Retrieval Infrastructure
The Hybrid Grounding Engine
Most RAG tools retrieve something close to the right answer. That's fine for exploration, not for a legal disclaimer or an API rate limit. MsgStack runs two retrieval modes side by side: deterministic graph traversal for the facts that must never be paraphrased, and vector search for everything else — fused into one answer, prevention-by-construction instead of a drift score you check after the fact.
Two-Layer Retrieval Architecture
MsgStack runs a dual-layer search, querying database graphs for locked truth while matching concept vectors for exploratory context.
| Retrieval Mode | Engine | Purpose | Constraint / Fallback | Avg Latency |
|---|---|---|---|---|
| Deterministic Traversal | SQLite Adjacency Tables | Verbatim Approved Claims | No approximation allowed. Strict match or failure. | < 0.8ms |
| Semantic Exploratory | Turbovec Vector Store | Exploratory / Concept Search | Retrieves nearest neighbor context nodes. | < 15.0ms |
See a query hit the graph
A typed edge (DEPENDS_ON) connects an Engineering Spec entry to a Policy Shield entry; an INFORMS edge connects it to a Message House proof point. One traversal, three departments, no copy-paste.
Alignment Scoring
Retrieval is only half the battle. MsgStack validates generated outputs against the matched graph nodes using an automated alignment validator.
If an AI assistant generates copy that contains metrics or claims not backed by a locked fact, the alignment score drops. Scores below 95% are automatically rejected or flagged for human approval.
Local Execution & Speed
Run MsgStack locally in-house for zero latency overhead. Integrate the FastAPI server or connect the MCP client directly.