Intelligencetomorrow

Recent messages

Dialogues and comments on predictive intelligence and data analysis.

Luciana Méndez 2 hours ago

Very interesting approach with LSTM. Do you recommend any specific framework to start implementing in Python?

In response to: Demand Forecasting with Neural Networks
Martín Roldán yesterday at 4:30 PM

In our company we use decision trees to segment industrial clients. The article on data mining gave us ideas to incorporate clustering.

In response to: Data Mining for Decision Making
Carolina Vega 3 days ago

Integrating predictive models into a legacy ERP was a huge challenge. The hybrid architecture you mentioned served as a reference for our project.

In response to: Integration of Predictive AI in ERP Platforms
Gonzalo Torres 5 days ago

Do you plan to publish a practical case study with open data from the Argentine market? It would be very useful for those of us who are starting out in predictive analysis.

In response to: Demand Forecasting with Neural Networks
Sofía Lencinas 1 week ago

Excellent explanation of association rules. We applied it to detect purchase patterns in B2B clients and the results were very clear.

In response to: Data Mining for Decision Making

What our clients say

Concrete results from integrating predictive intelligence into their operations.

JM

Jorge Martínez

Operations Director, Logística del Plata

“We implemented the demand forecasting model with LSTM networks. We reduced storage costs by 28% in the first quarter. The Intelligencetomorrow team understood our historical data limitations and adjusted the model seamlessly.”

CR

Cecilia Roldán

Data Analytics Manager, Grupo Sur

“The data mining they applied to our sales records revealed seasonality patterns we had not detected. We now plan purchases three months in advance. The process was transparent and the executive reports were clear.”

AL

Andrés Lucero

CTO, Industrias del Norte

“They integrated their predictive model with our legacy ERP without disrupting daily operations. The hybrid architecture they proposed allowed us to keep existing systems and add real-time predictions. Solid work.”

Corporate Trust

What Our Clients Say

B2B companies already optimizing their demand with artificial intelligence.

5.0

“We implemented their predictive models in our supply chain. We reduced inventory costs by 28% in the first quarter. The technical team instantly understood our operational needs.”

Gustavo Méndez

Director of Operations, Logística del Plata S.A.

5.0

“The data mining they applied to our historical sales revealed seasonal patterns we had never identified. Now we plan six months in advance.”

Carolina Linares

Planning Manager, Industrias del Sur

5.0

“They integrated their predictive AI with our legacy ERP without disrupting a single day of operations. Demand projection accuracy exceeded 92% from the first month.”

Martín Roldán

CTO, Grupo Tecnológico del Norte

Trusted by

Logística del Plata Industrias del Sur Grupo Tecnológico del Norte Alimentos Pampa Metalúrgica Centro

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