About Sifty

Sifty applies Machine Learning to sift through thousands of data points in seconds, reducing repetitive tasks and saving time for Customs Brokers.

With this approach, Sifty will change the flow of information in international trade to make it better together.

Our story

The market pushed us to build a solution for its bottlenecks.

A customs broker contacted Sifty's founders to explain an operational bottleneck he wanted to avoid solving in the same way that his competitors do. Usually by increasing staff and diminishing their revenue.

Sifty's approach was to analyse the customs brokers data to be able to reduce the time they spent on mundane and repetitive tasks.

Through a combination of experience in international trade, data science and working with industry partners, Sifty began to build products that immediately solved long standing problems within international trade and logistics.

Sifty's founders dislike repetitive tasks.

When they encounter anything like it,  Oscar and Julio immediately spend time coding something to reduce the burden of repeating the same task over and over.

Our customers constantly have to repeat low-cognitive activities; due to the vast amount of information, humans cannot remember and recognise data patterns as efficiently as computers do.

Oscar Morales

Oscar has a BA in International Business and an MBA. He has worked in the international trade industry, including freight forwarders, customs broker agencies, and multinational logistics companies, as well as building his own import/export business.

He's experienced both sides of trade bottlenecks and suffered the frustrations first-hand.

Oscar Morales, co-founder of Sifty
Julio Amador, co-founder of Sifty.

Julio Cesar

Julio is an experienced researcher and engineer in Machine Learning.

He has worked as both researcher and professor of Data Science at prestigious universities, including Imperial College and the London School of Economics.

Julio is passionate about harnessing the power of Data Science and Machine Learning to deliver efficiency and next-generation solutions for international trade.

A group of experts building Customs Tech

Sifty's growing team of data scientists, machine learning engineers, developers and industry experts are creating state-of-the-art software for Customs Brokers.

Soon, Sifty will become the OS for International Trade.

Our team writes in our blog about Machine Learning, AI business applications, Customs Tech, International Trade, Technology and more.

Take a look at our resources centre to read more on what we have been up to recently.

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Our Philosophy

Machine Learning as a support system to teams.

Sifty approach is to use Machine Learning to help people work faster—removing mundane tasks and focusing on exciting and engaging activities.

It's about doing more with software and the same amount of people.

We give computers low-cognitive repetitive tasks while Customs teams take on activities that require instinct and intellect.

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Sifty's philosophy is based on honesty, creativity and curiosity.
Quality assured

Customer testimonials

Read what our customers think of Sifty.

"Sifty is a very practical and useful tool, with just 5 clicks you have the information you need and it adapts to the needs of the client. We highly recommend that you try Sifty."

Manuel Alejandro Rendon Morales

Air Cargo Importer, Carga-Aerea

One of Sifty's customers: Carga Aerea is a customs broker in Mexico.
“Sifty has improved our speed, before Sifty the processes were manual and time-consuming. It makes our work a lot easier, we use it on a daily basis, it is a very efficient, accessible and easy-to-use tool.”

Wendy Paola Perez Lagunas

Customs Clerk, Leonisa, USA

One of Sifty's customers: Carga Aerea is a customs broker in Mexico.
“My experience with Sifty has helped me to be very agile and perform better in my work. With a few simple steps I can do the same operations but faster.”

Olga Lidia Arellano Hernandez

Global Order Management

One of Sifty's customers: Carga Aerea is a customs broker in Mexico.

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