Galley Solutions turns kitchen chaos into recipe for streamlined operations

Galley Solutions, a food data company providing food operators with technology to make more profitable decisions around their culinary operations, raised $14.2 million in Series A funding.

Ian Christopher, COO, started the company with his brother-in-law, Benji Koltai, CEO, in 2017. The food enterprise resource planning tool came out of Koltai’s previous work at Sprig, a delivery-only restaurant started by CEO Gagan Biyani and former Google executive chef Nate Keller.

Christopher explained that in the early days, there was not a system of record, so much of the work was done in a low-tech environment — spreadsheets or pen and pencil. Koltai, who has food sensitivities, kept getting mislabeled meals and having health reactions.

“He went to the culinary team and just said, like, ‘Why are we getting this wrong?’” Christopher told TechCrunch. “We have this source of truth for our recipes, so why isn’t this propagating every other corner of this operation, including the labeling and the allergen information. That was when a sous chef kindly walked him through the chaos that was their kitchen operations.”

Koltai, working with Keller, took a recipe-centric approach and coded the first version of Galley, which provides clean recipe data, predictive purchasing, smart inventory and accurate food production planning. Keller is now working with Galley as a part of its customer success program.

Galley Solutions

Galley Solutions website example. Image Credits: Galley Solutions

The company’s technology is a kitchen productivity tool that focuses on core recipe data, and the purchasing and inventory aspects stem from that. For example, the carrots for a carrot soup are mapped to real-time vendor items so the kitchen can make better purchasing decisions and more accurate recipe margins.

Galley works with companies like DoorDash, Aramark and Chowbotics. The company grew its subscription revenue by 280% from last year and saw a 146% net dollar retention in the first quarter of 2022, Christopher said.

It was also at the point in its growth where it was reaching profitability and was close to cash-flow positive when leadership decided to take advantage of its position to aggressively scale.

That’s where the Series A comes in. The investment was led by Astanor Ventures and includes participation from existing investor Zetta Venture Partners. This gives the company $20 million in total funding to date. Galley is the latest startup, bringing technology into the kitchen, to receive funding. Earlier this year, we also saw Meez raise $6.5 million for its recipe software.

Meanwhile, the new funding enables the company to scale and move into secondary marketplaces to connect supply and demand with a focus on automating the purchasing decision and purchasing activity.

“We were able to get to millions of dollars in revenue with two salespeople in our organization, so we have to scale our sales team,” Christopher said. The new funding will also go toward product and engineering.

Up next, the company is focusing on sustainability as part of its partnership with Astanor, including sustainability impacts and initiatives around food waste.

WhatsApp ramps up revenue with global launch of Cloud API and soon, a paid tier for its Business App

WhatsApp is continuing its push into the business market with today’s news it’s launching the WhatsApp Cloud API to all businesses worldwide. Introduced into beta testing last November, the new developer tool is a cloud-based version of the WhatsApp Business API — WhatsApp’s first revenue-generating enterprise product — but hosted on parent company Meta’s infrastructure.

The company had been building out its Business API platform over the past several years as one of the key ways the otherwise free messaging app would make money. Businesses pay WhatsApp on a per-message basis, with rates that vary based on the region and number of messages sent. As of late last year, tens of thousands of businesses were set up on the non-cloud-based version of the Business API including brands like Vodafone, Coppel, Sears Mexico, BMW, KLM Royal Dutch Airlines, Iberia Airlines, Itau Brazil, iFood, and Bank Mandiri, and others. This on-premise version of the API is free to use.

The cloud-based version, however, aims to attract a market of smaller businesses, and reduces the integration time from weeks to only minutes, the company had said. It is also free.

Businesses integrate the API with their backend systems, where WhatsApp communication is usually just one part of their messaging and communication strategy. They may also want to direct their communications to SMS, other messaging apps, emails, and more. Typically, businesses would work with a solutions provider like Zendeks or Twilio to help facilitate these integrations. Providers during the cloud API beta tests had included Zendesk in the U.S., Take in Brazil, and MessageBird in the E.U.

During Meta’s messaging-focused “Conversations” live event today, Meta CEO Mark Zuckerberg announced the global, public availability of the cloud-based platform, now called the WhatsApp Cloud API.

