Development of a central platform for networking activities

What was our brief?

We were commissioned by an interdisciplinary and international science and development center. This center serves as a hub for collaboration between hundreds of partners from business, science and administration and is dedicated to driving innovation through targeted networking and knowledge transfer.

The center needed a central tool that would give all networking activities a clear structure and document them in an audit-proof, transparent and GDPR-compliant manner. The aim was to create a platform that would significantly simplify both the management of relationships and the traceability of interactions.

The core requirements of the contract included

1. structuring into four clearly defined data areas: Companies (firms, institutes and organizations) Contacts, Cases and Activities.

2. powerful filter and search functions to find relevant information in seconds.

3. attachments and evidence that are directly linked to activities and can be accessed at any time.

4. a public network of experts that makes selected contacts accessible to outsiders as a subset.

What goals did we have in mind?

The implementation of the project focused on several key objectives:

• 360° view of relationships: The platform should bundle all interactions with an organization in one place to ensure complete transparency.

• Usability first: An intuitive user interface with a "zero learning curve" should ensure that the platform can be used from day one without major training.

• Scalability: The database architecture should be designed in such a way that future modules or extensions can be easily integrated.

• Data protection and security: The storage and processing of data had to be GDPR-compliant in order to meet the highest data protection standards.

• Fast evaluations: Tools such as filters, tagging, full-text searches and Excel exports should make it possible to extract relevant information in the shortest possible time.

• Public visibility: The expert network should be shareable as a widget or embed to increase the platform's reach.

How we solved this

For the implementation, we relied on a modular approach to meet the client's specific requirements.

The tech stack included our own Python framework DAISIE for backend development, PostgreSQL as database and SQLAlchemy ORM for data modeling. This stack ensured a robust and performant foundation for the platform.

The platform was divided into four clearly defined core modules, which map the data areas "Company", "Contacts", "Cases" and "Activities". These modules are linked to each other by precisely defined relations in order to create a consistent and comprehensible data structure.

A powerful filter engine has been implemented that combines multi-select filters, full-text search, date filters and tagging. These functions enable fast and precise searches, even with large amounts of data.

An object-based storage system has been integrated for file handling. Files, such as meeting minutes or presentations, can be uploaded while their metadata is stored in the database. Preview and download functions ensure that the files are easily accessible at all times.

The requirements for a public expert network have been met by the ability to provide selected contacts as a shareable subset. This can be displayed via widgets or embeds on external websites, providing increased reach for the network.

Result and added value

The completed platform provides the Science and Development Center with a unified and scalable relationship management solution for the first time. All interactions with partners are fully documented, creating an ideal basis for funding applications and project reports.

The shareable network of experts has significantly increased the center's reach. At the same time, the platform enables quick and precise evaluations, which significantly increases the efficiency of employees.

Thanks to its modular architecture, the solution is future-proof. New categories, functions or reports can be added within a very short time without affecting ongoing operations.

This solution has provided the center with a tool that accelerates the transfer of knowledge between research and industry in the long term. At the same time, it takes the pressure off employees and gives them more time for their actual innovation work.