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Singapore based Fintech Lending Solution Provider CrediLinq.Ai Secures SGD 1.35M via New Funding Round



Singapore-headquartered financial services tech firm, CrediLinq.Ai, reveals that it has acquired SGD 1.35 million through a new funding round.

The Fintech lender says that it plans to transform how credit is underwritten to SMEs using advanced tech solutions that will be integrated within its lending platform. CreditLinq.Ai’s platform is powered by its AI and machine learning algorithms. Investors in the firm’s round included Brandon Tee of B7 Capital, Sandeep Uberoi of Jungle Ventures, and software company Aerion Technologies.

The proceeds from the raise will allow CrediLinq.Ai to further expand its professional team, make updates to its technology and products, while accelerating the execution of its go-to-market strategy by financing its first set of loans. After introducing its services in Singapore, the company plans to expand operations regionally, focusing on the Hong Kong, Australia, and New Zealand markets.

Established last year by Deep Singh, an experienced banker and entrepreneur specializing in corporate and commercial finance, CrediLinq.Ai will create a more inclusive, accessible, all-digital, and seamless customer journey. Every business will be able to get quicker access to growth capital.

Singh’s extensive experience in credit and the finance sector led him to realize that small businesses continue to face challenges when accessing credit, especially as we emerge from the Coronavirus crisis.

Banks and credit asset management firms face challenges when trying to scale operations because of the conventional underwriting approach and a lack of proper automation within their sectors. After understanding these problems, Singh helped with creating the technology required to streamline credit underwriting – which should help an industry struggling to meet requirements.

GrabFinance and Bloomberg Media’s report, SMEs in a new decade, new economy – Feb 2020 Report, which surveyed over 600 MSMEs in Southeast Asian, found that 90% of respondents funded their businesses from their savings, with merely 39% having taken out a bank loan, and 15% acquiring funding from investors or VCs.

CrediLinq.Ai says it plans to lower the entry barriers for all businesses, particularly the smaller ones, which are currently underserved by banks. The company will help these firms acquire capital, which should help with empowering them to reach their growth plans.

As a Fintech firm, CrediLinq.Ai believes that all businesses should have seamless access to capital to allow them to reach their growth objectives. For investors, the company’s AI and machine learning tools/algorithms support a credit assessment approach that leverages numerous traditional and alternative data points to enhance credit underwriting.

This data-centric approach then offers a much better understanding of the borrower’s financial situation and improves the transparency and reporting to investors.

Deep Singh, Founder of CrediLinq.Ai, stated:

“As a passionate believer in the possibilities of technology disrupting the banking and credit sector, our platform aims to pave the way for all businesses to have better access to growth capital. Over the years I have been privy to what technology can do for this sector, and we hope to be able to add value by changing how credit is underwritten. We are also humbled to be able to leverage on the vast experience of our team and advisors, helping us support the growth of SMEs and help investors achieve their goals.”

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Artificial Intelligence

Eli Lilly joins $30M Series A financing for startup bringing AI analysis to endoscopy



Jonathan Ng, Iterative Scopes

The artificial intelligence-based technology of Iterative Scopes brings computer vision analysis to endoscopic images. The startup’s technology was initially developed to assist gastroenterologists in finding pre-cancerous polyps but CEO and founder Jonathan Ng said it’s also finding additional use helping pharmaceutical companies identify patients for clinical trials.

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Why Machine Vision Matters to Your Business



One of the most important kinds of artificial intelligence may be machine vision, also known as computer vision — image processing technology that allows machines to “see” the world like people can.

This tech is already having a major impact on the industry — especially the retail, warehousing, and manufacturing sectors. Any business owner should know about how machine vision may help reshape the economy over the next few years.

What Is Machine Vision and How Does it Work?

At its simplest, machine vision is the use of visual information and artificial intelligence to create algorithms that can process images — breaking them down into identifiable objects, scanning for patterns and looking for important information.

Machine vision technology has existed for decades, but it was rarely used due to the limitations of image processing technology and the high cost of sensors.

