Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include: Speech recognition. Recently voted one of the 20 most innovative companies to watch in 2019, Algo is here to make sure you are ready for the AI revolution that is coming to a business near you. ARE YOU READY? In this episode, Amjad Hussain, CEO of Algo joins me to talk about how they got started and why they are working with companies to help them get ready for the AI revolution. He will walk us through a real-life example of how his clients are benefiting from working with Algo, what you should expect when introducing AI, how they set themselves apart from their competitors and finally Amjad gives us his half-crazy intuitive prediction for the next 5 years of the supply chain.

Questions I Ask: Why don’t you tell us about Algo? Where did you start? What do you do? [0:34] Why don’t you tell us a little bit about the companies or kinds of companies that you are working with now or that you want to work with. [4:44] Can you pinpoint maybe one customer you have worked with and how exactly have they used Algo and what did it do for their business? [10:26] How do you differentiate yourself? What’s different about Algo compared to other competitors in the market? [19:32] What is your half- crazy, intuitive prediction for the next five years in the supply chain? [25:17] What’s next for Algo? [30:31] In This Episode, You Will Learn: Algo, what they do and who their team is. [1:00] Algo is a vertical software solution. [4:58] Who Algo works with. [5:05] Creating value [8:30] Allocation accuracy. [12:20] What makes Algo stand out? [20:00] The future of supply chain. [26:02]

Today, data is becoming one of the most valuable assets for many enterprises. From Manufacturing to IT, every industry is trying to find ways to become more data-driven and optimize their operations. The supply chain arena is no different, with most practitioners thinking about how to use data and quantitative methods to improve decision making across all levels of the supply chain.

However, the sheer quantity of data is exceeding the analyzing capabilities of many organizations. As a result, many supply chain professionals are struggling to collect, clean, and manage the right data across their departments, sources, and siloed systems. It is no wonder that Supply Chain is one of the areas most behind in the adoption of AI according to several new studies.

This is where Algo.ai comes in with its industry-specific full-stack Enterprise AI platform that not only solves customers’ data problems but also creates immense operational and strategic value through successful Supply Chain AI implementations. The company provides a robust vendor-managed inventory and supply-chain analytics platform for retailers and their suppliers. AlgoTMhelps customers launch new products, optimally manage their inventory, and takes the guesswork out of in-store merchandising. Algo.ai also offers a unique, risk-free rapid implementation process that gets to ROI much faster than traditional approaches.

The journey to Algo.ai

Before founding Algo.ai

In 2016, Amjad Hussain and his partners built SilkRoute, a Vendor Managed Inventory SaaS provider. Amjad’s background included building data-driven supply chains and business intelligence tools for some of the world’s largest distributors of media products. This background, combined with some groundbreaking research done with Dr. Dimitris Bertsimas and Dr. Nathan Kallus at MIT, led Amjad to found SilkRoute in 2008.

Silkroute started its journey as a Vendor Managed Inventory SaaS platform and IT services provider, and over the years, the company expanded its solutions to include mobile application, business intelligence, IoT and other custom software applications. SilkRoute’s first customer — Tesco, the UK’s largest retailer, started them down a road of providing mission-critical and data-heavy applications for Fortune 500 enterprises.  Reflecting on his entrepreneurial journey, Hussain says, “It gave us some revenues, so we could invest any economic margins back into the company and develop many more products and solutions. That is how it started.”

The success of Silkroute’s SaaS products and the increasing demand for predictive and prescriptive analytics led Hussain to conceive and build a unique horizontal Enterprise AI platform for data analytics powered by a Natural Language interface. Today, Silkroute is being operated as part of the Algo.ai family and is seeing rapid growth due to its mixture of cutting-edge technology and long-lasting relationships with many fortune 500 companies. “To this day, we have retained 100% of our customer relationships and reinvested our revenues in growth and product development,” says Hussain.

