Mobile App Development

How AI-Powered Predictive Analytics Can Help Modern Supply Chains Become More Efficient?


A slew of elements influences the success of logistics operations. It fails to meet distribution and consumer demands unless it maintains accuracy, timeliness, and resiliency. However, Artificial Intelligence in logistics entails more than just loading items and delivering them to customers. It has more to do with humanity’s best interests.

According to reports, the logistics business was increased to $1.2 trillion in 2021 and is predicted to grow even more in 2022, implying that it would require a strong infrastructure to function efficiently globally and meet client expectations more quickly. However, the conditions were different thirty years ago than they are now. It faced increasing hurdles, which large logistical organizations were able to handle while others continued to suffer.

The Logistics and Supply Chain Challenges

The business faces a significant difficulty in optimizing its supply chain and logistics. To accommodate the expanding demands, it will take a massive effort involving additional warehouses, ports, ships, and a large fleet of delivery trucks. And it necessitates a rapid increase in supply. Therein lies the most serious logistical and supply issue. It only adds to the complication, since many products sit idle in warehouses or ports for days or even months, causing problems for recipients. It damages the reputation of logistics and companies, and it is costly to hold idle stockpiles.

However, AI-powered predictive analytics can be used to overcome this deep-seated inefficiency. Predictive analytics is a clever technique to improve efficiency and precision in tracking freight and parcels utilizing existing data.

There are a variety of approaches to apply Artificial Intelligence in supply chain management to improve the environment. What’s more, this phenomenon offers a clever way to save waste while raising efficiency.

But What Is Predictive Analytics?

Predictive Analytics is an Artificial Intelligence-based technique that gathers data from a variety of sources, particularly past data that the organization already owns. These data sets or algorithms are parsed by the practice in order to assign scores to different user groups. Rather than making absolute predictions about anything, these numbers indicate some probability. Simply said, it uses a vast amount of data to apply probability theory and derive data-driven results that suggest what is likely to happen in the future based on the historical data. Artificial Intelligence applications in logistics now utilize Predictive Analytics to track historical data and make forecasts about certain trends, patterns, and metrics.

Today’s businesses can use predictive analytics for a variety of purposes, including inventory management, planning, and demand forecasting. Predictive analytics can assist in the creation of patterns that allow for a quick and agile response to future developments.

AI for the supply chain

The present focus on digitization is reshaping supply chain management, just as it is in any other industry. For many businesses, increasing the efficiency of the supply chain is critical. Even minor changes can have a significant impact on the bottom-line profit when operating within tight profit margins.

Demand forecasting and warehouse optimization are two areas where data analytics and machine learning may help supply chain management. The ability to utilize the huge volumes of data produced by industrial logistics, transportation, and storage to enhance operational performance can be a gamechanger for those who do it effectively.

Better Supply Chain Management with Predictive Analytics and AI?

Predictive analytics tools and artificial intelligence (AI) are critical in the aftermath of a pandemic for boosting forecast accuracy. This necessitates having current data on all resources. Natural disasters or unanticipated shipment delays, for example, could cause a shortage of particular raw ingredients in the plastic supply. AI systems may be able to predict anticipated events ahead of time, allowing for better decision-making.

AI is anticipated to expand to a $309 billion market by 2026, with 44% of CEOs reporting lower operating costs as a result of AI implementation. In order to increase predictive analytics in your supply chain, you can use AI.

  • Inventory Management:

    Inventory overstock and understock cost businesses millions of dollars each year, and real-time inventory visibility was critical in avoiding these issues. When you link real-time data with AI, you can optimize your inventory management beyond simple reordering. Monitoring technology, such as internet-of-things (IoT) devices, can send out real-time notifications regarding low inventory levels, allowing you to replace items before they run out. You can collect data over time and find patterns with AI-based solutions, which can help you plan inventories more efficiently.

