Seattle startup raises $12M to ‘rewrite the software of life’ (with a little help from the technology behind beer)

Arzeda designs custom molecules for use in manufacturing, agriculture and more. Building each molecule requires a complex path of biological engineering, shown above. (Arzeda Photo)

Proteins are incredibly important, but incredibly complicated, molecules. They control 98 percent of all biological functions and are used in industries from manufacturing to agriculture.

(Kurt Schlosser photo)

Seattle-based synthetic biology startup Arzeda has spent the last nine years developing the technology to build custom proteins and other molecules that can do things like grow cheaper food, make tougher nylon and even build stronger plexiglass. The company announced Thursday that it has raised its first round of venture funding with a $12 million Series A, led by the OS Fund.

The technology behind Arzeda traces its roots to a delicious beverage that many of us love: beer.

“The exact same process used to make beer can be altered to ferment sugars and other renewable resources such as agricultural waste into a plethora of valuable chemicals, provided that we can reliably design and manipulate novel metabolic pathways that convert the starting material (feedstock) into the ultimate desired product,” the company writes on its Web site.

Arzeda describes its custom protein development as “rewriting the technology of life,” basically designing proteins that can make new manufacturing and biological feats possible.

The enzyme RA61, designed using Arzeda’s cloud-based platform. (Arzeda Photo)

The company starts the process by designing proteins using its software platform. Its cloud-fueled technology can run through trillions of possible molecules and come up with a handful of ones that may work for a certain job.

Each protein has dozens of unique parts that make it act a certain way, and each of those parts need to be chemically synthesized with precise engineering. Because proteins are so complex, they can’t just be cooked up in a beaker.

Instead, Arzeda has to code genetic material that instructs a cell on how to make the protein. Those genetic instructions are then inserted into a batch of yeast or other small organisms which make the protein using the process of fermentation. The company then tests the different proteins in its lab and finds the right one for the job.

The company said the new funding will help it scale up that process significantly.

“With this Series A funding, we will be able to expand the throughput capacity of our protein design platform and deploy a robust product development pipeline. From concept to industrial-scale production, Arzeda’s existing and new partners will be able to leverage protein design to make better, more sustainable chemicals, food and feed ingredients, materials, and even new molecules that are not found in nature,” Arzeda Co-Founder and CEO Alex Zanghellini said in a press release.

The company is already working with high-profile clients like materials manufacturer DuPont to design proteins that change the makeup of plants and materials.

Arzeda was founded in 2008 by Drs. Alex Zanghelini, Eric Althoff, Daniela Grabs and David Baker based on work by the University of Washington’s Institute for Protein Design, which Baker directs. He also serves on the company’s board of scientific advisors, while the other three co-founders are all executives at the company.

As part of the recent funding, OS Co-Founder Jeff Klunzinger will join Arzeda’s board. The round also includes Bioeconomy Capital, Sustainable Conversion Ventures and WRF Capital, who invested Arzeda’s seed fund of just $250,000.

Seattle is paying the most for its engineers






A recent survey finds data-related jobs among the highest paying in the country.

SAN FRANCISCO — Demand for the nation’s more than 1.8 million software engineers has hundreds of companies scrambling for talent in machine learning and data sciences.

The battle is pitched in coastal cities such as San Francisco, Seattle, Los Angeles, Boston and New York, where start-ups and established companies are dangling six-figure salaries, benefits and the chance to do interesting research, according to a study released today by LinkedIn. The social network for professionals looked at data for engineering talent on its network in March.

Machine learning and data science skills rank as the most in-demand, though both specialties have the least experienced workforces — at less than five years — because they are emerging fields. Consequently, they are fetching the highest compensation, at a median of $129,000 annually.

In the competition for engineers, Seattle — home of Amazon and Microsoft — has emerged as an aggressive bidder, offering $132,000 a year.

The race for software engineers isn’t surprising. The booming tech market expanded 2% last year to approximately 7.3 million workers as the digital economy continued to flourish in jobs for software, cybersecurity and cloud computing, according to Cyberstates 2017, an annual analysis of the nation’s tech industry by technology association CompTIA.

More:Here’s what you need to land America’s best jobs

More:6 people who’ve nabbed the nation’s top jobs share a common trait

The vast majority — 6.9 million — were employed by tech companies. Yet hundreds of thousands of jobs remain unfilled, and demand is tightening due to the need for highly skilled workers in non-tech industries such as banking and healthcare. (LinkedIn lists more than 300,000 open engineering jobs.)

