The only gaps we've had with our production code and lisp is PDF (we use the java pdfbox), translating between RDF formats (also a java lib) and encrypting JWP tokens for PKCE dPop authentication (also java)
The complete conceputal AI system and space/time causal systems digital twin technology is all in common lisp (sbcl)
Also fantastic is the sb-profile library in sbcl that lets you profile any number of functions and see number of iterations and time used as well as consing all ordered by slowest cummulative time. That feature has been key on finding those functions that are slow and optimizing leading to orders of magnitude speed improvements.
The conceptual AI models operational concepts based on an understanding on how human concepts work, inference and automatic classification using those concepts, and then learning new concepts. The operational side of the digital twin uses functional specifications held elsewhere, which is also true of the operational concepts which use specifications in the form of conceptual definitions.
And the technology takes in RDF graph as data for input, builds the digital twin model from that data with extensive infererence, then expresses itself back out with RDF graph data. (Making https://solidproject.org/ the ideal protocol for us where each pod is a digital-twin of something)
We are working toward commercial launch in the coming weeks. (We are adding Project Pods, Business Pods, Site Pods with harvesting the sematic parse we do of PDFs into the pod, so we handle very big data)
EDIT: It's kind of ironic for me to make this claim since I use Emacs as my editor...
For parallel computing, we use: https://lparallel.org/ Its been great at handling massive loads accross all processors elegantly. And then for locking against overwrites on highly parallel database transactions we use mutex locks that are built into the http://sbcl.org/ compiler with very handy macros.