Memory and Retrieval Boundary
We clarified the boundary between conversation memory, retrieved evidence, and answer synthesis in the Agentic RAG runtime.
Product releases, platform milestones, and important changes across the Cortagent stack.
We clarified the boundary between conversation memory, retrieved evidence, and answer synthesis in the Agentic RAG runtime.
Datasource routing work was added so retrieval can target relevant sources instead of searching every corpus the same way.
Keyword retrieval work gave the RAG layer a lexical path for exact terms, identifiers, and phrases.
Retrieval stitching work was added to join evidence from multiple retrieval paths without losing source boundaries.
Reranker selection work was added to keep evidence ordering separate from initial retrieval.
Language routing work was added so multilingual queries can be handled without treating language as a knowledge silo.
Graph retrieval modules were added so relationship-oriented evidence can become a selectable retrieval path.
Vector integrity checks were added to catch invalid retrieval state before it leaks into answer synthesis.
RAG event journals and lineage artifacts were added so retrieval behavior can be inspected after a run.
A pronoun resolution path was added to reduce failures on follow-ups like 'what about that' and 'what was her role'.
Conversation context handling was added so follow-up questions can reuse prior state instead of being treated as isolated prompts.
We added query complexity logic so decomposition can be based on explicit signals instead of defaulting every request into a heavy path.
A retrieval router baseline was introduced to make vector, keyword, graph, and swarm-style paths selectable instead of implicit.
Early work moved query handling toward explicit structure parsing so retrieval could respond to intent and complexity.