“The best business experiences meet people where they are. Already more than 1 billion users connect with a business account across our messaging services every week. They’re reaching out for help, to find products and services, and to buy anything from big-ticket items to everyday goods. And today, I am excited to announce that we’re opening WhatsApp to any business of any size around the world with WhatsApp Cloud API,” he said.

He said the company believes the new API will help businesses, both big and small, be able to connect with more people.

In addition to helping businesses and developers get set up faster than with the on-premise version, Meta says the Cloud API will help partners to eliminate costly server expenses and help them provide customers with quick access to new features as they arrive.

Some businesses may choose to forgo the API and use the dedicated WhatsApp Business app instead. Launched in 2018, the WhatsApp Business App is aimed at smaller businesses that want to establish an official presence on WhatsApp’s service and connect with customers. It provides a set of features that wouldn’t be available to users of the free WhatsApp messaging app, like support automated quick replies, greeting messages, FAQs, away messaging, statistics, and more.

Today, Meta is also introducing new power features for its WhatsApp Business app that will be offered for a fee — like the ability to manage chats across up to 10 devices. The company will also provide new customizable WhatsApp click-to-chat links that help businesses attract customers across their online presence, including of course, Meta’s other applications like Facebook and Instagram.

These will be a part of a forthcoming Premium service for WhatsApp Business app users. Further details, including pricing, will be announced at a later date.


Data intelligence startup Near, with 1.6B anonymized user IDs, lists on Nasdaq via SPAC at a $1B market cap; raises $100M

The IPO window has all but closed for technology companies in the wake of a massive downturn in the market, but an opening still remains for some, in the form of SPACs. Near — a data intelligence company that has amassed 1.6 billion anonymized user profiles attached to 70 million locations in 44 countries — today announced that it would be listing on Nasdaq by way of a merger with KludeIn I Acquisition Corp., one of the many blank check companies that have been set up for the purposes of taking privately held companies public, at a valuation “near” $1 billion. It will trade on Nasdaq using the “NIR” ticker.

Alongside that, the company is picking up a $100 million equity investment into its business from CF Principal Investments, an affiliate of Cantor Fitzgerald. 

If you’ve been following Near or the SPAC market, you might recall that there were rumors of KludeIn talking to Near back in December. At the time Near was reportedly aiming at a valuation of between $1 billion and $1.2 billion with the listing. The last several months, however, have seen the IPO market virtually shut down alongside a massive drop in technology stocks across the board and a wider downturn in tech investing overall, even in much smaller, earlier-stage startups.

Near, originally founded in Singapore in 2012 and now based out of Pasadena, had raised around $134 million in funding, including a $100 million round in 2019 — which had been the company’s last big raise.

Its investors include the likes of Sequoia India, JP Morgan, Cisco and Telstra (which have agreed to a one-year lock-up according to KludeIn’s SEC filings). Company data from PitchBook notes that Near had tried but cancelled a fundraise in May 2021.

All in all, Near is an interesting example when considering the predicament that a lot of later-stage startups might be finding themselves at the moment.

On the one hand, the company has some big customers and some potentially interesting technology, especially in light of the swing from regulators and the public toward demanding more privacy in data intelligence products overall.

It works with major brands and companies including McDonald’s, Wendy’s, Ford, the CBRE Group and 60% of the Fortune 500, which use Near’s interactive, cloud-based AI platform (branded Allspark) to tap into anonymised, location-based profiles of users based on a trove of information that Near sources and then merges from phones, data partners, carriers and its customers. It claims the database has been built “with privacy by design.”

It describes its approach as “stitching” and says that it’s patent-protected, giving it a kind of moat against other competitors, and potentially some value as an asset for others that are building big data businesses and need more privacy-based approaches.

On the other hand, while financials detailed in KludeIn’s SEC filings show growth, it is at a very modest pace — numbers may not look that great to investors especially in the current climate. In 2020, Near posted revenues of $33 million, with estimated revenues of $46 million for 2021, $63 million for 2022 and $91 million for 2023. The company estimates that its gross profit margin for this year will be 72% ($44 million) but equally estimates that EBITDA has been negative and will continue to be until at least 2024.

Image Credits: Near

Looking out further than Near, it will be interesting to see how many others follow the company in taking the SPAC exit route, which has proven to be a controversial vehicle overall.

