The new era in industrial biotech is driven by new and fast-emerging sequencing technologies. While years ago the throughput in sequencing might have been the bottleneck, we today have to redesign the strategies for data handling, assembly and comparative genomics to mine and leverage the generated sequence data for various applications. There are different solutions for individual tasks, developed by technology providers and research institutes. We identified a need for high throughput biological interpretation of the genome sequences generated and decision support for production strain engineering. We present a recent development of Genedata Phylosopher that addresses the integration and automatic interpretation of modified genomes and strains. It takes into account the integration of existing public and proprietary knowledge, maps new sequence information and points to the biological implications of detected mutations. The adaptable classification of mutations enables easy data navigation and investigates correlated effects on protein level, metabolic pathways or regulatory level. We will present an example of software that handles these data in collaboration with further experimental data like transcriptomics, proteomics or metabolomics, to decipher a production strain history and guide further developments.