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About us2024-02-10T17:34:38+00:00

About Us

Why Did We Create Allyy.io?

The move to a Global Digital Attention Economy has entirely changed the game and will have winners and losers. Winners are those with the capability to automatically cut through the overwhelming noise with accurate, relevant, and individualized messaging.

What until recently was hugely expensive and required a team of data scientists is now available to companies of all sizes in a SaaS solution: designed to optimize our customer’s performance across several services.

We created Allyy.io to empower companies of all sizes by giving them tools to make accurate predictions, in order to target consumers with genuinely individualized and relevant messaging.

Customers Achieve Their Highest Purpose

When a concert venue uses our platform, we contribute to broadening the live performance audiences while supporting a new breed of artists.

When we help an NGO to raise funds, we will contribute to making sure more resources reach those in need.

For Media houses, we increase the reach and lifetime of journalistic content and create room for critical first-class journalism.

We also contribute to, e.g., knowledge sharing for members of health-related associations, fewer cars in large cities, and higher health protection.

Ethics & Regulations

How does Allyy.io use AI to apply high ethical standards and comply with design with the strictest regulations?.

At Allyy.io, we are using the power of machine learning and AI to revolutionize marketing personalization. Central to our approach is the use of SHAP (SHapley Additive exPlanations) scores. This state-of-the-art approach allows us to de-mystify our AI models by providing clear, interpretable insights into how each feature influences predictions.
By prioritizing transparency and accountability through SHAP values, we build trust with our clients and align our innovative solutions with the highest ethical practices, ensuring responsible and effective marketing strategies.
From its origin, Allyy.io has committed itself to applying high ethical standards fully complies by design with regulations such as GDPR, and follows best practices such as in EU Commission’s “A European approach to excellence and trust.”

What is Allyy.io’s purpose?2022-08-30T14:47:24+00:00

The purpose of Allyy.io is to make communication more relevant for every individual with the help of algorithms and statistical models.

Our clients are already communicating with their customers through website tracking, email, app, SoMe, call center, etc., with the ambition to make the communication as relevant as possible for their audiences.

We just use non-sensitive data to optimize communication relevance and only with the customer’s consent.

Which personal data is used?2022-08-30T14:48:24+00:00

Data used to make predictions are first-party, non-sensitive data only:

  • Anonymized customer data such as socio-demographics, transaction history
  • Response data from web tracking on the client’s website, and email click history

The client is in control of which data is uploaded to Allyy.io.
No sensitive data such as name, address, race, sexual orientation or religion is uploaded to Allyy.io.

There is full transparency about which data variables explain the models’ outcome.

If the client does not want specific variables to be used in the models as the outcome may lead to discrimination, such as e.g. gender, the client has the option to remove this data variable.

How is data secured?2022-08-30T14:49:23+00:00

Personal data are pseudonymized before being uploaded to Allyy.io.

Allyy.io does not have access to the pseudonymization key.

It means that data in Allyy.io can not be related to specific data subjects.

Moreover, column names and column content are hashed. It means that data subject attributes and values are not available in the platform other than in a code.

How does modeling work?2022-08-30T14:50:00+00:00

Allyy.io has developed an algorithm that we call “Cognitive Match.” Cognitive Match creates new data features to be used in modeling by analyzing a) response data and b) content descriptions.

These features quantify a match between an individual, an anonymous customer profile, and a specific piece of content. 

The Cognitive Match expresses the anonymous individual’s interests and preferences.

These features are processed in the Machine Learning model with other structured data.

How do we make models explainable?2022-08-30T14:50:47+00:00

Allyy.io’s clients have access to a blueprint of the models and documentation of the algorithm as a feature in the Allyy.io API.

How to use predictions?2022-08-22T11:55:51+00:00

The client can access recommendations per individual contact, subscriber, lead, etc.

The client can filter recommendations and can exclude specific content types.

We tell clients not to recommend content that can be offending or inappropriate to the customers or that can damage the customer’s reputation.

The A-Team

Olivier Poivey

CEO & Co-founder

O, Captain! My captain! – Olivier is our fearless yet calm leader. His house is even built on ancient Yogi principles . Although not fond of admitting it – the rest of the team seems to be beating him at Petanque – maybe he’s been living in Denmark for too long ;).

Kim Gregersen


Our C(3)PO is the man with ideas and the oracle when it comes to Marketing individualization and Automation – I guess you could say he speaks more than 6 million Marketing Automation languages.

Mads Frederik Frederiksen

Senior Account Executive

He is a cross fitter and a life/fishing enthusiast – the story has it that he has attempted “smuggling” back 20kgs of fish from Norway. Unfortunately, the cargo got misplaced and arrived a few days late – needless to say, it wasn’t frozen at this stage.

Evgeni Sokolov


Our version of the Sitting Bull Chief when it comes to the Development team. We’ve been told he is quite the accident-prone daredevil regarding Snowboarding and Mountain Biking.

Álvaro González de Sande

Data Analyst & Product Owner

Aka. the Chameleon. He wears many hats in his job; possessor of solution and data cognoscenti. However, it has been said that the nickname was not cultivated by work performance but by chameleon-like behavior while taking exams.

Jack Lee

C# Developer

Senior Software Inventor the fairy tale goes, that the senior part comes from being a three-time medalist (Gold, Gold, Silver) with the DR case that won in a few different categories during the Danish Digital Awards in 2020.

Dmitry Dyadin

Senior Software Developer

Senior Code Maker and fixer

When he isn’t dabbling with code he rocks with his Band called Modernova.

Check it out here: https://lnk.to/HitchhikingTheAir

Iris Elizabeth Pali

Marketing Strategist Manager

The heart and soul of our book club! With 24 books on her yearly list, she’s almost there. For her, AI isn’t just a another tool; it’s a confidant, always there to assist and maybe even share a laugh.

Ivan Shakhorski

Front-end Developer

When he is not diving into the deep and mighty space of Front-End development, he’s either eating pasta or riding his soon-to-come motorbike or, who knows – maybe both at the same time? Only Ivan knows.

Vincent Haunberger

Data Scientist 

Skillful with Python and a quick learner, he approaches data with the dynamism of an NFL quarterback and the curiosity of a SpaceX enthusiast. Embracing a ‘try first, theorize later’ mantra, he transforms complex data into winning plays.

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