Deployment and Integration

Deployment matters as much as analysis. Mnemosyne is building with on-premise delivery and existing institutional infrastructure in mind.

In many of the settings we know well, cloud is not regarded as a neutral choice. It may be unwelcome for governance reasons, impractical for institutional reasons, or simply at odds with how local facilities are already organised.

At the same time, many groups have already invested heavily in HPC. A serious platform should be able to work with those realities rather than asking customers to ignore them.

Why this matters

Institutions where cloud services are difficult or unacceptable
Academic environments with existing HPC investments
Teams that need local control over data handling and workflow execution

Operational priorities

On-premise deployment where local control is important
Use of existing HPC resources rather than bypassing them
Practical integration into established sequencing and reporting workflows
A delivery model that respects local operational constraints

For many potential customers, the question is not whether analysis can be run somewhere, but whether it can be run in a way that fits their actual environment. That is a core design assumption for us.