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Report: U.S. Companies Led AI-Tech Acquisitions 2014-18

AI

Report: U.S. Companies Led AI-Tech Acquisitions 2014-18

.Leading data and analytics company, GlobalData, released a report this week highlighting companies that dominated the artificial intelligence-tech space from 2014-2018. In the report, four out of five top acquirers were U.S. based: Facebook, Microsoft, Apple and Splunk. These companies represent a combined total of 30 acquisitions during the time period studied. Accenture made the list as the only non-U.S. based company, representing six acquisitions total.

“Technology companies have been the dominant deal makers in the AI space. However, with artificial intelligence making inroads into diverse sectors, the buyer universe in expanding and the space is also attracting investments from non-technology companies,” said Aurojyoti Bose, Financial Deals Analyst at GlobalData.

Top Deal Makers-Payment Tech_V2

“The high number of American firms attracting investments in the AI space is a testimony to the country’s dominance in AI technology. The recent launch of American AI Initiative program also augurs well for the development of the sector or start-ups operating in this space,” added Bose.

Additional insights in the report confirm the U.S. as a leading region for targeted acquisitions, representing 70 percent of those acquired by the top five in the list. Regions closely following include the UK, China, India, Canada and Israel due to the talent pool and innovative technology offerings.

Top Deal Makers-Payment Tech_V1 Table

“With increasing adoption of AI across sectors, this space is bound to witness growth in an already burgeoning M&A activity. Corporates are extensively evaluating options to integrate AI in their business operations and automation initiatives. Going forward, AI solutions will be an integral part of their strategies,” Bose concludes.

Source: GlobalData

Streamlining Global Trade: How AI-Enabled Business Networks Can Make Your Business Smarter

We hardly need reminding of the global challenges facing companies today, from increased competition from low cost foreign competitors, to tariffs and changing regulations. As if that weren’t challenging enough, there is the need to keep abreast of technology innovations such as digital business networks, artificial intelligence and blockchain, that are giving startups the opportunity to leapfrog more traditional and mature companies. Within this landscape, companies need to transact with more and more companies, using different systems and often in different time and regulatory zones, which increases the complexity of doing business exponentially.
So, how do you address these issues while modernizing and continuing your business?

Digital Transformation or Consumer-Driven Transformation?

Fundamentally, conducting business is about supplying to the demand of the end consumer. Businesses that win are the ones that create demand with innovative products; or, better serve existing demand. Regardless of the approach, successful companies also understand that they need to be sensitive and responsive to customers’ needs and the market.

Technology serves a vital role as the means by which businesses register demand, plan, forecast, make, move and sell products and services. Technology can make or break a company’s ability to react to changing consumer demand, market shifts, and supply constraints. It can also limit a company’s ability to fully exploit the innovative technologies that are constantly emerging.

For example, most companies are split into functional silos. This is partly corporate culture and partly technological, thanks to the typically inward-focused nature of enterprise systems. Whatever the causes, silos inhibit visibility, speed and agility. Steven Bowen, in his book Total Value Optimization, calls silos “one of the most pervasive and profound barriers to real competitive advantage in every company.” This problem is multiplied across the global business footprint and across the worldwide supply chain, with regions, countries and trading partners having their own systems and silos.

For optimal functioning, all departments need to align around the corporate strategy, and all trading partners around the same objectives, with the primary concern of serving the end customer as effectively as possible. After-all, it takes just one weak link to drag down the performance of the whole supply chain.

Networks Break Out of the Box

We can learn a lot from disruptive leaders in today’s world, as companies like Uber and AirBnB have each disrupted their respective industries because of their ability to sense and respond to consumer demand and match it to supply in real time.

For instance, Uber leverages a multiparty network where all drivers and riders connect to a single platform and drivers are routed to riders, automatically. What’s more, you use the same platform to summon your ride (or your stay in the case of AirBnB), make the contract and transact payment, and rate the other party. Both are “end-to-end” platforms that handle all aspects of the search, booking, payment and review processes. They make the whole process seamless and provide value for both buyer and seller.

The multiparty networks at the heart of these types of businesses, are creating huge efficiencies by eliminating delays and costs and connecting all parties in real-time with a single, authoritative version of the truth. No silos, no delays, no confusion; just a frictionless network for transacting with anyone, anywhere, anytime.

