SAP’s SAP.io Foundry debuts the graduates of its second women-focused accelerator

SAP, the German-based enterprise software giant, has unveiled the New York-based cohort from its SAP.io Foundry accelerator programs focused on women-led technology companies. The first program was launched in San Francisco in July 2017, and while the company has launched additional accelerator programs in Berlin and Tel Aviv (with plans for a Paris accelerator in […]

SAP, the German-based enterprise software giant, has unveiled the New York-based cohort from its SAP.io Foundry accelerator programs focused on women-led technology companies.

The first program was launched in San Francisco in July 2017, and while the company has launched additional accelerator programs in Berlin and Tel Aviv (with plans for a Paris accelerator in the Fall), it’s SAP’s San Francisco and New York programs that have a specific focus on women and founders of color, according to Vanessa Liu, a vice president in charge of the New York program.

“The first one launched last summer, with San Francisco that was in July. Berlin launched in the fall with TechStars as a partner, Tel Aviv launched with The Junction,” Liu said. 

The partnerships with Techstars in Berlin and The Junction in Tel Aviv were designed solely to gain exposure to those markets, while the San Francisco and New York programs focused on diversity — as well as building out the SAP network among startups.

The Foundry accelerator programs are independent from the company’s $35 million Foundry fund, according to Liu. Companies that progress through the program give up no equity and receive no capital. Rather, the companies involved get access to the SAP network of partners and customers and the companies various technical and support services, Liu said.

“This is more about how do you work together with SAP and customers like GE, Coca Cola, and Stanley Black & Decker,” said Liu. 

For the New York cohort that demoed their wares yesterday, eight of the nine companies that participated were also based in New York, with one group of founders making the trek up from Georgia for the program.

And while there’s been no instance yet where companies that graduate from the accelerator receive a capital commitment later from the Foundry fund, Liu did not rule out the possibility.

That Foundry fund typically will invest between a quarter of a million and one million dollars into companies focused on machine learning, big data, and other enterprise software related applications. Checks are typically $250,000 at the seed stage increasing to $1 million as a company grows into a Series A investment.

In some ways, Liu said, the Foundry fund was a way for SAP to build on the work it had done with startups through its (now independent) Sapphire Ventures fund. That had been the vehicle SAP had previously used to connect with the startup world and early stage tech companies and entrepreneurs.

“We’re definitely not the first to market,” said Liu. “But we’re looking at it not just only in making investments and thinking about how to do that but it’s also about cultivating investments and making sure that we do that right.”

For the Foundry accelerator programs in the U.S. doing it right means focusing on gender and racial diversity. The criteria for the program is that at least one c-suite executive and member of the founding team be female. And of the nine companies in the cohort, only two companies were admitted where women were not serving in the chief executive role, Liu said.

These are the executives and companies that went through the SAP.io Foundry Accelerator in New York.

Tongtong Gong, founder and COO of Amberdata, a provider of monitoring and analytics for blockchain infrastructure and smart contract applications.

Margaret Martin, founder and CEO of CN2, a software service that transforms the CAD, 3D and 2D content they create everyday into compelling mobile X-Reality (AR+VR=XR) applications.

Ariadna Quattoni and Paul Nemirovsky, founders of DMetrics, which enables non-developers to build machine learning algorithms to extract insights from any text, in mere hours, and with zero coding.

Kate Brandley Chernis, co-founder & CEO of Lately, is selling a machine learning-based marketing dashboard to provide more consistent marketing messages across large platforms.

Shirley Chen, founder & CEO of Narrativ, sells a contextually relevant smart linking and ad placement technology

Lisa Xu, co-Founder & CEO of Nopsec, a provider of threat prediction and cyber risk remediation solutions for enterprises to prevent security breaches.

Jade Huang, co-founder & CEO of StyleSage,  which enriches product listings with attributes and then maps those products to eCommerce sites.

Jag Gill, founder & CEO of Sundar, a software service connecting apparel brands and retailers with suppliers of textiles, raw materials and garments.