Recently, artificial intelligence has made machine vision much more practical.

With an AI-based approach like machine learning, if you have enough visual information — like photographs and recorded video — you can train an algorithm that’s capable of breaking down what a camera sees and picking out distinct, identifiable objects that a machine or robot can use.

For example, a machine vision algorithm trained on information from grocery stores may be able to identify the different products visible in a picture or video feed, as well as objects like shelves, barcodes, displays, customers and floorspace.

One of the better-known applications of machine vision is in self-driving cars. These cars are outfitted with a number of sensors that scan the environment around them — including cameras. Footage from these cameras are processed by a machine-learning algorithm.

This algorithm breaks down the visual data from the cameras into information that the self-driving system can use — like where the road is, the location of other drivers and obstacles the car will have to navigate around.

Fully self-driving cars haven’t hit the market yet — but smart driver assistance systems that use similar tech are starting to become common offerings in high-end vehicles.

The biggest beneficiaries of machine vision, however, are probably companies that can use the tech to streamline business processes.

How AI-Powered Image Processing Is Transforming Business

Across the economy, machine vision is being used in a few different ways.

In retail, machine vision often helps support “smart stores” that use networked sensors and AI to streamline customers’ shopping experience.

These smart stores include the cashierless stores being pioneered by Amazon right now. In these stores, cameras, combined with other sensors like shelf weight sensors and motion detectors, track customers as they move around the store and fill their cart.

Similar tech could also be used to make existing, non-smart stores more intelligent. For example, several companies are experimenting with the use of machine vision to create smart cashierless checkouts in stores that don’t adopt the grab-and-go model.

These could provide a more streamlined alternative to existing self-checkout systems without requiring the same investment that smart stores require.

In manufacturing, machine vision is often used for quality assurance purposes.

For example, you may see a manufacturer use machine vision on a conveyor belt robot that sorts out ideal products from those with obvious defects.

Another algorithm may be used just for color inspection of finished products. Manufacturers sometimes use color inspection for quality assurance processes, using color as a guide to look for chips in paints, defects or errors in components like color-coded wires.

With machine vision, the use of specific lights can help make this process even more effective. By using colored light, rather than pure white light, you can highlight certain colors and help the algorithm to track them.

Manufacturers also use machine vision to support new, self-piloting robots. In factories with warehouses, for example, some manufacturers are using autonomous mobile robots (AMRs) to partially automate picking and packing.

These robots use machine vision like self-driving cars to navigate the factory floor with little or no supervision. They can also use machine vision to read barcodes and identify individual objects, like pallets, allowing them to pick out items to transport around the factory.

How Your Business Can Benefit From Machine Vision

As machine vision becomes more popular, businesses across the economy will be able to benefit from new devices and platforms that use the tech.

A few cutting-edge applications of the tech are already widely available. These may help a number of businesses to automate processes that they couldn’t automate before, or to speed up tedious and difficult labor.

For example, there is a growing number of handwriting analysis and digitization tools on the market that use AI-powered optical character recognition (or OCR). These tools convert scans or photos of handwriting into digital text — reducing the need for transcription and making notes more accessible.

Retailers can benefit from machine vision-powered robots like those used by Walmart for inventory management. These robots move up and down aisles, using cameras to scan for products that need restocking.

Small businesses could also benefit from working with large manufacturers that have adopted the technology. Machine vision can help to reduce costs and improve product quality — for SMBs, this partnership could lower manufacturing expenses and the risk of defective products.

In some cases, it may also be possible to bring this technology in-house to improve quality assurance processes.

The Growing Importance of Machine Vision

AI is likely to become even more important to the business world over the next few years. Tech powered by artificial intelligence, like machine vision, will probably become more sophisticated at the same time.

Right now, businesses can use machine vision in a few different ways — like improving quality control or automating processes like inventory checks. Small businesses without the resources for complex AI-based solutions can also benefit from machine vision through tools like handwriting OCR apps.