On the plus side, SPACs are lauded by supporters for being a faster, more efficient route for strong startups to enter the public markets and thus raise money from more investors (and giving sight of an exit to private investors): this is very much the position Near and KludeIn are taking.

“Enterprises around the world have trusted Near to answer their critical questions that help drive and grow their business for more than a decade. The market demand for data around human movement and consumer behavior to understand changing markets and consumers is growing exponentially and now is the time to accelerate the penetration of the large and untapped $23 billion TAM,” Anil Mathews, founder and CEO of Near, said in a statement. “Going public provides us the credibility and currency to double-down on growth and to continue executing on our winning flywheel for enhanced business outcomes over the next decade.”

“I am thrilled to partner with Anil and the entire team at Near as they continue to help global enterprises better understand consumer behavior and derive actionable intelligence from their global, full-stack data intelligence platform,” added Narayan Ramachandran, the chairman and CEO of KludeIn. “We believe this merger is highly compelling based on the diversified global customer base, superior SaaS flywheel and network effects of Near’s business, highlighted by the company’s strong customer net retention.”

On the minus side, those positives are also the very reasons for some of SPAC’s problems: Simply put, they have enabled public listings for companies that might have found it much harder, if not impossible, to do so through the scrutiny of more traditional channels. Sometimes that has played out okay anyway, but sometimes it has ended badly for everyone. Just this week, Enjoy — which also listed by way of a SPAC — said that it was on course to run out of money by June and was reviewing its strategic options.

Time, the appetite for more data intelligence and potentially some factors out of its control like the investment climate, ultimately will show which way Near will go. The transaction is expected to generate $268 million of gross proceeds, assuming there are no redemptions and a successful private placement of $95 million of KludeIn common stock, KludeIn said.

Former AWS engineer sets out to build a better log search engine

When ZincSearch founder Prabhat Sharma worked as a solutions architect at AWS, he helped customers implement a lot of tools on top of AWS infrastructure services. He noticed that most of the solutions that were designed to help companies sift through log data were from a different era, and those that weren’t, hadn’t really caught on in a big way.

He decided it was time to build a more modern alternative and last August he began noodling with an idea. “I looked around, and then I saw that there were a couple of people who had tried building a couple of things. But none of them was actually good enough. So then I thought, let me give it a shot and see if I can build something,

He spent several months developing what would become ZincSearch. In December, he put it on GitHub, and was happily surprised to find that it got some traction. The largest incumbent in this space is Elastic, the makers of ElasticSearch, a public company founded in 2012. He wanted to build something that was a modern alternative to that tool without some of the overhead he observed when he was at Amazon. So he set out to create a single binary that would set up quickly and not use a ton of RAM.

He believes that the solution he built is an improvement over what’s out there, and it appears that users agreed. The launch generated some discussion on Hacker News and Reddit, and quickly built up 2000 stars on GitHub – today the tool is approaching 8,000 stars, a sign that people are liking it.

This did not go unnoticed in venture circles, who monitor open source projects looking for potential companies to invest in. As investors reached out, Sharma realized he was onto something. In April, he left his job at Amazon to launch ZincSearch as a company.

The startup is still very early and still a work in progress as an alpha project, but Sharma has big plans. “Right now it is still in alpha, but I plan to make a general release within three to six months and offer a cloud service by the end of the year, most likely,” he said.

As he completes the administrative aspects of legally forming the company, which is only a couple of months old at this point, he is looking to hire six people by the end of year to help finish the open source project and launch the cloud version. As a first-time founder just putting the initial pieces of the company together, he is only beginning to think about hiring and how to bring in diverse employees, but he knows diverse teams perform better, and he says that he is looking at ways to make that happen.

The company announced a $3.6 million seed investment to help push his vision forward. The round was led by Nexus Venture Partners with participation from Dell Technologies Capital, Secure Octane, Cardinia Ventures and several tech industry leaders.

Fetcher raises $27M to automate aspects of job candidate sourcing

Reflecting the growing investor interest in HR technology startups, Fetcher, the talent acquisition platform formerly known as Scout, today closed a $27 million Series B funding round led by Tola Capital with participation from G20 Ventures, KFund, and Accomplice. The new money — $7 million in debt and $20 million in equity — brings the startup’s total capital raised to $40 million, which co-founder and CEO Andres Blank says is being put toward international expansion and building out the Fetcher platform with new applicant tracking system (ATS) integrations and customer relationship management capabilities.