Susan Danziger, Co-founder and CEO of Ziggeo, an embeddable video recorder/player that captures video and provides insights.

Y Combinator invests in HappiLabs to help scientists shop smarter

To create life-saving drugs or groundbreaking technological advancements, scientists first need the proper lab equipment. Everything from intricate and expensive specialized machines to beakers and rubber gloves must be sourced, price compared and ordered by a lab manager before even the first steps toward discovery can take place. But, says Tom Ruginis, CEO and founder […]

To create life-saving drugs or groundbreaking technological advancements, scientists first need the proper lab equipment. Everything from intricate and expensive specialized machines to beakers and rubber gloves must be sourced, price compared and ordered by a lab manager before even the first steps toward discovery can take place.

But, says Tom Ruginis, CEO and founder of the virtual lab manger startup HappiLabs, the process for finding the best and most cost-effective materials for your lab is far from a standardized process.

“The pricing aspect started catching my attention more and more,” Ruginis told TechCrunch. “The profit margin for lab supplies is extraordinarily large. Scientists don’t know that, and even if they know that it’s really hard for them to shop around. There’s nowhere for them to go.”

As an ex-PhD student and lab manager himself, Ruginis has first-hand experience with the struggles — and shortcuts — necessary to properly stock your lab. After leaving his PhD program in pharmacology, Ruginis took a job as a salesman for a scientific distributor and saw that even labs that were floors apart were paying drastically different prices for the same basic supplies.

Taken aback at how far behind scientific purchasing was from the rest of the retail world, Ruginis began compiling his own spreadsheet of pricing information and, with the help of his then-girlfriend (now wife) Rachel, began designing small price-comparison pamphlets for items like gloves and beakers to distribute to local labs to give them a perspective on the pricing space.

“I went to this one lab that I knew was paying too much,” said Ruginis. “I had data showing that a lab three floors up in their building was paying almost half the price. I went straight to [the lab] and showed [them] this. I asked ‘would you give me $10 for this info and if I kept bringing you more pricing info?’ They gave me $10 and in my head that was our first customer.”

Ruginis says the pamphlets grew from one page to eight and it wasn’t long after that labs began coming to him directly for purchasing guidance and outsourcing. And in 2012, with $20,000 raised from friends and family, he launched HappiLabs as a virtual lab manager for labs, spanning topics from biotech and brain research to robotics.

Since its launch, HappiLabs has grown to 14 employees — comprising six PhD virtual lab managers and eight support staff — and, after earning $1 million in 2017, this summer received a $120,000 investment from Y Combinator .

Actively working with 26 labs across the country, Ruginis says the company is ready to begin incorporating more software and technology into the company and is searching for a CTO to help it reach that goal.

“We’re building an internal software tool that’s strictly for lab managers,” said Ruginis. “What some other companies have done is they’ll try to build a tool and give it to all the lab managers on the planet, but what we’re doing is we’re building a tool for us [first]. We’re going to use it for a few years, make it awesome, and then we’ll end up selling that somewhere down the line as a lab manager software.”

Even further down the road, Ruginis says he imagines creating both hardware and software that can not only be installed in labs across the world (think Alexa for scientists) but even support scientific advancement in labs that are out-of-this-world for future scientists working on the red planet or the ISS.

Observe.AI raises $8M to use artificial intelligence to improve call centers

Being stuck on the phone with call centers is painful. We all know this. Observe.AI is one company that wants to make the experience more bearable, and it’s raised $8 million to develop an artificial intelligence system that it believes will do just that. The funding round was led by Nexus Venture Partners, with participation from MGV, Liquid 2 […]

Being stuck on the phone with call centers is painful. We all know this. Observe.AI is one company that wants to make the experience more bearable, and it’s raised $8 million to develop an artificial intelligence system that it believes will do just that.

The funding round was led by Nexus Venture Partners, with participation from MGV, Liquid 2 Ventures and Hack VC. Existing investors Emergent Ventures and Y Combinator also took part — Observe.AI was part of the YC’s winter 2018 batch.

