What We Offer


Endless Possibilities

Artificial Intelligence and Advanced Analytics

Challenges we solve

Artificial Intelligence, Machine Learning, and Data are increasingly critical for an effective digital transformation strategy, but there can be a steep learning curve when it comes to their adoption. Siloed data is a challenge because it is difficult to integrate, analyze and ultimately use for powering business use cases. Legacy systems and data silos induce other challenges such as data quality issues, and hampers data understanding and visibility across the organization. Open Market Network modern platform ingest and integrate with commerce and finance systems and ultimately create a single source of truth for the data in a tiered Data Lake, unlocking data potential as an competative edge.

The Economics of Data

Data has unique properties that suggest it should be accessed in the digital economy rather than owned. As economic activity moves online, it produces an increasingly long trail of data. Firms in all sectors of the economy are starting to realise the value of this data. The largest technology firms are already demonstrating the value of gathering and analysing data at scale to understand macro trends and predict demand. Innovative businesses are using novel sources and big data to understand customers better and deliver more tailored and more keenly-priced products and services.

In an economic model, data would be considered a factor of production. Analysis of that data forms part of the production function, in which businesses combine their land, capital, labour and data resources to produce the goods and services that consumers demand. Data helps firms understand their customers and their own production process. And just as technology innovations can generate gains in productivity, advances in data analytics can improve the quality and efficiency of their production process. Data therefore has private value to a business.

Building a modern data infrastructure

Artificial Intelligence Enabled Digital Commerce

When the consumer buys a product do not imagine the complexity behind this operation. Simplicity in purchase, order tracking and delivery is the result of powerful information systems interconnected in real time. From consumer purchase suggestion systems, anti-fraud systems to accept an order, systems that ensure the most requested products are in stock, and distribution systems with order tracking and evaluation systems to assist in making decisions for future buyers. All this to offer a shopping experience that between a product in hours, the next day or annoying deliveries with more than one day, which are only acceptable by cost/benefit ratio. Without artificial intelligence systems it is impossible to manage this entire ecosystem efficiently.

In the current electronic market, the concepts retail and wholesale are confused, because the large virtual stores operate as retailers and wholesale at the same time. The consumer can make the purchase of a product in a small online store, but all storage infrastructure, payment and distribution system are doing by ecommerce stores, allowing the small online store to have a competitive price.

If the criteria that consumers adopt for their purchases are price, delivery time and after-sales service, at the limit, we will have few virtual attacks with thousands of associated retailers, allowing to sell at wholesale prices. That is, solitary flights will survive only for niche and unique products.

Behind this revolution is artificial intelligence, gathering mountains of data in its big data, coming from IoT devices, sales websites, consumer banking information for anti-fraud decisions, warehouse inventories, route information for optimization, dispatches, receipts, customer reviews, consumer protection agency complaints, purchasing suggestion systems and so many other information and decisions that are incapable of being made by a human or organizations. Remembering that the greater the number of people involved in decision-making, the more likely it is to make mistakes and slow processes.

This means, that at the limit, every retailer must have a wholesaler infrastructure, own or outsourced. When we think of wholesale, one of the biggest costs is the maintenance of inventory, that is, how much it costs to maintain the stock of a particular product. This cost consists of taxes, employees, air conditioning costs, space opportunity costs, depreciation, insurance and business administrative costs.

AI comes in as a vital tool to keep costs as low as possible, monitoring how long inventory ends up to the time it takes a vendor to ship inventory replacement. Imagine monitoring millions of items in an un automation-free inventory and machine learning algorithms to seamlessly synchronize supply with the demand you need at the best possible costs.

Now imagine an exceptionally large warehouse controlled by AI algorithms determining where there is space, which product group should be where and how to take these products to a separation station, all automatically. Like amazon warehouses where all transportation is carried out by robots with AI algorithms to recognize more efficient patterns to move around. In smaller warehouses, the benefits of AI are associated with capacity planning and space allocation. AI systems understand the size of the space, the dimensions of each product, and will optimize the space for product storage.

When a company operates multiple distribution centers (CDs) it is important to place the right products close to demand. This avoids longer journeys, consistent delays, poorly allocated resources, and higher fleet costs for deliveries. AI can control traffic time, product availability, demand fluctuations, and route optimization, and reduce operational tasks and fleet control and notifications to carriers automatically.

For what makes cargo transport knows that one of the challenges of delivery is the last mile, which consumes between 25-28% of the total delivery costs. Many cities have vehicle type restrictions at certain times, and the right type of vehicle allocation can optimize fuel reduction deliveries, time savings, reduced distances traveled, among other factors. An efficient routing system operator by an AI system can define optimized routes automatically.

The Picking, product selection in the warehouse, can be optimized by AI systems guiding robots or tracing an employee’s optimized routes. An AI system learns which trips are most frequent and optimizes both the product warehouse location and the fastest routes to separate orders. The Packing can be optimized with AI systems learning, dynamically, the best classification of packages associated with the configuration of conveyor belts.

As we have seen one of the criteria of consumer purchase is the price. In this way, retailers and wholesalers must constantly monitor the prices of products, their similar and substitutes in the market. AI systems and price research robots analyze competitors’ prices, assess profit margins, and suggest new prices to increase sales, with approval from a supervisor or automatically.

For a long time, Electronic Data Exchange (EDI) systems support product replacement systems in warehouses with automatic orders based on certain pre-established criteria, such as minimum inventory. AI systems can optimize replacement systems by changing warehouse supply criteria based on demand fluctuation forecasts.

The complete robotization of the warehouses will make the operation cheaper and more efficient, can work 24 hours a day, 7 days a week without reducing productivity, increasing the reliability of deliveries and customer satisfaction.

The big challenge for companies is to build an artificial intelligence system that orchestrates all the functions of retail, wholesale, and distribution as a unique ecosystem – a Big Brother. This is possible with the new technologies of IoT, Big Data, Cloud Computing, Edge Computing, Robots, Robotic Process Automation (RPA), Digital Twins, Blockchain, drones, autonomous vehicles, 5G and recognition of images controlled by artificial intelligence.

Digital Innovation

In a fast-paced digital world, the expectations of customers are shifting. A big part of what we do is exploring the innovative digital technologies that are shaping our future. We examine the ideas of tomorrow that are going to impact our world these future-market insights decide how business can take advantage of the latest trends. And because we always place value over technology, it means any innovations we implement solve business and societal challenges.