Eleanor Hecks is editor-in-chief at Designerly Magazine. She was the creative director at a digital marketing agency before becoming a full-time freelance designer. Eleanor lives in Philly with her husband and pup, Bear.

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How to Build a Powerful Shopify Chatbot



You can increase sales on your Shopify eCommerce platforms with chatbots. How you may ask? Well, the best way to achieve conversions is to ensure your customers are happy. You can make this possible by making the buying process seamless and pain-free. 

Ensuring prompt responses to queries is critical. 24/7 access to customer service reduces waiting time. You can lose a potential customer if you do not catch them at the right moment within the purchase cycle.

Another effective method is to help guide decision-making with product recommendations. Personalizing services based on past shopping behavior makes customers feel you value them. Chatbots integration with Shopify allows you to achieve all these, and more.

Our article looks at how you can build a powerful Shopify chatbot. We will walk you through critical steps to follow.

  1. Chatbots vs. Live Chats: Which is the Better Option

Live chats can take care of customer service on your Shopify platform. Live agents take digital calls anytime a customer needs help. Many companies will outsource such work to call centers. The advantage is the human-to-human interaction that is not achievable with machines. 

The agent can also start the push to sales, depending on the nature of the conversation. The downside is many businesses cannot afford to have a team on standby 24/7. In case of a lot of calls, the waiting time for customers will belong. 

Human agents may also mismanage the customers. We have all experienced a rude, disinterested, or ignorant agent. You could lose a lot of business this way.

Chatbots can be available day and night. Investing in AI chatbots gives you access to machines with human-like abilities. Handling customer issues is quick, meaning they can manage large volumes of work. 

AI chatbots can also adjust responses, depending on the situation. Chatbots are also excellent for leads generation. Data-driven insights will allow the business to know which leads to pursue or discard.

The initial investment in such technologies may indeed be a little high. But, computing the costs long term will make you see the savings. 

Write a checklist of what it means to have live agents day and night. Your list should include salaries, insurance, overheads, and office equipment.

  1. Decide on the Job Description of the Chatbots

When investing in chatbots, have clarity on exactly what you want them to do for the business. A basic chatbot can take care of simple customer support tasks.

The other option is sales bots which provide more functionalities. Such include:-

  • Leads generation and qualification
  • Personalized product or service recommendations
  • Scheduling meetings and sales calls
  • Inputting data into the CRM, and so much more.

A third option is to build chatbots that incorporate both functionalities. Budget allowing, these may be the preferable option. You get to take care of customer service and sales on one robust platform.

  1. Integrating the Chatbots With Your Shopify Store

There are three methods to integrate chatbots with a Shopify store.

  • Use a Shopify app. you have tons of options available on the Shopify store. Such include Ochatbots, Relish, Acobot, and Octane. Please take time to read up on whatever you choose. Look at things like the cost implications and configuration requirements. Your due diligence should also include reading customer reviews.
  • Integration through third-party systems. One of the most popular options is the Facebook Messenger chatbots system.
  • Develop a custom chatbots system. This option gives you a lot more leeway. You can include features that respond to your unique business needs.
  1. Develop the Chatbots Conversations

Once you decide on the system, the true work begins.

Start by analyzing the type of questions your customers tend to ask a lot. Think about it like developing an FAQ script. 

Developing categories and maps of common issues is important. It makes it easier for the system to provide a response based on the customer query.

Next, determine what areas you want the chatbots to cover. Such include sales support, campaigns, and promotions like coupon trials and discount codes.

Next focus on the flow of conversation. The flow should start something like this;  greetings > you are speaking to > how can I help.

Do note, creating a chatbot conversation can be very challenging. You must understand your customers and have developed relevant personas. It helps to have clear expectations and easy-to-follow instructions. Also, provide directional cues, fallback answers and so much more.

Once you have all the scripts and a good flow, comes the copywriting part. Place yourself in the customer’s shoes. How would you like the interaction to sound like? One solid tip is to humanize the conversation.

  1. Setting Up and Configuring the Chatbot

Setting up and configuring the chatbots may need some expert-level advice. It is especially important if you have customized the chatbots with advanced features. 

