Glossary

Plain-English definitions of transcription and knowledge-base terms.

Model Context Protocol (MCP)
An open standard that lets AI agents connect to external tools and data sources through a common interface — including memory and knowledge stores.
On-premises (on-prem)
Software that runs on infrastructure you control — your own servers or workstations — rather than a vendor's cloud. Data never leaves your environment.
Retrieval-augmented generation (RAG)
A technique where an LLM retrieves relevant documents from a knowledge store (often a vector database) and uses them to ground its answers.
Speaker diarization
The process of partitioning an audio recording by speaker — determining "who spoke when" — and labelling each segment (Speaker 1, Speaker 2, …).
Transcription
The conversion of spoken audio into written text, usually by an automatic speech recognition (ASR) model such as Whisper.
Vector database
A database that stores data as high-dimensional vectors (embeddings) and retrieves by semantic similarity rather than exact keywords.
Word error rate (WER)
A standard accuracy metric for transcription: the percentage of words the system gets wrong (substitutions, insertions and deletions) versus a reference.