Custom
digital solutions

Technology is cross-cutting and can span multiple areas, markets and niches.

That’s why our services meet the needs of any business or organization, regardless of its sector.

At the same time, to specialize our offering we focus on the verticals presented here, ordered by the volume of information they may handle.
 

Retail

This sector has the particularity of generating data even when the activity is paused for rest.

The use of sensors and IoT devices that collect environmental data allows for a comprehensive view of the store, helping to record foot traffic, heat-mapping of visitor journeys within the shop, study the storefront engagement, track which products attract the most attention, and calculate conversion rates; furthermore, the implementation of immersive phygital experiences expands visitor interaction with the store while allowing data collection on their exploration. Simultaneously, data generated through online presence provides information on user interests, helping to anticipate demand in the physical store.

In warehouse management, sales data helps anticipate future demand, facilitating purchase planning to avoid overstocking or stockouts, and restocking shelves before products run out. 

In customer service, analyzing anonymous data helps understand visitor behavior in the store and assign the right staff to each shift. Business intelligence and predictive analytics allow for a deeper understanding of customers and the environment in which the store operates, studying the audience to adjust the offer according to the area profile, local sales trends and regional preferences.

Integrating data from both physical and digital stores enables a holistic business analysis, helping to improve customer experience and communication, identify new opportunities, understand market trends, optimize distribution and streamline internal processes.

Logistics

In the supply chain, data management defines the business's response to a chaotic environment.

Prescriptive analytics of real-time information provided by sensors and IoT devices helps identify issues and facilitates decision-making to anticipate or prevent problems, resolving bottlenecks in internal processes and resource allocation. Integrating external data, such as weather, traffic, or supplier performance data, provides a broader view of the current situation, adapting operations to current needs.

Predictive analytics models help anticipate demand peaks, facilitating production, inventory, and distribution planning.

Automating data flow between stages or departments and using automatic identification technologies, help to monitor the logistics process and enable more agile and informed management that reduces delays and errors, optimizes dynamics and improves the customer experience.

Manufacturing

The use of sensors and machines connected to the data infrastructure, helps to monitor the manufacturing process, facilitate the distribution of resources, synchronize logistics flows, and improve responsiveness.

The virtual replica of the production in its digital twin, fed with real data, allows for the simulation of scenarios to analyze, predict and optimize performance. This enables testing changes, anticipating failures and improving decision-making without impacting the real system, before implementing solutions in the physical environment. 

The integration of data from different sources and departments, helps provide a more complete view of the business and anticipate demand to improve organization and streamline operations.

Real Estate

In asset management, handling property data helps automate routine processes, streamline portfolio maintenance, reduce operating costs and enhance transparency. 

The use of sensors and IoT devices that collect real-time building data, provides information that helps optimize property management, improve efficiency and facilitate reporting and audits.

HoReCa

In inventory and sales management, historical sales data helps identify patterns and anticipate demand, facilitating purchase planning to avoid food waste, excess inventory, or stockouts. Furthermore, sales analytics helps reveal customer traffic trends, allowing the optimization of resource allocation. 

In cost control, analyzing supplier information helps identify savings opportunities, allowing to reduce expenses, eliminate money leaks, improve profitability and renegotiate purchase terms. 

In customer service, the study of anonymous data helps to understand the dynamics of reservations and behavior in the establishment, allowing for improvements to the customer experience, prediction of their needs and adaptation of the offer. 

Business intelligence and predictive analytics open up even more possibilities; for example, by integrating sales, booking and calendar data, you can forecast customer traffic based on season, weather or local events.

Data also helps to understand the reality of the business and detect internal anomalies or risks, alerting to unusual sales, strange performance, labor frictions, and material wear and tear. The use of sensors and IoT devices that collect environmental data allows for remote, real-time monitoring of the facility's status, which helps to streamline regulatory compliance, maintain quality standards, facilitate predictive maintenance and anticipate failures or breakdowns.