Vertical Specific AI

To effectively leverage the power of Big Data and AI, a team must both have the rare combination of technical know-how and domain expertise.  The Silk route team includes domain experts in retail inventory management, retail analytics, in-store inventory planning, and warehouse inventory planning. Pairing domain experts for each functional area with a highly skilled team of data scientists, machine learning and software engineers has allowed the company to develop flexible, full-stack solutions that leverage the AlgoTMplatform, which uses a conversational interface to accomplish an array of data analytics and smart workflows comprised of both people and machines. Further, Hussain says, “Predictive and prescriptive analytics are used heavily along with other machine learning algorithms in making optimized decisions under uncertain conditions and tradeoffs for millions of products faster than humanly possible.”

SkyLight + AlgoTM

SkyLight is Silkroute’s longest running SaaS solutions. It is a robust vendor managed inventory tool, which optimizes all aspects of the retail demand chain with a mission to sense demand, stock smart, sell more, and see everything. SkyLight receives POS (Point of Sale) data from the world’s top retailers and merges it with internal and 3rd party data to effectively manage multiple product categories for the retailers as well as their suppliers, wholesalers, and distributors.

SkyLight’s key functionality includes new product introduction, demand sensing, and shaping, demand driven replenishment, assortment optimization, and reverse logistics. Now, powered with AI from the AlgoTM platform, SkyLight employs superior demand forecasting, perpetual inventory management, and assortment optimization algorithms. “SkyLight is a high performance rapidly deployable and easy to use solution with a global and growing customer footprint,” says Hussain.

Customer Relationships

“As a bootstrapped company we have had to rely on our customers to fund our growth; hence our customers are our #1 priority,” says Hussain.

Algo.ai’s most important focus is on customer success. The company believes that the most effective source of new business is through its customer’s referrals and references. Therefore, it develops solutions according to customer needs and ensures that customer relationships are built on trust and a mutually shared mission.

Hussain proudly remarks, “We work hard to deliver, and our customer relationships reflect that.” He adds, “Our very first check was just a couple of hundred thousand. Very soon, that relationship became over a million dollar a year relationship that is long-standing and still growing. To effectively support large enterprise customers, you have to be willing to grow and fill the gaps they have and support their missions like they are your own.”

This attitude and focus on customer success has proved to be pivotal in gaining significant market share in niche categories such as Home Entertainment and Music distribution. Additionally, Algo.ai was recently recognized in an Entrepreneur article highlighting the journey to achieving “negative churn,” often considered the holy grail for SaaS companies.

Looking Ahead

Amjad kept hearing from customers that they have unique problems that they want to solve with some novel AI and ML approaches, but they needed a partner that can produce more reliable outcomes than their in-house efforts. To this end, Algo.ai recently launched AlgoVision Lab, an internal R&D department that works to design, test, and deploy novel AI methods using their proven B2B integration framework.

Going forward, Algo.ai intends to expand its business across the globe. It has already extended its reach by launching a new office in London last year. They are also on the hunt for new talent and technologies: “We believe in a smart M&A strategy and are always interested in talking to small entrepreneurial teams with great talent, innovative concepts, and unique technologies that can benefit our enterprise customers” concludes Hussain.

Whether you are a retailer, manufacturer, dealer, wholesaler, or distributor, inventory management is a crucial part of your operations. Issues with inventory can make or break the business. Without proper inventory management, it is very difficult for companies to maintain control and handle the needs of customers. Proper management of the supply chain, inflow and outflow allow the business to thrive in today’s competitive environment.

While inventory management has always been a critical part of any business, it has become more valuable over the past decade as consumer expectations and shopping behaviors have changed rapidly in the age of Amazon and Omni-channel. As the stress on retailers to keep up increases, in turn, they increase the demand on their suppliers to perform. Therefore, it is very important for suppliers to maintain excellent inventory management to be able to meet customer demands for fast fulfillment while optimizing their warehouse space and assortment allocation. Today, many new inventory management solution providers have surfaced using more advanced data-driven methods to provide transparency, clarity, and efficiency to these complex operations.

With modular architectures and customizable tools, these new inventory solution providers offer flexible inventory management software to suit any business size or vertical. They also provide more user-friendly interfaces and end-to-end data connectivity to streamline operations and reduce costs. Moreover, predictive and prescriptive analytics using AI is making it easy to analyze the mountains of data generated in commerce to inform better strategies based on the real-time insight of what is happening in the business. The space is also seeing the emergence of drones and robots using AI technology to check and re-stock inventories.