  • Delivery Optimization:

    In recent years, using predictive analytics to assure on-time deliveries has grown more frequent. But what if there’s a car accident, a traffic bottleneck, or bad weather? These, as well as other unanticipated factors, could cause delays in product delivery or shipment. This is where AI and analytics come into play. By analyzing these experiences, it will provide future insights on coping with and preparing for these scenarios. Real-time rerouting based on previous factors is possible with route optimization software and AI. 

Final Words

Predictive analytics is clearly the key to unlocking new doors of cost savings and efficiency in logistics and the supply chain. Furthermore, these solutions are shifting the sector from human-driven to data-driven decision-making, which is a major contributor in the industry’s overall digitization.

Over three-quarters of chief supply chain officers confess that their digital transformation projects are still not coordinated, according to Gartner’s 2017 CSCO survey. So, what can companies do to get started with predictive analytics implementation? In some circumstances, hiring or appointing a Chief Digital Officer to lead your company’s digital transformation and develop an information-driven supply chain could be the initial step. 

About Digital Crafters

Digital Crafters is a leading AI Software development company that helps organizations harness the power of AI by developing cutting-edge mobile and online apps. With their knowledge in Natural Language Processing, Deep Learning, Machine Learning, and Computer Vision, the Artificial Intelligence developers with us turn your idea into reality. We collaborate with both large and small businesses to integrate AI technology into their products. We create AI software that simplifies things and helps enterprises stand on their own.

Mobile App Development

Investment App: Key Features and Development Essentials


Investing and trading used to be so complicated that trading stocks and generating passive income required a specialist degree. Investing, on the other hand, has become so simple thanks to technological improvements that even a teenager can do it.

With the rise of cryptocurrency, investing became even more popular, to the point that some of the most popular stock trading apps now also support cryptocurrency trading. Investors pick open-end funds for long-term portfolios because they diversify risk by investing in a variety of equities, gold, cryptocurrencies, and bonds. Because of mobile applications, ordinary people now have a profusion of financial alternatives.

What is an Investment App?

In general, an investing app is software that helps manage numerous investment-related operations. The investment app can be used to manage publicly traded financial information, receive professional recommendations, and manage assets. Apps for investing come in a range of shapes and sizes, depending on the type of financial problem they solve. Budget trackers, stock trading systems, and social networking apps for finance-focused communities abound on the market.

Furthermore, mobile investment apps can range from fantasy stock games (such as Invstr and Wealthbase) to actual robo-advisors (like Wealthfront and Betterment). In essence, an investment app can act as your personal financial advisor, coach, and helper through the internet. Of course, this does not imply that investing is any less risky, but the software is an excellent tool for making this activity easier to begin and manage.

The Key Characteristics of High-Quality Investing Apps

Investing applications typically include a variety of features, based on the specific focus product creators have chosen. Nonetheless, there are a few characteristics that every successful investment app should possess. We’ll reveal them right here.

  1. Personal Account:

    To access a personal profile with a virtual private office, an investment app requires a login method. As a result, it’s critical to take your time with this stage. Make a personal account as simple and intuitive as possible to avoid turning off your customers from the start of their interaction with your software.

  2. Digital Wallet:

    In a nutshell, here is where the balance for future investments is kept. The key rule is great security, as well as quick access for anyone who is authorized to administer the assets held there. An investment app should be able to connect to the bank and card networks for real-time updates, as well as securely store data on the phone.

  3. Money Management Instruments:

    People dislike having money solely for the sake of having it. They want to put their money into something productive. As a result, your mobile app should provide a variety of capabilities to meet these requirements. You can integrate gamification components, dynamically changing charts, credit management dashboards, tables comparing many investment options, and so on, depending on the exact appearance and your app development goals.

  4. Chatbot:

    Users can interact with any app with ease when they have instant access to help. This function can be used by beginners to seek professional help. More experienced users can also profit from and solve the issues that arise when using an app while on the go. The existence of a chatbot improves the trustworthiness of your trading app in general.