The India-U.S. startup was founded last year with the goal of solving a very personal problem for founders Swapnil Jain (CEO), Akash Singh (CTO) and Sharath Keshava (CRO): making call centers better. But, unlike most AI products that offer the potential to fully replace human workforces, Observe.AI is setting out to help the humble customer service agent.

The company’s first product is an AI that assists call center workers by automating a range of tasks, from auto-completing forms for customers to guiding them on next steps in-call and helping find information quickly. Jain told TechCrunch in an interview that the product was developed following months of consultation with call center companies and their staff, both senior and junior. That included a stint in Manila, one of the world’s capitals for offshoring customer services and a city well known to Keshava, who helped healthcare startup Practo launch its business in the Philippines’ capital.

That effort to know call center operates directly has also shaped how Observe.AI is pitching its services. Rather than going to companies, it is tapping the root of the tree by offering its services to the call centers who manage customer support for well-known businesses behind the curtain. Uber, for example, is one of many to use Philippines-based support centers, but the Observe.AI thesis is that going directly to the source is easier than navigating large companies for business.

One such partner is Concentrix, one of the world’s largest customer support providers with over 100,000 staff and offices dotted around the globe, while the startup said it has tapped Philippines telco PLDT for infrastructure.

In addition to helping understand the problems and generating business, working directly with these companies also gives Observe.AI access to and use of data, which is essential for developing any AI and natural language processing-based systems.

Beyond improving its customer service assistant — which Jain likens to an ‘Alexa for call centers’ — Observe.AI is working to develop a virtual assistant of its own that can handle the more basic and repetitive calls from customers to help free up agents for callers who need a human on the other end of the line.

“We aim to eventually automate a large part of the call center experience,” Jain explained in an interview. “A good set [of customer calls] are complex but a large set can be fairly automated as they are simple in nature.”

The startup is aiming to introduce ‘voicebots’ before March 2020, with a beta launch targeted at the end of 2019.

“The kind of company that will disrupt call centers will come from the east — we truly understand the call center life,” Jain told TechCrunch.

He explained that, while Silicon Valley is a hotbed for tech development, understanding the problems that need to be solved requires spending time in markets like India and the Philippines.

“That knowledge is super, super valuable… someone in the U.S. can’t even think about it,” he added.

That said, Observe.AI is headquartered in the U.S., in Santa Clara. That’s where Keshava, the company CRO, is based with a growing team that is dedicated pre- and post-sales and to building relationships with major software platforms used by call center companies. The idea with the latter is that they can provide an avenue into new business by working with Observe.AI to add AI smarts to their product.

In one such example, Talkdesk, a U.S. startup that offers cloud-based contact center services, has added Observe.AI’s services to what it offers to its customers. Talkdesk CEO Tiago Paiva called the addition “a huge opportunity for call center efficiency and improving the caller experience.”

The startup’s India-based team is Bangalore and it handles technology, which includes the machine learning component. Total headcount is 16 people right now but the founding team expects that will at least double before the end of this year.

Amazon’s newest Alexa Fund recipients are less consumer-focused

Amazon is today announcing the new batch of startups joining its Alexa Accelerator program, powered by Techstars. Members of last year’s Amazon’s Alexa Accelerator program, which backs companies developing new experiences using voice-based technologies, went on to raise over $10 million in venture capital following their participation in the program, says Amazon. The new group […]

Amazon is today announcing the new batch of startups joining its Alexa Accelerator program, powered by Techstars. Members of last year’s Amazon’s Alexa Accelerator program, which backs companies developing new experiences using voice-based technologies, went on to raise over $10 million in venture capital following their participation in the program, says Amazon. The new group includes startups focused on business use cases, STEM education for kids, accessible technology, and more.

The idea behind the accelerator is to help fuel early-stage companies developing for voice, giving Amazon an equity stake in the businesses.

The teams will participate in a three-month long accelerator program that culminates on October 9th with Demo Night, where they’ll present their business to venture capitalists and angel investors, and present their new Alexa experiences.