Fetcher was co-launched in 2014 by Blank, Chris Calmeyn, Javier Castiarena, and Santi Aimetta as a professional networking app called Caliber. After a few years, the founding Fetcher team decided to pivot into recruitment, leveraging some of the automation technology they’d built into Caliber.

“Hiring high-quality, diverse candidates had always been a pain point for me. At one of my prior startups, I personally experienced this issue, and after bringing on a recruiting team to help scale hiring efforts, I saw that their time was also too valuable to be spent on the manual, repetitive tasks that come with sourcing candidates,” Blank told TechCrunch in an email interview. “Rather than relying on expensive staffing fees, I thought there must be a better way to keep sourcing in-house, without it taking up too much time and energy on the talent acquisition teams and hiring managers.”

Through a Chrome extension, Fetcher’s platform ties in with ATS products as well as Gmail and Outlook to allow recruiters to source candidates directly from LinkedIn. Fetcher filters jobseekers into prebuilt email workflows, offering analytics including progress toward diversity goals at the individual, team, position, and company levels.


The Fetcher candidate directory.

Fetcher also performs predictive modeling, automatically gauging the interest of job candidates from their replies, and “automated sourcing,” which runs in the background to push applicants through vetting processes via automated emails.

“A great candidate experience is essential for any company, and part of that experience comes from building long-term relationships with candidates over time. Fetcher’s candidate directory allows companies to remarket to qualified candidates, set up reminders for future connections, and add additional outreach emails to the automated sequences,” Blank said. “Overall, the goal is to make it simple for companies to store, update, and connect with great candidates over time, messaging them about future job opportunities, milestones at the company, and more.”

The reliance on algorithms is a bit concerning, given the potential for bias — Amazon infamously scrapped a recruitment algorithm that favored male engineers and New York City recently placed restrictions on the use of AI in hiring. When asked about it, Blank asserted that the platform’s automation technologies allow for “a more diverse group of prospects” to push through the hiring funnel. He also highlighted Fetcher’s outreach policy, noting that people who don’t wish to be contacted about opportunities via Fetcher can send data deletion requests.

“[O]ur secret sauce here at Fetcher is combining both machine and human intelligence in order to minimize the biases that exist on both sides,” Blank said. “Beyond this, we also have diversity metrics on each search (visible on our platform to the client too), which keeps us in check. If we’re over- or under-indexing anywhere on the gender or demographics front, the platform can course correct. Finally, we remove selection biases from the client. The way we do this is that once a client trusts that the search is heading in the right direction (after vetting a handful of candidates upfront), they place the search on full automation. This means that going forward, they are no longer vetting every candidate, but simply reaching out to all qualified candidates that are found for [a given] open role.”

Blank linked to case studies from customers like, which recently used Fetcher to hire employees mostly from underrepresented groups. But biases can enter at many different, often unpredictable stages of the pipeline. As Harvard Business Review’s Miranda Bogen writes: “For example, if [a] system notices that recruiters happen to interact more frequently with white men, it may well find proxies for those characteristics (like being named Jared or playing high school lacrosse) and replicate that pattern. This sort of adverse impact can happen without explicit instruction, and worse, without anyone realizing.”


Image Credits: Fetcher

The risk doesn’t appear to be dissuading recruiters. Fetcher currently has over 350 customers (growing 10% month-over-month) including Behr Paint, Albertson’s, Foursquare, and Shutterstock., and annual recurring revenue tripled in the last 12 months.

Beyond the strong top-line numbers, Fetcher is benefiting from the broader boom in the HR tech segment, which has seen high venture capital activity over the past few months. According to Pitchbook, HR tech startups collected more than $9.2 billion in venture capital funding globally from January 2021 to October 2021 — a 130% jump from 2020’s total.