  5. Security Elements:

    Any investing app should include data protection as a standard feature. Consider implementing a robust IDPS to handle DDoS attacks, encryption methods, two-factor authentication, anti-spam, and phishing protection. The more security tools you add, the better the user experience will be.

  6. Notifications:

    Real-time alerts are a must-have tool when it comes to investing. They enable users to monitor performance and make required modifications in real time. Customers’ happiness with trading apps is frequently harmed by the lack of timely notifications.

Guidelines for Developing an Excellent Investment App

Developing an investing app necessitates a cautious approach and consideration of several aspects. As a general rule, finding a dependable vendor and establishing excellent communication and regular interaction with the development team are critical. Prepare to learn the ins and outs of building an investment app so you and your IT partner are on the same page.

These seven pointers can help you get started.

1. Adhere to the Development Basic Implementation Plan:

Making an investment app, like any other sort of software development, involves careful planning and execution. Ascertain that your IT partner is aware of and capable of developing a mobile app in this manner.

The following is the basic development roadmap for building investing apps:

  •           Planning
  •           Picking a business model
  •           Building the core app
  •           Adding custom features
  •           Testing

Naturally, not every investment app development follows this approach to the point — especially when it comes to personalized investing apps. Nonetheless, this plan can serve as a long-term foundation for achieving appropriate development outcomes. Using the Agile methodology, you can keep the development process moving forward while quickly resolving any issues that arise.

2. Put in a lot of effort to create a good algorithm:

The capability of robo-advisors or an algorithm that assists in managing your investments is used by the majority of successful investment applications. The benefit of this feature is self-evident: it’s pure magic for consumers to acquire easy-to-follow and effective investing strategy advice. Once in place, this mechanism encourages users to use your app more frequently.

3. To enter an app, request a minimum amount:

Due to the low cost of installation and testing, all of the top-performing trading apps are simple to get started with. Some believe $50 is all you need to get started investing, while platforms like SoFi Invest simply ask for $1. Regardless of your readiness to offer the lowest feasible price in order to attract as many customers as possible, choosing the proper amount to maximize your budget is critical.

4. Don’t make users’ registrations too difficult:

Using investment applications follows a standard method. As a result, while creating your own software, ensure that the installation plan follows these steps:

  • Please sign up (include an opportunity to use social media accounts for that).
  • Connect with your bank account (also, make it easy for users to fund it in your app).
  • Choose an asset to invest in.
  • Track the performance of your stocks (the notifications features is highly useful here)
  • Invest in assets.

5. Ensure the highest level of security possible:

Many users are concerned about the safety of utilizing an investment app. Money is a sensitive subject, and your users are exceedingly cautious when sharing their personal financial information. As a result, when dealing with an app, you should pay special attention to data privacy and the overall security of the user experience. Ensure that your efforts are noticed and recognized by your users.

6. Accurately use APIs (Application Programming Interfaces):

Third-party APIs will definitely be required while designing investment apps. They can occur in a variety of ways:

  • Adding a bank account
  • Obtaining financial details
  • Updating the market data feed
  • The stock exchanges
  • Conversion of currencies

It’s critical to employ only trusted solutions in this case, such as Plaid, Paybook, and Xignite.

7. Hire a Vendor for Outsourcing:

Hire the team on an outsourcing basis to get the most out of your collaboration with the software development firm on developing investment apps. This technique has several significant advantages for creating SaaS products:

  • Cost-cutting
  • Setup time is minimal.
  • Upgrades are ongoing.
  • Scalability and ease of access

Contact Digital Crafters for Building an Investment App

We at Digital Crafters are glad to assist you if you’re looking for a skilled and successful software development partner. We have a long list of successful projects executed for businesses of all sizes and in a variety of industries. By recommending your investment app to us, you can be assured that we’ll give it our full attention and enhance its functionality with a diverse set of high-performing features and aspects.