Many industries are changing rapidly because of ongoing disruptive innovation. At everis we support our clients through this change. We help our clients to improve their business results by taking advantage of disruption and add value through new ecosystems, service models and solutions.
We have our innovation centre, NextGen, where we focus on the disruption of the business world as a result of advancing technologies. NextGen provides the next generation of technology through innovative and disruptive initiatives. We designed the bank of the future, increase the value of
employees with artificial intelligence, promote technology education through creative technologies, and bridge the gap between start-ups and large corporations.
NextGen lives and breathes global digital transformation.
From CAPEX to OPEX, cloud models and taking a strategic approach to production. From digital and legacy transformation, Blockchain, Big Data Analytics, AI and Robotics. We have the know-how, the attitude and drive to maximise our clients’ opportunities.
Decentralisation, transparency and automation
We believe that the key to success lies not only in technology, but in business processes, cultural change and customer understanding. Success begins and ends with the client, not with a proof of concept in a sand box.
Blockchain & DLT
We ask questions to understand the aspirations, desires and existing reality of our client. We use design thinking methodologies to find innovative solutions, and to make prototypes that bring results.
We build and develop viable products that will be tested by real users.
Let’s learn from our mistakes and stop internalising knowledge, and change our culture to embrace a new reality, the decentralised world.
in new sectors and locations
i-deals, thanks to its network of contacts, operates as a technology broker to connect innovative technologies produced in the academic and business world with markets that require such innovations.
i-deals works globally, coordinating European projects or bringing technologies from Asia to Europe and America.
Turning Data into Real Value
Most organisations struggle to improve their internal IT-driven processes and core operations in order to achieve better corporate performance. Powered by machine learning and artificial intelligence, Process Mining technology leverages the digital footprint organisations leave behind in their IT systems and provides complete transparency into how processes are working in real life.
How it works:
Data provided by Information System operations are used as a data source. They are collected and analysed in real time to extract information used to build the process instances (also known as cases). Thanks to Process Mining algorithms and machine learning techniques, cases are analysed and characterised to model business processes (process). It is then possible to check the conformance of each new process instance (case) with the nominal process (process).
Your business processes and the way your Information System works are then revealed to you; places where time is wasted, and places where errors occur in a particular operational context. It is also possible to detect failures or bottlenecks and optimise business processes.
Automatic Technology Data Migration
Based on artificial intelligence and machine learning. The use of these technologies for migrating data provides compelling cost and performance benefits.
We provide a specific tool designed to migrate schema and data. During schema migration, the tool automatically maps the corresponding schema from source to destination. After the schema has been migrated, the tool provides the option to move data with automatically generated scripts.
In addition to schema and data migration, this tool gives you the option to generate compatibility reports which summarise incompatibilities between the target and source instances which would prevent streamlined migration.
Augmented workforce is an initiative which seeks to increase the value of employees through software (artificial intelligence) and hardware (social robots).
AW – Artificial Intelligence:
Augmented Workforce uses artificial intelligence to create virtual workers (Next Artificial Workers / NAWs) to assist employees so that they can focus their full potential where they feel most comfortable and contribute most, while the remainder of work is supported by a virtual worker. The NAWs will need to be taught the tasks to be performed through a learning environment and will then be able to perform the task like a person would – even improving their method.
AW – Social robotics:
The goal of the augmented workforce is for the robots to integrate socially and enhance people’s capabilities. This requires flexible interaction with people and fostering good relationships. The robot’s behaviour is key; we use a Cloud Robotics Platform which enables development of behaviours, separating this from the technical aspects, to design and implement behaviour and the logic of it. These behaviours may then be used in any robot in the cloud.
Building win-win bridges between start-ups and corporations
everis NEXT is the world’s largest B2B-ICT start-up repository, connecting the global innovation ecosystem. Using highly differentiated technology, everis NEXT accesses millions of start-ups worldwide, seeking the perfect connection for the needs of large corporations. We follow the dynamics within everis NEXT in real-time and identify opportunities from the most advanced technology trends available.
With everis NEXT we aim to capitalise disruptive innovation while boosting the growth of start-ups and their talent.
everis works with leading global banks to explore ‘the future of banking’ to understand where major disruption will occur. We host an annual programme where global leaders come together to discover local Fintech ecosystems. Together, we look at the most significant developments and analyse the results and implications of the various disruptive challenges.
We work together to define and co-create the future of banking by defining disruptive and innovative business models.