Intelligent Business Networks

The opportunities for business-to-business companies are even greater, because the buyer-seller-mover relationships are complex and multi-layered. There are many more silos, blindspots and delays in a global supply chain compared to a simple one-to-one relationship of rider to driver as in Uber, or guest to homeowner as in AirBnB.Thus, a multiparty network that connects all seamlessly in real-time, has a much bigger impact. Instead of a business partner waiting days or weeks for information to flow upstream, they get it instantly and can react immediately. If a customer’s promotion is selling more than expected, a supplier with visibility to sales can proactively plan for increased orders and ramp up its own supplies and production.

And it gets better. Advanced multiparty networks not only share data, provide real-time visibility, and enable business partners to collaborate as events happen, they also leverage technologies like artificial intelligence and machine learning to optimize and automate processes. “Intelligent agents” monitor conditions across the supply chain, things like sales data, inventory levels, orders, shipments and how they relate to critical milestones. They can predict sales and identify trends and anomalies.

Because all business partners are on the same network, intelligent agents are able to not only flag potential issues, but actually intervene to solve them. They are able to continuously reconcile sales data with projected inventory levels, shipments from ocean and domestic carriers, along with actual lead times, to predict supply and demand issues in advance and then execute proactive solutions to avoid them.

With the vast amounts of data flowing across the network, these systems are ideally suited to machine and deep learning, enabling them to identify patterns and correlations. This data can then be used to predict sales and cascade the order forecast back through the supply chain through distribution centers, manufacturers and suppliers. They continuously monitor the sales and inventory in near real time, and can foresee issues like pending stock out swell in advance. Intelligent agents can then resolve them by autonomously reallocating supply from DCs to stores, adjusting forecasts, creating new orders and helping manage logistics processes.

Better yet, the system monitors the outcomes of these autonomous actions and recommendations, and continuously “learns” and adapts to recommend and execute the most effective resolutions to similar problems in the future.

Data-Driven Agile Ecosystems

This is merely a glimpse into the nature of these emerging intelligent business networks, as they are evolving rapidly. Unlike traditional systems, they are able to harvest new and unstructured types of data, such as weather, traffic, social media chatter and more.
The volume of data in today’s supply chains is set to explode with the increasing use of sensors and live streaming data from containers, vehicles, handheld devices and industrial machinery.

While the sheer volume of data is overwhelming for human managers and for traditional systems, it is ideal for multiparty networks with machine learning algorithms and intelligent agents. They can learn from it and extract new insights that can drive better operations, higher service levels to customers and lower costs for all automatically, and often without the need for human intervention.
Multiparty networks are smarter, enable easy onboarding of trading partners (with a single connection) and provide pre-built solutions with PaaS tools that enable rapid tailoring and extension of functionality to suit changing business needs. Further, the multiparty network model makes it easy to consume both legacy data and leading-edge data from technologies like IoT, product authentication, 3D printing, and blockchain.

It is often said that intelligence is really the ability to adapt to change. Multiparty networks are built to be adaptable through and through. For instance, connections between trading partners are virtual and thus easily reconfigured should trading relationships change. The permissions controlling each trading partner’s rights over visibility and execution on each specific data object is configurable and can easily be turned on and off through a simple user interface. Old and new technologies can co-exist, with multiparty workflows coordinated across different systems and parties. Software developer kits make it easy to adapt existing network solutions or build entirely new ones on the platform.
The result is an extremely adaptable network platform, supporting an agile ecosystem of all trading partners centered on serving the customer at the highest service level at the lowest cost.

About the Author
Nigel Duckworth is a marketing strategist at One Network Enterprises, provider of a blockchain and AI-enabled network platform that enables all trading partners to transact in real time. To learn more, visit https://go.onenetwork.com/article-one or follow them at https://twitter.com/onenetwork

 

Artificial intelligence

THE RISKS, CHALLENGES & OPPORTUNITIES OF PROCUREMENT POWERED BY ARTIFICIAL INTELLIGENCE

Artificial intelligence, better known as AI, is popping up everywhere as the panacea for everything. There appears to be no limit to where it can be used to make businesses work smarter to improve profitability. The International Data Corp. (IDC) Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide forecasts that cognitive and AI spending will grow to $52.2 billion in 2021.

