Due to the uniqueness of the paper structure, fraud is no longer possible
Tracking of the items in operational processes and volume prediction
No need for florescence ink, RFID or Frankit Machines. Can be used with any product, no need for additional marking
No process change in the existing operations. Due to the simple process only a camera is needed
We are digitising logistics with just a blank sheet of paper!
Prevent revenue leakage by identifying fake stamps with PixoMail!
Revenue leakage in mail operations due to fake stamps is estimated to amount to 500 Million Euros.
PixoAnalytics identifies fake stamps on mails and parcels as well as re-used stamps in the sorting operations up to 4m/s conveyor speed.
No impact on your sorting process
Patent pending technology with very high accuracy
High volumes without interruption
Sustainable approach with low investment
Our white paper for stamp fraud is available now!
How PixoAnalytics makes identification secure
Did you know that just a piece of paper can contain more information than any QR code has?
Low reading rate due to low printing quality
Low verification rate due to low reading rate- very limited number of mails can be verified and billed correctly
Billion of business letters cannot be fully controlled due to the low reading & verification rate
Revenue leakage only in mail operations are assumed more than 500 million Euro only in Europe and North America
Unless all previous solutions,
PixoAnalytics cannot be exactly copied
PixoAnalytics is always unique like a fingerprint since the paper structure can not be reproduce
High reading rates
Regardless of the printing quality
Works with every type of mail
The only technology for identification and tracking of letters without any environmental footprint
Faster processing thanks to automation
Working even on partially damaged paper
How it works
PixoAnalytics is a unique code generating technology using paper art, and the future technology for non-tampered identification.
Each piece of paper has its unique and natural paper structure what we call fingerprints. Our technology uses these fingerprints for identification of parcels, mail and any other identification purposes.
Just like regular fingerprints, the paper structure can not be reproduced.
Benefits for Business Customers
Significantly low investment
Only camera and standard scanner needed
No process change
In the current mail operation
The only technology for identification and tracking without any environmental footprint
Usable with any product
no need for additional marking
Easy installation & process
by the consolidator company , business customer or letter shops
Check of number & type of mails according to sender
information is used to control the received payment and offered discount
PixoAnalytics offers automated revenue protection for every mail product, without changing the nature of the franking product itself.
Identification of fake stamps on mails & parcels
Sustainable approach with low investment
Patent pending technology with up to 99,9% accuracy
Identification of parcels without label via ordinary (smartphone) camera
Calculation of shipment volume and identification of shipment material
Patent pending technology to track parcels without labeling
Return shipments without paper & labeling for e-commerce customers
PixoReturn algorithm can be integrated with a mobile app
Improve your e-commerce customer experience
Software to identify labels in supply chain operations with > 99% reading rates
Reduced inventory cost by precise item counting, locating & tracking
Increased reading rates by inventory robots in warehouse management
PixoPharma can read the medication box and sealing on the box with high resolution camera
No need for special cameras or change in packaging operations
Identification of fake medication or medical tools with 99,9% precisicion
Algorithm and camera to read paper fingerprint and control unique characteristics visually
PixoID can be used as add-on software by security agencies, companies and governments
Identification of paper fingerprint of important ID documents (passport, drivers license etc.)
Deutsche Post AG / P&P, EVP / Operations
"This new solution seems to be a complete new way to identify all of our letters, in an automated approach and help us to protect our company's revenues."
DHL Supply Chain, EVP / Solutions Design
"If we are able to use paper as identifier, we are more independent and flexible to offer identification as a service to our customers without relying on individual engagement with our customers for every single part."
PixoAnalytics is a German based vision recognition and AI company founded in 2020. Deutsche Post AG is currently the biggest investor of the company.
PixoAnalytics makes it possible to identify any item like letters, parcels, medications, fabrics, plastics etc.. at any point in time in any location with its unique surface structure recognition algorithm. PixoID can track and trace any item without requiring any additional identifier. Unique algorithm can identify an object in milliseconds among billions of others. Its unique algorithm can also identify fake and original products only looking at material structures even by a smartphone camera. PixoAnalytics has 6 patents pending worldwide.
PixoAnalytics revolutionises the future of business with just a blank sheet of paper and fights against frauds successfully.
Ali is an expert in automation, innovation and product development in logistics. He has more than 20 years of international experience and holds 1 issued patent and 7 patents pending worldwide.
During his 20 years of working life, he has worked in the big and international companies such as Alstom (General Electrics), Bosch & Siemens, Schenker logistics, DHL etc. and managed automation and innovation projects in the different locations such as Germany, Turkey, Poland, Spain, USA, Thailand and Singapore.
He has M.Sc. degree in Mechanical Engineering and executive MBA degree from Kellogg-WHU.
Baris Cem Sal
Baris has previously led Analytics and Information Management Practice for Deloitte Turkey, Research Scientist in Amazon. He is experienced in leading software development, business consultancy and data science teams. He has been leading Operations Research team in Corporate Data Analytics Department since October 2017 in DPDHL. He has worked with customers such as Schneider Electric, The Home Depot, Turkish Telecom, Turkish Armed Forces, Sisecam and more in Turkey, Australia, China, United States and many Pan-EU projects.