All told, about 4% of the U.S. workforce is employed in the $1.3 trillion industry, about 8% of the national economy, says Tim Herbert, senior vice president for research and market intelligence at CompTIA.

Follow USA TODAY’s San Francisco Bureau Chief Jon Swartz @jswartz on Twitter.

2017 Customer Service Excellence Recognition Program Winners Announced – SYS



Audible, T-Mobile and Mayo Medical Laboratories among honorees at Customer Contact West: A Frost Sullivan Executive MindXchange

SANTA CLARA, California, July 20, 2017 /PRNewswire/ — Frost Sullivan’s Customer Service Excellence (CSE) Recognition Program honors world-class companies and individual leaders today for their outstanding achievement in distinct areas of customer service.  CSE Recognition Program honorees will be presented with their award on October 18, 2017 at the 13th Annual Customer Contact West: A Frost Sullivan Executive MindXchange in Huntington Beach, California. In addition, the Customer Service Excellence High Achiever for each category will be announced at the event.

The CSE Recognition Program honors organizations and individuals that are breaking new ground in customer service excellence. Nominations are entered into one or more of five categories, including omni-channel customer experience, artificial intelligence, web customer experience, social media customer engagement and customer engagement analytics. There are several honorees in each category, from which one High Achiever in each category will be identified.

The CSE Recognition Program is pleased to announce the recipients of the 2017 Customer Service Excellence Recognition:


  • Newegg
  • Vida Health
  • Diligent Corporation
  • Nutshell


  • Worthy
  • ReplyBuy


  • Vida Health
  • Nutshell
  • Zuora
  • MindTouch
  • Spongecell


  • T-Mobile
  • Newegg
  • Zuora
  • Enso Rings
  • Audible


  • ezCater
  • WeddingWire
  • Zuora
  • Dollar Shave
  • Castel Communications
  • Mayo Medical Laboratories
  • Audible 

About The Customer Service Excellence Recognition Program

The Customer Service Excellence Recognition Program, made possible through the coordination of the Frost Sullivan Customer Engagement Digital Transformation practice, Frost Sullivan Research Insights practice and the Frost Sullivan Customer Contact Executive MindXchange, honors companies and individual leaders that are shaping the future of Customer Service. Honored recipients have demonstrated achievement in one or more of five categories:  Omni-channel Customer Experience, Artificial Intelligence, Web Customer Experience, Social Media Customer Engagement and Customer Engagement Analytics. There are several honorees in each category, from which one Highest Achiever in each category is identified.

Companies are vetted through a rigorous two-stage evaluation process. The initial stage involves the completion of a questionnaire application. Questions posed will range from customer engagement capabilities to business outcomes. Entrants are free to apply in one or more categories, provided responses are complete for each section.

Qualifying companies will then progress to the second stage for evaluation by a judging panel consisting of experts from the industry and Frost Sullivan research analysts.

All honorees will be celebrated and the top-scoring project in each category will be announced at the 13th Annual Customer Contact West: A Frost Sullivan Executive MindXchange, taking place October 15-18, 2017 at the Hyatt Huntington Beach Resort Spa in Huntington Beach, California. For more information about the Customer Service Excellence Recognition Program, please go to

About Frost Sullivan

Frost Sullivan, the Growth Partnership Company, works in collaboration with clients to leverage visionary innovation that addresses the global challenges and related growth opportunities that will make or break today’s market participants. For more than 50 years, we have been developing growth strategies for the global 1000, emerging businesses, the public sector and the investment community. Contact us: Start the discussion

Nicole Coons
Marketing Vanguard/Principal Consultant
P: 908.603.7207
E: [email protected]


Extreme to unify wired, wireless campus with Avaya fabric software

Avaya customers as important as technology

Besides technology, Extreme’s acquisition of Avaya’s networking business brought a customer base that Extreme wants to hold. The company plans to keep those customers by honoring all Avaya contracts and continuing to support and service all products.

Catering to Avaya customers is important because Extreme would have had difficulty acquiring them on its own, given the maturity of the networking market, said Jim Duffy, an analyst at 451 Research. “It’s more of a customer grab than any benefit from the Avaya technology.”