In addition to autonomous vehicles, predictive maintenance and chatbots responding to customer inquiries, AI can have an immediate positive impact on the bottom line by helping companies select suppliers that provide goods and services at the lowest price, with the least amount of risk.

Here are some opportunities and challenges of using AI to increase procurement effectiveness.

Spend Analytics

Spend analytics can be armed with AI software to collect, cleanse, classify and analyze expenditure data to help procurement teams identify excessive costs. For example, AI systems can identify when duplicate suppliers were used to purchase the same goods, urgent purchases were made without using better terms in existing contracts, and when there were suboptimal payment terms.

But to find savings opportunities, AI software has to be good at classifying data. Statistical and pattern-based AI techniques can have weaknesses dealing with one-off purchases and infrequently used suppliers. They can also be stumped by new languages and geographies, which happens more and more often as supply chains become global. The best way to achieve ROI is to pilot a system where there is a large volume of transactions involving standard repeated purchases, so that there are more opportunities for increased efficiencies.

Strategic Supplier Sourcing

By using AI, procurement officers can be armed with knowledge about market conditions, upcoming mergers and acquisitions and real-time product and support comparisons. This ensures that there is a data-driven strategy for awarding suppliers, and that procurement is getting the best possible terms.

Using AI also reduces the time required to analyze all of the supporting data. Evaluating responses to a bid process can be reduced by as much as 80 percent. It can also be used, on a continuous basis, to provide recommendations of suppliers on demand. Responding to market opportunities in seconds versus weeks can speed up time-to-market by receiving the needed parts and materials quicker.

Guided buying is also an AI innovation that enables employees to quickly and easily buy goods and services from preferred suppliers with minimal support from procurement teams. Employees can use voice-activated commands to find the best price or a supplier that can deliver on time where there is an urgent request. Many of these systems enable direct communication with suppliers with embedded rules to ensure that the buying process is compliant with procurement policies.

Many automatic personal assistants also have the advantage of being able to learn from experience. But if the AI system is self-taught, there is the risk that it can be corrupted by outside influences, so communications and procedures need to be protected from hackers or rogue employees. For example, the famous chatbot, Microsoft’s Tay, was taught by trolls to use inappropriate language until it was taken off the market for further testing.

Contract Analytics

The majority of organizations do not have a database containing all of the data in their contracts–and they definitely do not have an easy way to extract all that information–so there’s no quick and efficient way to, for example, view and compare agreements. Using AI, companies can review contracts more rapidly, organize and find large amounts of contract data to significantly lower the possibility of contract disputes and increase the number of contracts that they can negotiate and execute.

For example, using AI, company contracts can be accessed based on renewal dates to inspect conditions and negotiate accordingly. Finance and procurement teams can inspect if pricing discounts are not being consistently applied across the organization in line with contract terms or keep track of the wording of specific clauses in different divisions. The beauty of AI contracting software is that it helps organizations maintain consistency in the terms and usage in all of their contracts, which makes it easier to identify instances of non-compliance, and make sure that less-than-ideal provisions are dealt with quickly.

The Challenge: Data and Application Integration

None of the benefits of AI can be realized without a strong data foundation. Firms need to invest in data management—as well as data and analytics—to have a 360-degree view of their business operations. Only if their CRM, ERP and financial systems are fully integrated can they have access to all the data that is required.

Point-to-point integrations can initially appear to be more cost effective when there are only a few systems connected together. But, in time, with more and more data shared with different departments, suppliers and partners, a third party integration platform can result in lower development and maintenance costs while providing the scalability and consistent data handling that’s needed.

Once companies have a strong data foundation with all of the necessary integrations and data sharing, new machine learning-based platforms can be used to enforce the best procurement practices. Although today AI procurement systems are not always accurate, machine learning uses algorithms to learn from data, allowing platforms to continuously improve themselves.

As we start to see spend analysis platforms classifying data at levels of 98 percent accuracy—the same level as human analysts—it is more and more likely that AI will become a trusted tool for the procurement process.