“Fetcher is uniquely positioned as one of the only software-as-a-service recruiting platforms to automate both candidate sourcing and email outreach efficiently,” Blank said. “Rather than using a straight database model, Fetcher is the only sourcing solution that can truly automate the sourcing process for companies, based on its unique combination of ‘machine learning with human intelligence.’ This model allows for what feels like a 24/7 sourcer to work in the background for each client. By automating both the sourcing and outreach sides of recruiting, Fetcher can reduce the number of internal sourcers and recruiters a company needs, as well as significantly reduce the budget being spent on outside recruiting firms, agencies, or consultants.”

Fetcher employs 45 people, currently, and plans to double that number by the end of the year.

Everstream Analytics secures new cash to predict supply chain disruptions

Everstream Analytics, a supply chain insights and risk analytics startup, today announced that it raised $24 million in a Series A round led by Morgan Stanley Investment Management with participation from Columbia Capital, StepStone Group, and DHL. CEO Julie Gerdeman said that the new money would be used to “propel technology innovation” and “further global expansion.”

Everstream, which was launched as Resilience360 and Riskpulse, provides predictive insights for supply chains. Drawing on billions of supply chain interactions, the company applies AI to assess materials, suppliers, and facilities for risk.

Plenty of startups claim to do this, including Backbone, Altana, and Craft. Project44 recently raised $202 million to expand its own set of predictive analytics tools, including estimated time of arrivals for shipments.

But what sets Everstream apart is its access to proprietary data that goes beyond what competitors are leveraging, according to Gerdeman.

“[Everstream provides] visibility into essentially every network, component, ingredient, ​and raw material around the world,” she told TechCrunch via email. “Connected business networks, scalable computing power, graph data base technology, and advances in AI algorithms enable Everstream to combine massive volumes of public and proprietary data to build a model of the global supply chain.”

As new data enters the platform, Everstream, which integrates with existing enterprise resource planning systems, retrains its AI system to reflect the current supply chain environment. Customers receive proactive warnings based on signals including financial reports and news of weather events, environmental and sustainability risks, and natural disasters.

For example, Everstream can warn businesses when it might be difficult to source a specific material and how likely customers are to cancel, increase, or move forward orders. It can also provide suggestions for optimizing logistics operations based on metrics such as timeliness, quality, and cost of goods shipped.

“Everstream’s AI-based models and preset dynamic thresholds can be used to predict disruptions and prescribe recommendations to mitigate risk and deliver better results to the business needs,” Gerdeman added. “[Everstream] identifies the most impactful risks in the network and creates targeted insights-based on inputs from the … platform, including incident monitoring, predictive risks, ESG, and shipment data — slashing time, cost, and complexity.”

Most would argue these are useful tools at a time when uncertainty continues to dog the supply chain — assuming Everstream’s AI systems perform as well as advertised. While some surveys show tepid adoption of predictive analytics among the supply chain industry, Gartner recently found that 87% of supply chain professionals plan to invest in “resilience” within the next two years, including automation and AI.

Investors seemingly see the potential. Last year was a banner year for venture-backed supply chain management companies, which saw $11.3 billion in funding, according to Crunchbase.

For its part, Everstream claims its customer base has grown 550% to date in 2022 and now includes brands like AB InBev, Google, Bayer, Schneider Electric, Unilever, and Whirlpool. Mum’s the word on concrete revenue numbers; Gerdeman demurred when asked about them.

“The pandemic has illustrated why deep visibility is needed not only into a company’s network, but down to the component, ingredient, ​and raw material level, because it doesn’t matter if the company’s supplier is operational if their suppliers are not,” Gerdeman said. “Everstream’s insights are not only predictive in nature, but they are also prescriptive – meaning we not only tell clients what’s coming next, but also what they should do about it.”

Everstream, which employs 100 people, has raised $70 million in equity and debt funding so far.

Stripe expands its infrastructure play with Data Pipeline to sync financial data with Amazon and Snowflake

Stripe — the payments giant valued at $95 billion — is on a product sprint to expand its services and functionality beyond the basic payments that form the core of its business today. Today the company took the wraps off Data Pipeline, an infrastructure product that will let its users create links between their Stripe transactions data and data stores that they keep in Amazon Redshift or Snowflake’s Data Cloud.

The move underscores how Stripe is positioning itself as more than just a payments provider, but a larger financial services and data powerhouse, a “financial infrastructure platform for businesses” in its own words.

The launch comes just weeks after the company announced Financial Connections, which lets Stripe customers connect with their customers’ banking services to pull in more complete financial data about those users.

