Many companies have a variety of unstructured data sources — from emails and PDF documents to technical drawings and legacy databases. This data is often isolated in silos and is difficult to access. This makes continuous process automation difficult, leads to media disruptions and hinders rapid decisions. Manual merging is complex, error-prone and barely scalable.
Together with the customer, Liquam has developed an AI-based solution that automatically retrieves, consolidates and makes unstructured data usable for digital processes.
A practical example:
An industrial company had data from various sources — emails, scanned documents, supplier databases — that were relevant for quotation and order processes. Until now, this data was combined and processed manually. The aim was to use AI to consistently extract data, eliminate silos and create the basis for continuous process automation.
In this project, Liquam developed an individual solution that automatically processes and consolidates unstructured data. After analyzing the existing data sources and formats, an AI-based platform was built that recognizes, extracts and combines content from emails, PDFs, technical drawings or databases in a structured form.
The solution eliminates data silos, provides consistent data centrally and thus enables seamless further processing in ERP, CRM or DMS systems. A dashboard ensures transparency about data quality and the level of automation. The platform can be flexibly extended, e.g. with image and drawing recognition, translation functions or connection to self-service portals.