Tsipora Cohen is the global head of Marketing at Magic Software Enterprises, a global enterprise software company headquartered in Or Yehuda, Israel. Visit www.magicsoftware.com.

Dubai Customs Reports Export & Non-Oil Foreign Trade Growth for Q1

Non-oil trade volumes, exports, and re-exports were all reported with robust growth percentages during Q1 for Dubai, according to information released this week from Dubai Customs. Exports led the growth patterns by increasing 30 percent and accumulating AED 42 billion. Additionally, Dubai’s non-oil trade volumes were reported at 28 million tons, up from 21 million tons for Q1 in 2018. Overall, the report highlighted 7 percent year-on-year growth for non-oil foreign trade.

“This robust performance and marked growth of Dubai’s non-oil foreign trade is an indication that we are on the right path of revenue diversification in alignment with the values and standards outlined in the 50-Year Charter.,” said His Highness Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, Crown Prince of Dubai and Chairman of The Executive Council of Dubai. “The Dubai Silk Road Strategy supports decades of successful investment in developing the emirate’s infrastructure. In line with the vision of His Highness Sheikh Mohammed bin Rashid Al Maktoum, Vice President and Prime Minister of the UAE and Ruler of Dubai, we are committed to developing our government services so that we can become a world-class model for future governments based on knowledge, innovation and advanced AI applications.”

Credit: Dubai Customs

Breaking down the numbers even further, gold, diamonds, and jewelry traded through Dubai saw values increased by nine percent and totaling AED 90 billion. Leading the way in growth contributions, phones were reported at AED 42 billion while petroleum oils increased by more than twice as much from last year.

Credit: Dubai Customs

Among several AI-based initiatives, Dubai Customs boasts the first of its kind ‘Virtual Stock Guarantee’ initiative providing support for re-exports from free zones to external markets. Other disruptive strategies implemented consist of the Smart Vessel Berthing System and the ‘Productivity Engine.’ All three serve a unique purpose from enhanced productivity to cost reduction, all while helping Dubai remain a leader in the market.

“We are pleased to report that trade in Dubai has rebounded in the first quarter of 2019 with non-oil trade growing 7.3% year-on-year to reach AED 339 billion,” added Sultan Bin Sulayem, DP World Group Chairman & CEO and Chairman of Ports, Customs and Free Zone Corporation. “This strong growth has been delivered despite the challenging macro and geopolitical environment, which further highlights the strength and resilience of the Dubai economy. Importantly, we have seen significant growth in both exports (+30%) and re-exports (+7%) which reinforces Dubai’s profile as the key hub for the region. Overall, despite geopolitical headwinds, we remain excited about the outlook for Dubai, particularly with the lead up to EXPO 2020.”

Source: Dubai Customs

How Technology Can Help Recruit and Retain Workers of all Ages

The big question in the minds of business managers–in warehousing, manufacturing, transportation and beyond–is not only how to retain a solid workforce, but how to attract a variety of skillsets and ages within the worker population. It’s not a surprise to imagine that old-school approaches are becoming a thing of the past. As Gen Z workers continue to increase representation in the workforce, employers are faced with the reality of adopting more innovation, technology and mindsets to successfully cater to both older and newer generations of workers. If the current strategy is limiting recruiting capabilities, companies are setting themselves up for failure and limiting their full potential in operations and employee expertise.

What some companies might not realize is the amount of visibility provided with modern technology and the capabilities enabled through automation. As the workforce changes, so does the method of recruiting and the level of technology necessary for successful staffing. Completed.com is a great example of how automation and technology take recruiting one step further through real-time, reliable feedback on employees seeking work in any industry.

“We saw a need to create a platform where one can review anyone in business,” explains Completed.com CEO Michael Zammuto. “One of the reasons employers haven’t had a successful platform like this before is because it’s inherently at risk of being used improperly. The technologies we’re starting to talk about are one potential and significant source of solution for that.

“Completed.com at its core includes machine learning-driven technology which looks at and develops an internal credibility score for every reviewer and every review,” Zammuto continues. “This is one of the more important things that companies like Yelp have been working on, but it’s a difficult challenge. It starts with things like technology where the talent is validated, making it more credible. In addition to that, there’s a lot of pattern matching and sediment analysis that’s done to develop an internal credibility score. This is important because of constructive, professionally-focused reviews.”