Indeed, Extreme has been growing its customer base through a buying spree that started in September 2016 with the $55 million acquisition of Zebra Technologies’ WLAN business. Extreme announced the $100 million Avaya acquisition in mid-March of this year, roughly two weeks before agreeing to buy Brocade’s data center business from Broadcom, also for $55 million. The Brocade portfolio includes switches, routers, and network automation and analytics software.

Extreme’s combined revenue from the acquisitions will reach about $1 billion, according to the company. However, Duffy said he is skeptical the company will be able to grow much larger, given that Cisco, Hewlett Packard Enterprise (HPE), Huawei and other rivals have similar products. 

“I don’t see them taking any Cisco share, I don’t see them taking any HPE share, and I don’t see them taking any Huawei share,” he said.  Also, Extreme still has to effectively integrate all the technologies it has acquired and demonstrate that it can hold onto the new customers.

Drones and phones are the next frontier for AI breakthroughs

The artificial intelligence revolution is being underwritten by the cloud. Every decision made by an AI involves sending information to vast data centres, where it’s processed before being returned. But our data-hungry world is posing a problem: while we can process data at rapid rates, sending it back and forth is a logistical nightmare. And that’s why AI is heading to your pocket.

In essence, this means adding brains to the phones and other technologies we use on a daily basis. “Machine learning and artificial intelligence not only makes devices more autonomous and valuable but also allows them to be more personal depending on what a customer likes or needs,” says Vadim Budaev, software development team leader at Scorch AI.

Much of the work in the area is being led by tech’s biggest companies, which are adding basic AI and machine learning applications to products as they develop them. Facebook has introduced deep learning that can “capture, analyse, and process pixels” in videos in real-time within its apps. Google’s latest framework lets developers build AI into their apps.

Microsoft wants to be a major AI player. Here’s its master plan

Machine learning versus AI: what’s the difference?

Apps are the likely first step for introducing AI to devices, but it’s predicted this will quickly move to other products. “An expanding variety of mobile devices will be able to run machine learning,” says David Schatsky, a managing director at Deloitte. “Virtual and augmented reality headsets; smart glasses; a new generation of medical devices that will be able to do diagnostics in the field; drones and vehicles; and internet of things devices will combine sensing with local analysis.” His company predicts that during 2017, 300 million smartphones will have a built-in neural network machine-learning capability.

The first products using on-device AI and machine learning are starting to appear. Australian startup Lingmo International’s in-ear language translator claims to work without Bluetooth or Wi-Fi. Meanwhile, DJI’s Phantom 4 drone, released in 2016, uses on-board machine vision to stop it from crashing.

AI-powered lip sync puts old words into Obama’s new mouth

Technology developed by Xnor AI is using CPUs (rather than GPUs) to put AI on devices. It claims to be able to detect objects, in real-time on a cellphone. A promotional videoand a report from TechCrunch claims its systems can also be run on a lower-powered device. A Raspberry Pi, for example, could be used to detect knives and guns.

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“Where the data sets are smaller or involving more individualised data sets (such as personal information), it will be significantly more practical to process on-device,” explains Ofri Ben-Porat, from Pixoneye, a firm using on-device machine learning to scan photos.

When successful, there are multiple benefits of running machine learning on a device. To start with, the processing and decision making can be quicker as data doesn’t need to be beamed to a remote location. Keeping data local means it doesn’t have to be transmitted to the company providing the service – giving users greater privacy levels. Apple is testing the model through a system it calls differential privacy.

“Protecting customer information is a major priority for businesses, and we’ve seen in many instances the damage that can be done to a brand where customer data is hacked,” Ben-Porat adds. “Processing data on-device alleviates this issue by ensuring that the data is retained on the user’s mobile rather than being transferred to the server”.

At present, the difficulty in bringing AI to devices at scale lies in computing power. If phones can’t process data quickly enough, AI systems will run down their batteries. Electrical engineers at the Massachusetts Institute of Technology have developed a way for neural networks – one of the key underlying systems behind machine learning – to reduce power consumption and be more portable.

There’s also a new range of chips being developed that can specifically handle machine learning applications. Google’s Tensor Processing Units powers its translate and search systems, while UK startup Graphcore has developed its own machine learning chips. Elsewhere, the field of neuromorphic computing is growing considerably.

On-device artificial intelligence is still in its infancy, but for the wider AI industry to continue to make big breakthroughs it’s going to need all the computing power it can get.