Amazon says it received hundreds of applications from 44 countries around the world for the 2018 program, and narrowed it down to nine it believes have the most potential.

During the accelerator program, the companies will improve their products, refine their business model, and develop for Alexa, while receiving mentorship from both Techstars and Amazon, as well as the broader Seattle community.

This year’s batch includes participation from the following:

Blutag

Blutag seems especially relevant to Amazon’s interests, as its company is helping stores create voice-based shopping experiences for their customers. It aims to enable retailers to build a voice-based store without coding, allowing customers to shop by asking Alexa for a particular product, then receive personalized product suggestions over text or email.

Conservation Labs

This startup is operating in the smart home space, offering a produce that connects to the home’s main water line to monitor household water use, in order to help homeowners gain money-saving insights and detect leaks.

HelixAI

HelixAI is taking Alexa to scientific laboratories. Not to be confused with genetic services marketplace Helix, this startup’s HelixAI digital assistant can respond to natural language queries to provide scientists and other others in lab settings with real-time information about their operating procedures, lab safety information, workflow and processes, and reference information. For example, you can ask HelixAI things like “what’s the boiling point of benzene?” or “What about the cut site for the restriction enzyme EcoRI?”

Imageous

Imageous is expanding Alexa’s smart home capabilities to the “smart building.” Its smart facilities AI assistant for occupants of commercial buildings brings the benefits of AI technology to building operators. The AI can take advantage of system data (environmental), social data from the occupant population (if they’re reporting they’re hot, cold or comfortable), and external data sources (e.g weather or traffic data), to optimize the building for energy use and comfort with a focus on efficiency and cost savings.

Jargon

Jargon is offering an on-demand translation service that removes language barriers by combining technology with human assistance.

Novalia

Novalia offers a Bluetooth platform connected to paper-thin self-adhesive touch sensors that capture data through touch, in order to create immersive, touch-based experiences, Its audio platform then responds to touch, and turns it into audio through a surface sound actuator or line out. The company has worked with a number of brands on digital signage, touch-based posters, and other projects.

Presence AI

This company is developing AI-powered conversations for small businesses to replace phone calls for things like bookings. Currently it operates over text message, but an Alexa integration could translate this to voice. (A less troublesome version of Google’s Duplex, perhaps, as it doesn’t try to impersonate a human.)

Unruly Studios

Boston-based Unruly is combining STEM education with physical activity by building programmable, electronic floor tiles that kids can code, then jump on, and run around on to play interactive games. The startup includes former engineers from Hasbro, iRobot, Mattel and Rethink Robotics.

Voiceitt

This company is working to make voice technology accessible, with the development of Automatic Speech Recognition technology (ASR) that allows people with severe speech impairments to communicate and be understood by voice. Customers train the software to understand their unique pronunciations, which it then translates into normalized speech output in the form of audio or text. The system can also be used to help people have face-to-face conversations.

(TechCrunch coverage: Voiceitt lets people with speech impairments use voice-controlled technology)

A number of these companies in this cohort are more focused on supporting businesses, rather than consumers, using voice technology. That’s not surprising given Amazon’s recent interest in putting Alexa in the office and in hotels, for example.

Amazon’s Alexa Fund backs the participating startups with an initial $20,000 funding in return for a six percent equity stake. The startups also have the possibility of receiving another $100,000 as a convertible note. 

However, there have been some concerns that along with the rewards, there are also risks for startups joining Amazon’s program. As The WSJ pointed out as did The Information, some entrepreneurs have taken a wary view of working with Amazon’s VC arm – especially after it led the Series A for home videoconferencing startup Nucleus, then proceeded to directly compete with it with the subsequent launch of the Echo Show.

But on the flip side, startups get an early peek at Amazon’s Alexa roadmap, and access to Amazon staff for help in developing Alexa skills.

Last November, Amazon announced an additional $100 million in venture capital for the fund targeted at international investment opportunities. Past Alexa Fund portfolio companies have included ecobee, TrackR, Rachio, Toymail, Ring (which Amazon acquired), Sphero, Vesper, Owlet, and many more.