So, how much is technology really changing the pace for employee recruitment? Quite a bit, according to Zammuto, who adds that the human element is still very much needed, just for a different role. It’s not about eliminating the human element in recruiting, but reallocating it.

“Everybody in every industry has the same issue: finding and attracting the right talent,” Zammuto says. “We got to see it from the other side–the client’s issue about how they were represented online. We realized that hiring people has become complicated because of technology, but the important part of this topic is that one can automate 99 percent of something that’s content-driven and has a subjective element to it, but you do need people to review things that algorithms determine problems with.”

This insight confirms that technology is becoming more involved within the logistics world, creating even more of a dynamic between connectivity, visibility and efficiency. The secret here is employer and company information are just as valuable to recruiting the right kind of talent as is the available employee information. Just as companies want to learn about the candidates sent their way, employees are looking for an environment that offers more than just a paycheck. If a strong candidate is subjected to a miserable climate, outdated practices and lack of recognition, they’re more likely to visit with competitors that meet their expectations.

In the modern workforce, competing companies are willing to offer tempting salaries with promising career incentives to win over another great employee. Recognition is just as much of a factor as the dollar amount on the paycheck. “Part of this process is ensuring great employees receive recognition they seek while others are held accountable,” Zammuto notes. “This gives you a chance to hold people accountable and celebrate the employees and managers that do great work, and you can take it at face value.”

Taking it even further, regular internal reviews are highly encouraged to successfully maintain talent retention. Not only do these regular checks reiterate accountability for management and the employees, skills development is evaluated and encouraged, ultimately eliminating the mundane aspect of a job. Workers are encouraged with feedback and become motivated to polish their skillset while voicing concerns and addressing redundancies. This is a critical element that goes beyond recruiting and retention as it impacts all aspects of company operations. At the end of the day, your employees are the backbone of the company.

“Most of the traditional methods have either disappeared or been weakened in some way,” Zammuto says. “The remaining method that’s useful is direct referrals to jobs. This is the only remaining valid strategy for getting good candidates to your company, but it’s very slow and doesn’t always scale very well. Companies are having trouble finding people because of the mechanisms for doing so have weakened a lot. With people being more mobile than before, but the information about that mobility shielding the good from the bad performers, how is anyone supposed to hire the right candidates?”

Technology is the common denominator in solving this problem. As companies learn about automation integration for maximizing workflows, this same method should absolutely be considered for selecting the best and preferred types of employees. This approach challenges the old-fashioned methods and takes a granular look at the talent pool, saving time, money, resources and energy invested.

The bigger picture shows that recruiting methods are changing and directly impacting retention. Any company can fill a position, but retaining that position is where the challenge is. What benefit is it to hire a candidate if they don’t contribute and end up leaving? There is no benefit. A company that fills three roles but only retains one isn’t fulfilling its bottom line. Something is missing and technology is the answer to solving this issue. Preserve company resources and time by investing in technology that can identify the best candidates that are looking for long-term careers. The investment upfront will pay off in the long haul.

Google and Facebook Victim of $100 Million in Accounts Payable Fraud: How It Could Have Been Prevented

By now you may have heard about Evaldas Rimasauskas, the Lithuanian man who pled guilty in March of this year to scamming Facebook and Google out of more than $100 million. Impersonating a company with whom both tech giants do business, Rimasauskas sent fake phishing emails containing forged invoices and convinced the companies to wire funds to bank accounts he controlled.

Business email compromise scheme

The U.S. Department of Justice portrayed the crime as a fraudulent business email compromise (BEC) attack, but it’s worth noting that the victims aren’t small mom-and-pop businesses—they’re sophisticated, well-established companies with mature business processes and state-of-the-art procurement and ERP systems. So why did they fall for this scheme?

Let’s take a look at how the criminals took advantage of common “best-in-class” accounts payable (AP) processes and practices. And more importantly, let’s look at how you can avoid falling victim to a similar hoax.