The latest edition of The Technology Headlines highlights 10 Fastest Growing Inventory Management Solution Providers to Watch in 2019 who are offering innovative solutions to achieve efficiency and productivity in operations.

We are honored that Algo.ai was chosen to be on this list and appreciate the recognition!

Read the latest edition of The Technology Headlines Magazine to see the complete list.

With the quickening pace of business and consumer expectations for immediate gratification, it’s not enough to conduct inventory controls every month, week or even day. While they’re indispensable, they’re not going to help your company reduce costs and increase revenue, but real-time inventory management just might!

What is Real-Time Inventory Management?

Real-time inventory management is a way of keeping a constant up to date record of your inventory. It’s especially useful if you have an online store or e-commerce, and can also be referred to as perpetual inventory.

Why Is it So Important?

First, let’s take a look at what lack of stock does to your company’s sales:

The results may be disturbing, but the root cause is very simple: Lack of real-time inventory tracking and coordination.

If you could see all of your inventory’s movements in real time, and set up the right automation processes so that when a product’s purchase patterns change, new stock is ordered instantly, you wouldn’t be facing these losses.

For a long time, the industry has struggled with this problem. It was impossible to see what was happening until the reports came in for the day (or the week).

And this is where real-time inventory management comes in.

As a method of tracking, automating and analyzing inventory movement, real-time inventory can help with:

  • Smarter replenishment
  • Better vendor & customer communication
  • Organization
  • Understanding trends, patterns and cycles
  • Decision making

To put it simply: real-time inventory management helps you understand how your products are being sold and when they’re close to being out of stock.

The technology monitors all of your sales channels so don’t worry if you’re selling online and in brick & mortar stores. Omnichannel inventory management isn’t a problem.

And what’s even better: you can get insights from the field without manually going through thousands of reports.

Inventory forecasting is made easy as the tools for real-time inventory management keep track of everything.

They can even predict spikes in sales with access to your previous data, helping you reduce spoilage that adds additional $0.43 cost to every $1 you earn.

And since most of the real-time inventory management tools are stored in the cloud, they’re easily accessible organization-wide. You can cooperate with the sales and marketing departments to predict an increased demand for a certain product.

Finally, you can focus on optimizing your process to make sure that no shopper abandons their $100 cart just because they can’t get the $5 product they want.

When you have to manage inventory at a large scale in multiple markets it may seem like a daunting task. However, we’ve pulled together some of today’s best practices to bring you 10 tips for effective inventory management for a global business.

Camcode, a worldwide manufacturer of bar code labels, recently reached out to Amjad to be part of their panel of Inventory Management Experts and asked him to pitch in on advice for warehouses looking to save money. It may not come as a surprise that Amjad points to data analytics as a powerful factor in optimizing inventory to save money:

“Prescriptive Analytics is the most powerful tool in optimizing inventory…”

The explosion in the availability and accessibility of data is creating new opportunities for better decision making in applications of inventory control. Prescriptive analytics starts by predicting consumer demand and then using Machine Learning to recommend the optimal inventory levels to make the most profitable use of warehouse space. Demand is the key uncertainty affecting inventory decisions, which presents a huge opportunity to leverage transactional data combined with large-scale, publicly available data such as web search queries, reviews, and social media chatter to optimize inventory and improve warehouse profitability.

Head on over to the Camcode blog to see 26 other tips on Inventory Control Methods for Saving Warehouses Money:

You may also be interested in 4 Steps to Streamlining Inventory Management Operations

Fully understanding the data behind your inventory management practices is essential to running an efficient and modern supply chain operation. Across every touch point, data provides actionable intelligence that can help any supply chain provider reduce costs, streamline operations, and maximize potential. If you want to set up your supply chain for success, follow these four easy steps to start maximizing your network’s potential.

