are growing to rely on artificial intelligence to record, transcribe, and analyze phone calls, meetings, and other audio. The speed and low cost of using AI can make up for the errors and sometimes imprecise analysis that results. Deepgram claims its approach can outperform the industry standard without sacrificing the speed and cost benefits.

“The old way of doing speech recognition is not going to be the same as future versions,” Deepgram CEO Scott Stephenson told Voicebot in an interview. “The heuristics model of speech recognition has too many flaws; it’s why I wanted to start Deepgram. When we began, we decided to start from scratch with end-to-end deep learning.”The AI now can learn their jargon, learn the background noises at their meetings, and learn their natural cadence of speaking.”

Almost five years after its founding, Deepgram’s platform now offers multiple price points depending on just how precise the client wants the transcription and analysis to be. Stephenson explained that because Deepgram is built on deep learning rather than heuristics, adjusting precision is relatively straightforward, and the standard version platform can outperform most other options.

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Deepgram raises $12 million to train custom speech recognition models for businesses

Deepgram, a Y Combinator graduate building tailored speech recognition models, today announced it has raised $12 million in series A financing. CEO and cofounder Scott Stephenson says the proceeds will bolster the development of Deepgram’s platform, which helps enterprises to process meeting, call, and presentation recordings. If all goes according to plan — if Deepgram’s scale eventually matches that of the competition — it could save organizations valuable time by spotlighting key results.

Deepgram leverages a backend speech stack that eschews hand-engineered pipelines for heuristics, stats-based, and fully end-to-end AI processing, with hybrid models trained on PCs equipped with powerful graphics processing units. Each custom model is trained from the ground up and can ingest files in formats ranging from phone calls and podcasts to recorded meetings and videos. Deepgram processes the speech, which is stored in what’s called a “deep representation index” that groups sounds by phonetics as opposed to words. Customers can search for words by the way they sound and, even if they’re misspelled, Deepgram can find them.

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Deepgram Blog: We raised $12 million to solve speech recognition in the enterprise

The excitement around speech recognition is real: it has the potential to power the next wave of modern applications and give businesses and vendors a competitive advantage. But, with excitement comes misaligned expectations. Speech recognition is a messy, tough and persistent problem for enterprises, one that has languished under existing technology providers for decades. At Deepgram we have been working to change that by rebuilding speech recognition from the ground up. Today, we celebrate a key milestone on our path with a $12 million Series A round led by Wing VC, with participation from NVIDIA, Y Combinator, Compound and SAP.iO.

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