You want to ensure that you have the right scripts and codes in place. If not, the customer experience can end up being very unpleasant. Imagine trying to get information about a product but the chatbot does not have the right information. 

What if the chatbots are not able to redirect urgent issues to live agents due to poor coding? You can find some pretty amusing or cringy examples of such situations online.

Always have it at the back of your mind that the chatbot is in direct communication with your customers. The experience can start a great relationship. On the other side of the coin, it could end it before you achieve conversions.

Final Thoughts

Chatbots provide a lot of functionalities on your Shopify platform. You get to improve customer experience. They provide prompt inquiries and are excellent for personalization and product recommendation. 

The sales team can also use the bots to generate and qualify leads. They can then spend time pursuing hot leads or nurturing warm ones. Such have a higher chance of converting into actual sales.

Our article has looked at steps to take to build a powerful Shopify chatbot. Articles like this are an excellent starting point. But, it is important to take the time to do a lot more research. There is so much exciting stuff to uncover about chatbots.

Also, consider it an investment to hire an expert to help with the process. The one thing you can take to the bank is this. Chatbots are an excellent investment for your Shopify eCommerce platform. So, get building!

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Genesis Digital Assets Raises $125M to Expand Industrial-Scale Bitcoin Mining



Although he made his fortune trading penny stocks and manipulating the markets, Jordan Belfort, the trader who inspired the iconic movie “The Wolf of Wall Street,” is currently not very happy with a lot of what’s going on with the crypto industry.

In a recent interview he explained in detail what excites him and what bothers him about the crypto space.

The Good: Bitcoin and DeFi

Belfort confesses to being an optimistic Bitcoiner. He explained that since discovering Bitcoin, he has found it to be an exciting idea.

He hopes that soon there will be more and better regulations for Bitcoin and the crypto industry. From his point of view, the more regulations there are, the better the consequences for cryptocurrency users and traders in the future.

“The sooner that massive regulation comes into the market, the better it is for Bitcoin, stablecoin and everything else. I think people are scared of regulations, they shouldn’t be. If you look back in history … let’s say the junk bond market, everybody said, ‘Oh no, the regulators are coming in! [But ultimately] the market got much bigger, so I think it’s a good thing,”

Belford commented that Bitcoin has a “bright future” and that the industry has evolved favorably over time, now being much more mature. He believes BTC could become a serious substitue for gold, and he expects the crypto to end the year somewhere between $45,000 and $70,000.


Belfort is also very enthusiastic about DeFi, an industry he believes to be very innovative. He even advises a DeFi company today.

The Bad: Shitcoin ≠ Crypto

Belfort was concerned about the growing number of worthless cryptocurrencies being created to attract many unwary people who end up losing their money.

From his point of view, these scams are a harm to the crypto industry in general

There are so many scams, it is really sad … You have all these shitcoins out there. Literally, every single day, there are new ones being printed. They are simply designed to separate people from their money.

However, he assured that all crime leaves a trail and eventually the organizers of these scams will pay, even though they are currently walking free due to the legal loopholes.

He called for cleaning up the crypto markets, although he declined to specify which cryptocurrencies he considered to be scams.

The Ugly: Tether

For Belfort, the top stablecoin in the ecosystem at the moment is a stain on the crypto industry’s credibility. When asked if he considered Tether a scam, the seasoned trader stressed that he had several years warning about his suspicions regarding USDT.

I have been saying that since 2017 that I thought there was a big problem with Tether … It seemed like a pretty convenient thing that Tether supply expanded when it needed to expand. And then when they settled something civilly, I was like Wow, How did they get away with that?

He declined to call Tether a scam or a shitcoin. Still, He said that while Tether may currently operate cleanly, past mistakes could cost it dearly, even to the point of not being able to recover.

However, although this scenario could bring negative consequences for the crypto ecosystem, from his point of view, it would simply be a matter of time until the markets balance migrating to another stablecoin of proven legitimacy.


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