Universities & research
We have worked with universities on two very different kinds of problem, and we are equally at home in both.
Archives and humanities projects
Digital archives, collections and other humanities websites — the kind of project where the material is irregular, the metadata matters, and the thing has to still be there and still be citable in fifteen years. This is where generic content management systems tend to fall down hardest: the collection gets flattened to fit the software instead of the software being shaped around the collection.
We model the structure to the material, keep URLs stable and citable, and make sure the collection can be found — by search engines, by answer engines, and by the researcher who has only a half-remembered fragment to go on.
Scientific and research computing
At the other end of the building, we have built a Slurm-based parallel processing cluster for a university research group: many machines scheduling scientific workloads, with the storage, queueing and user management that has to sit around them, and the ongoing maintenance to keep it running.
Universities are institutionally slow and permanently under-resourced, and that is not a criticism — it is a design constraint. It means building things that survive a change of staff, a change of budget and a change of priorities.