A sophisticated phishing scam

From 2013 to 2015, Rimasauskas orchestrated a combined phishing and invoice scheme targeting Google and Facebook, who confirmed to NPR that they were the companies referred to by the DOJ as “a multinational technology company” and “a multinational online social media company.”

According to the 2016 indictment filed in the U.S. attorney’s office, Rimasauskas registered and incorporated a company with the same name as Taiwan-based electronics manufacturer Quanta Computer, which supplies computer hardware to major tech companies. He then proceeded to open bank accounts in the company’s name in Cyprus and Latvia.

Next, he sent fake emails and invoices to Facebook and Google and directed unsuspecting employees to wire payments to the fraudulent bank accounts that he controlled. And from those bank accounts in Latvia and Cyprus, Rimasauskas laundered the funds by quickly wiring the money into accounts not only in Latvia and Cyprus, but in Slovakia, Lithuania, Hungary and Hong Kong.

How were the employees fooled by the fake invoices?

Using a fairly common phishing practice, Rimasauskas and his co-conspirators sent spoofed emails—emails designed to look like they came from Quanta accounts—to the companies’ AP departments. Many companies only require vendors to email their invoices to an accounts payable  email address; there aren’t any checks in place to ensure that those invoices are coming from a legitimate vendor.

But shouldn’t a human have approved the payment?

As a part of their internal financial controls, most companies require business users to approve invoices. In this case, the approvers were most likely familiar with Quanta and the types of purchases they usually made from them, so they probably had no reason to question the invoices.

Weren’t there purchase orders that the invoices should have matched before they were approved and released for payment?

Yes. It’s not clear from the indictment or news reports how the criminals knew valid P.O. numbers, SKU numbers, pricing, terms, invoice formats or other information for not one but two major companies. One assumption we could make is that they had insider information of some sort from Quanta and therefore could produce invoices with the right PO and line-item information on them.

Why didn’t Facebook and Google realize that the bank accounts to which they were asked to wire money weren’t the same as the Asia-based Quanta accounts on record?

The scammers used correspondent banks in New York and other cities, no doubt realizing that a request to wire funds to Latvia might have aroused suspicion.

How were the companies fooled into transferring such large sums of money?

As some observers have pointed out, the idea that Rimasauskas “just asked the companies for money” sells short the scheme’s high level of sophistication. In addition to being a talented forger, he clearly had in-depth knowledge of big companies’ internal finance operations. Companies like Facebook and Google use advanced invoice and contract management software and follow industry-standard practices such as the three-way match, which verifies price and unit numbers across purchases, invoices, and receipts.

The fact that Rimasauskas was able to skirt these controls indicates that standards like the three-way match may no longer be enough to reconcile documents and prevent overpayments—or outright fraud.  

How your organization can prevent invoice fraud

If the sophistication of Rimasauskas’ scheme was able to defeat the best-in-class procurement system and AP process of a Facebook or Google, what hope do companies have for detecting and stopping overpayments? Here are a few strategies that can work.

Use true electronic invoicing with B2B integration

The problem with emailed invoices is that they must either be keyed in manually by AP staff or entered into invoice automation software, leaving you exposed to errors or scams. When it comes to preventing phishing scams, electronic invoicing through electronic exchange like XML is a much better option than invoices that are emailed as attachments or even sent by snail mail. You may not be able to control what vendors send to you; however, by putting the right controls and technology in place, you can quickly detect fraudulent invoices before they’re paid.

Add controls to verify bank account activity

A vendor request to add or change a bank account should always require a confirmation phone call or other human verification. Solutions like AppZen use AI and data augmentation techniques to detect suspicious activity even when such requests are made electronically.

Require more than a P.O. number; verify work activity or product fulfillment

Purchase orders serve an important function—they verify that approved funding is in place—but they don’t confirm whether goods or services are actually received. For inventory items, a good receipt in the warehouse works as part of the P.O. matching process, but for non-inventory items such as services, procurement systems rely on human requestors to perform a goods receipt or provide approval to fulfill the control of a three-way match.

The problem is that in large organizations (or even smaller ones), it’s impossible for business approvers to accurately determine if every product or service was received as ordered or contracted. As a result, they often rely on their familiarity with the product or service or their knowledge that it’s in the budget, and they end up approving invoices as a matter of routine. Unfortunately, this leaves the process open to error or fraud.