Data Pipeline — which has been working in a closed beta up to now — has already picked up a few early customers: ChowNow, Housecall Pro, HubSpot, Lime, Shipt, and Zoom, which Stripe said use it to “automate downstream reporting and identify growth opportunities.” In other words, payments are still happening, but now Stripe’s turning the payments data result from those into a profit center of its own.

The product will let users incorporate Stripe financial data more comprehensively and easily with other business information, which in turn will let those users leverage that data in wider business intelligence efforts, as well as in financial reporting and in their work monitoring business activity for fraud, security issues and more.

This is notable for Stripe launching an infrastructure product, specifically in the area of ETL (extract, transform, load), which it built from the ground up internally, with the aim of replacing third-party products for its users. It is not the first product from the company aimed at the wider area of enterprise analytics, however: in 2017 the company launched Sigma, a tool to track payments data.

“Whereas Sigma allows you to access/query your Stripe data in the Stripe Dashboard, Data Pipeline allows you to access your Stripe data directly in your Snowflake or Amazon Redshift data warehouse,” said Vladi Shunturov, product lead at Stripe, in an emailed interview. “This way, Data Pipeline makes it easier to query your Stripe data in combination with your other business data.”

Snowflake and Amazon work with other third-party ETL providers, and Stripe declined to comment on what financial arrangements, if any, exist with these specific partnerships. It also declined to comment on whether it would be adding other data warehouse providers to that list.

“We’re always considering ways to expand our services and better serve our users, but don’t have any specific plans to share at this time,” said Shunturov

With the Amazon and Snowflake integrations, Stripe partnered with the two to use their respective data sharing technologies to build its product, he said. Specifically, Stripe initiates a data share that enables us to store the user’s Stripe data in the Stripe cluster and we then provide the user read access to this data. “This way, the user can access their data without giving write access to their cluster,” he said. “We are committed to continuously improve data freshness and expand the breadth of business-ready reports and metrics. Accomplishing this required that we build this capability natively on Stripe.”

Shunturov added that the impetus for the product, and perhaps the company’s strategic roadmap for how it’s building out these new wave of services overall, stems from requests from users.

Stripe users, and especially larger users, have requested easier ways to not just export but continuously sync their Stripe data to their data warehouse so they can centralize their Stripe data with other business data without having to build or maintain an API integration themselves,” he said. “By making product-level reports and metrics available we are also significantly reducing the data engineering investment our users have to turn raw data into business insights. Snowflake and Amazon Redshift were selected as our initial launch partners due to high user demand. In fact, both were the most widely-used data warehouses among the Stripe user community.”

Data Pipeline is currently only in the U.S., for Stripe users that also use Amazon Redshift or Snowflake’s Data Cloud.

New Relic enters the security market with its new vulnerability management service

New Relic, which has long been known for its observability platform, is entering the security market today with the launch of a new vulnerability management service. Aptly named New Relic Vulnerability Management, the service aggregates data from botth its own native vulnerability detection system and third-party tools, giving security, DevOps, SecOps and SRE teams a single service for monitoring their sotware stack for vulnerabilities.

“Minimizing security risk across the entire software development life cycle is imperative — and we are seeing more pressure on DevOps to manage risk while making sure it doesn’t become a blocker to the pace of innovation,” said New Relic CEO Bill Staples. “New Relic Vulnerability Management delivers more value to engineers harnessing the power of observability with our platform approach, and accelerates our mission to help every engineer do their best work with data, not opinions.”

The company argues that one if its major differentiators is that this new tool can integrate with third-party security tools. This in turn should help teams prioritize which security risks to focus on (because there are always more than any team can handle), with the new service also helping them to identify which actions to take to remediate those risks).

The new service is part of a series of announcement New Relic made at the CNCF’s KubeCon + CloudNativeCon conference and its own FutureStack event today. Other announcements include enhancements to the company’s application performance monitoring service (which now collects logs in context), new partners in its Instant Observability ecosystem (which now features more than 470 integrations), and a major new partnership with Microsoft, allowing Azure users to use New Relic as their default observability platform natively inside the Azure Portal.