1. Develop an Implementation Strategy

Getting the most out of your supply chain operations begins with a carefully implemented optimization strategy. Like nodes in a network, each component of your supply chain and inventory management operations needs to be aware of and in communication with the other nodes to keep traffic flowing and to immediately address any concerns. 

2. Choose Key Metrics

Begin by choosing three to five key metrics that effectively capture the essence of your mission, such as producers in the supply chain, your warehouses, or the end consumption points like retail stores. From there, factor in metrics that have a direct impact on your business, like seasonality for warehouse operations or your inventory turnover. 

Ultimately, this data will help you identify demand: who in your network has a specific need, like on-time, in-full delivery? With proper demand planning and forecasting, your supply chain operations can turn data points and metrics into a comprehensive forecast of the future. Many modern software solutions include AI and machine-learning capabilities to improve decision making and weigh any necessary compromises and tradeoffs. 

3. Identify the Low-Hanging Fruit

From there, you can begin to identify the low-hanging fruit of your inventory management operations. Your data will inevitably point to particular products that are either rapidly flying off the shelves or that just haven’t resonated with customers and are taking up valuable warehouse real estate. Starting with these readily apparent items, you can follow the bread crumbs leading to a proper inventory management strategy. 

4. Use Data Visualizations to Take Action

Brought to life through data visualizations, you can quickly and clearly identify areas of waste, opportunity, and improvement in your supply chain. No matter the specific determining factor, properly understanding your data and its full context ensures time, money, and resources are not being squandered. By ignoring or underutilizing your data and the story it’s telling, you risk missing current and future opportunities that are waiting to be taken advantage of. 

With a comprehensive strategy to assess, analyze, and implement decisions drawn directly from your data, your supply chain operations will have improved inventory management capabilities that can ensure the long-term success of your organization. To be sure, your customers, clients, and supply chain partners will appreciate having access to actionable intelligence that ultimately improves speed, lowers costs, and reduces waste.

If you’re tasked with finding new ways of optimizing your supply chain operations, understanding what’s valuable and what’s worth discarding can help you run an efficient and streamlined operation. Here are some Marie Kondo-inspired inventory management tips to help get the most out of your supply chain:


Inventory management is no longer a matter of guesswork. Thanks to machine learning and prescriptive analytics techniques, better decision-making in operations management makes it easier to predict demand for inventory based on a variety of different factors. With help from all kinds of data, inventory management decisions can be made correctly and successfully to create a competitive edge.

For a retail store, that data can be used to predict and prescribe optimal stock levels — even for products that have no prior sales history. Whether it’s a seasonal product, a new release or an item a store has never carried in the first place, relevant historical information related the product’s details can be used to predict and prescribe its sales potential.

Using big data to assist inventory management can help cut down on costs, maximize sales and ensure a store has the correct amount of stock on hand. The advent of omnichannel retailing and e-commerce offerings like “ship-to-store” options makes accurate inventory management crucial to ensure goods are where they need to be at the right time and aren’t being put to waste.

In one case study, we looked at the distribution and manufacturing arm of a global media conglomerate responsible for shipping an average of 1 billion units of CD, DVD and Blu-ray entertainment titles. Their challenge was to lower operational costs due to declining sales, diminished shelf space and the availability of digital alternatives.

For this vendor, their key goal was to maximize network-wide sell-through of their inventory. Because of the uncertainty of new releases that drive many sales as well as the lack of physical space on an endcap display, determining which titles had the best sales potential was essential.

Harvesting data from sales records, search queries from Google Trends and public sources such as Rotten Tomatoes and IMDb, we built inventory prescriptions taking into account a 150-week period. Building upon each previous week’s data, we scored our prediction performance in order to inform the next week’s prescription. With this data, we were able to make future sales predictions using both data-poor decisions and perfect-foresight decisions.

Being able to accurately manage, predict and organize retail inventory with the help of machine learning leads to retail operations that are far more streamlined and efficient. No matter the product or industry, prescriptive analytics using big data can greatly improve inventory management across the entire supply chain. 

To get an in-depth understanding of the data and methods we used you can download our scientific paper Inventory Management in the Era of Big Data.