Instead of depending entirely on humans, consider a solution with AI auditing technology that can confirm that receipt of products or services. For example, AppZen can look at unstructured data like ticketing systems, badge data, network logins, and tracking numbers. AI can easily verify whether a product was indeed part of a new shipment and not referenced in previous invoices or already received. Our AI can spot discrepancies and duplicate transactions and to recognize invoice patterns that humans can’t easily see, alerting business approvers if it detects a risk so they can make informed decisions.

Scammer now behind bars—but more are out there

Rimasauskas was eventually caught and extradited to the United States in 2017, where he was charged with wire fraud, money laundering, and identity theft, although he’s only pleaded guilty to wire fraud. He now faces up to 30 years in prison.

“Rimasauskas thought he could hide behind a computer screen halfway across the world while he conducted his fraudulent scheme,” said U.S. Attorney Geoffrey Berman in a statement, “but as he has learned, the arms of American justice are long, and he now faces significant time in a U.S. prison.”

But even though the indictment mentions co-conspirators, Rimasauskas is the only person who has been charged with in connection the crime, meaning he’s potentially part of a larger organization lurking in cyberspace. The risk from similar swindles is growing exponentially: The FBI’s Internet Crime Complaint Center warns that BEC scams are up by 1,300% since 2015 and estimates that companies have been defrauded of more than $3 billion.

Reviewing every invoice you receive is critical if you want to protect your company from falling victim to scams like the one that targeted Facebook and Google. With AppZen’s AI platform, you can audit 100% of your invoices before you pay them, flagging only high-risk spend like errors or fraud for manual review.

Anant Kale is the Co-Founder and CEO of AppZen where he’s passionate about helping companies audit every dollar of spend with artificial intelligence.  As CEO he is responsible for the product vision and execution of the company’s broad mission. Previously he was the VP of Applications at Fujitsu America from 2009-2012, responsible for product management, and delivery of Fujitsu’s applications and infrastructure for enterprise. He has 15+ years of experience in software development. He has an MBA and a BS in Finance and Engineering from Mumbai University.

ProMat Expo 2019: Day One Overview

Day one of ProMat Expo 2019 in Chicago concluded with thousands of attendees more educated on industry trends, products, and expert insight than when they arrived.

The trade show featured a vast array of massive displays, game-changing products, and innovative technology solutions – from robotics and disruptive AI, to packaging and warehouse solutions to support seamless operations and reduced inefficiencies.

With dozens of education seminars to choose from, the primary themes focused on AI integration and challenged perceptions on trends such as lean manufacturing. Keynote speakers took education one step further through comprehensive analysis and presentations filled with valuable expert knowledge and key takeaways essential for stepping up operations in 2019.

Among the presenting speakers included topic expert Scott Redelman, National Manager with Toyota Forklift in Atlanta, who took the trend of lean manufacturing and debunked common misconceptions on how to successfully integrate lean methods into operations. Redelman emphasized the importance of fully understanding the problems lean manufacturing solves before implementation.

“Lean manufacturing reduces process, not manpower,” he said.

Artificial Intelligence was another topic focal point with an entire morning filled with tech and AI-focused education seminars. Among these topic experts was Omar Rashid, Vice President of Operations Development at DHL Supply Chain. Rashid took a granular look at what drives the integration of AI, citing the goal of a dynamic environment as a key driver. Rashid also made it clear that although AI supports operational efficiencies, “there will always be a role for humans.”

As day two quickly approaches, Global Trade Magazine will continue capturing the best knowledge and industry expertise while learning about new challenges in innovation and technology solutions to share with our readers.

generative AI market platform edge

ORITAMES APS Scheduler v2.5 Breaks Traditional Barriers

Thanks to increased efforts in autonomous Artificial Intelligence, the ORITAMES APS Scheduler v2.5 – created by Brussels-based company MangoGem S.A., is now capable of handling levels of resources and scenarios of equipment, people, and consumables.