Apple unveils online training to close IT skills gap around managing Apple devices

As with many skilled professions these days, there is a gap between demand and supply when it comes to IT pros. As more people turn to Apple devices at work, whether computers, phones or tablets, the need for people who can service and manage these devices has increased.

While we may find ourselves in an economic downturn at the moment, it doesn’t really change the math when it comes to the IT skills gap we are seeing, one that is expected to linger until the end of the decade.

To address this issue, Apple announced it has updated its certification and training for IT pros and management who are working with Apple products. That includes two specific courses being added online: Apple Device Support and Apple Deployment and Management.

“The training has been completely redesigned and moved to an online, self-paced format. Users can further demonstrate their competency with two new exams and earn certification from Apple,” the company said.

Susan Prescott, Apple’s vice president of enterprise and education marketing says the company is simply addressing the demand it’s been seeing in the market with these updated offerings, while giving people an opportunity to train for high paying jobs in a convenient way. “Apple Professional Training helps anyone with an interest in technology — whether they are changing careers or upping their skill set — to pursue high-paying IT jobs with certifications that will stand out to potential employers.”

Apple Certification course example looking at setting up an iPhone or iPad.

Image Credits: Apple

She says that by moving the programs online, it opens them up to a much wider group of people to take advantage. “We believe deeply in inclusion in technology, so the new courses are self-paced and freely available, and we are working to ensure ability to pay isn’t a barrier to earning Apple certification,” she said in a statement.

The courses are meant to build on each other, so you start with the more basic Apple Device Support course, and once you complete that, you can move onto the Apple Deployment Management program.

The courses cost $149 each, and are available online starting today at

CipherMode Labs launches open source solution to protect data without encryption expertise

CipherMode Labs CEO and co-founder Sadegh Riazi has been working with encryption his entire career. He studied it as part of his PhD. He was part of the Microsoft SEAL team that worked on improving homomorphic encryption and making it more efficient.

What he found was that while homomorphic encryption allows you to work with encrypted data, it does so at an extremely high resource cost, one that’s so high, it is bad for the environment. He spent much of the first part of his career working to make it more efficient, but he found that even with custom chips, he and his fellow researchers could only move the needle so much.

That’s when he decided to go in a different direction and take an encrypted road less traveled. He teamed up with Ilya Razenshteyn, who had studied encryption at MIT, and they began looking at a method that previously hadn’t been taken very seriously in the encryption community.

“So first of all, it’s very different from homomorphic encryption. It’s based on a completely different paradigm in cryptography. It’s not a better version of it. It’s not a variant of it. I worked on both. So our field is called Secure Multiparty Computation,” Riazi said.

He said that when he began studying SMPC, he saw an area that was largely untapped and perhaps with more possibilities for secure encryption without the computational overhead inherent in homomorphic encryption.

“We have our own challenges, but at least, to put it very simply, it’s a more fertile ground for innovation. We have more room for improvement. We have more dimensions for improvement. And that’s why we’re working on this,” he said.

To be clear, there was a lot of skepticism in the community on whether this particular technology could be put to work to protect encrypted data at scale. “At the beginning of my PhD, when I went to security conferences, and I said that I’m working on this topic, Secure Multiparty Computation, people said ‘oh, that’s a cute cryptographic toy, but it’s never going to be used [widely],’” he said.

But he and Razenshteyn saw the potential and they went against conventional thinking and began building a set of tools to put SMPC to work. They created an open source library, called CipherCore, which they are launching today. This new tool allows researchers to protect data without cryptographic expertise by simply pointing to the data source by writing some code. CipherMode takes care of the encryption for you on the back end by building the appropriate protocol to protect the data.

“We essentially decouple the application layer from the protocol layer, which means users can write very simple programs. And then we are able to create the corresponding protocol that they need to run and to process encrypted data,” he said.

The solution provides a similar set of benefits to homomorphic encryption without the same overhead offering 2-3 orders of magnitude improvement compared to the state-of-the-art homomorphic solutions. It also offers fast computation times and provable security, but in a way that’s easy to implement, and secure even against quantum computers, according the company.

The startup is working on a commercial version they expect to be ready some time later this year.

In addition to launching the open source library today, the startup also announced that it has closed a $6.7 million in seed investment led by Innovation Endeavors with participation from Pillar VC, the National Science Foundation and several industry luminaries.