“The ORITAMES APS Scheduler v2.5 uses AI-assisted autonomous machine learning to explore optimization scenarios better than traditional approaches, combining the best of machine computing power and human know-how to facilitate better planning and scheduling,” said Ben Rodriguez, Chief Technology Officer of MangoGem. With solver heuristics notoriously difficult to fine tune, the ORITAMES APS Scheduler v2.5 discovers which settings work best, checks validity and detects trends in data to improve ramp-up and adoption. It can also discover the most promising improvement scenarios and propose them as potential solutions to human planners. It combines several AI-assisted machine learning meta-heuristics including Genetic Algorithms (GA), Taboo Search (TS), Simulated Annealing (SA), Swarm Intelligence (SI) amongst others.”

Photo: MangoGem S.A.

By breaking the barriers of a traditional APS, ORITAMES APS v2.5 sets a new standard by taking on and solving complex and multi-layered cases typical for larger companies.

“The use of AI-assisted autonomous machine learning also eases the integration and reduces the cost of implementation of the ORITAMES APS Scheduler v2.5 within overall supply chain management (SCM) strategies by making modeling easier, improving data quality and decreasing dependency on human expertise,” he concluded.

This advanced software platform was specifically designed to cater to a variety of industries including discrete manufacturing, construction and infrastructure projects, logistics and transportation, equipment and property maintenance, engineering projects and service organizations.

“The AI-assisted disruptive technology delivered in ORITAMES APS Scheduler v2.5 is capable of solving many of the operational performance challenges of Industry 4.0,” concluded Ben Rodriguez, CTO of MangoGem. “It uses AI-assisted autonomous machine learning techniques with multiple solvers and heuristics and, depending on an analysis of the case at hand, will apply many methods to find the one that produces the best results.”

Rigado and Kontakt.io Partner for Addressing IoT, AI Challenges

Intelligent analytics paired with innovative solutions will extend the IoT and AI networks of Rigado and Kontakt.io through their recently announced partnership.

“This partnership addresses the key challenges of commercial IoT by combining a robust, ready-to-deploy intelligence platform with secure and scalable edge infrastructure,” said Kevin Tate, Chief Revenue Officer at Rigado. “The Kontakt.io Simon AI is an impressive complement to our secure edge infrastructure, and it allows companies to immediately translate data from Rigado into the insights that apply to their business.”

By bringing together Rigado Cascade IoT Gateways’ edge connectivity, computing and security with Kontakt.io Simon AI’s abilities in location and sensor analytics software, the partnership aims to reduce complexities and costs associated with optimizing asset management, logistics and operations.

“The value of Simon AI relies on being able to receive rich, real-time data from the smart environment,” said Philipp von Gilsa, CEO at Kontakt.io. “The Rigado Cascade solution provides a secure, scalable and cost-effective way to receive that critical data, no matter the scale.”


Google Cloud added to Blume Global’s Advanced Technologies Toolbox

Blume Global and Google Cloud announced their technology partnership earlier this week, adding to Blume’s already extensive tech toolbox. The company confirmed the partnership will help to improve artificial intelligence (AI), algorithms and machine learning for customers.

The Google Cloud platform provides companies with increased visibility on shipments while enabling them to more accurately predict estimated time of arrivals through its real-time cloud-based performance features.

“Digital supply chain capabilities are evolving quickly and partnerships like this play a critical role in connecting those capabilities and enabling next level integration. A strong ecosystem of partners is crucial to the success of a modern supply chain,” said Simon Ellis, program vice president, global Supply Chain Strategies at IDC.

Blume currently employs data management, blockchain, AI/ML, cognitive interfaces and visualization as part of their strategy to support customers with supply chain solutions.

“We’re delighted that Blume Global will bring its leading digital supply chain capabilities to Google Cloud” said Kevin Ichhpurani, Corporate Vice President, Global Partner Ecosystem at Google Cloud.  “Retail customers want to modernize quickly, and our partnership with Blume will be an asset to them, letting them leverage Blume’s expertise in supply chain alongside the scalability, flexibility and leading AI and ML capabilities of Google Cloud.”

“By joining Google’s Cloud Technology partner program, we are able to focus more on developing our proprietary technology to create advantages in the supply chain,” said Pervinder Johar, CEO, Blume Global. “We chose Google Cloud because they are an open, neutral cloud platform that allows us to scale quickly and take advantage of their expertise in technologies like AI and ML.”