Traditional Graph RAG vs. GitNexus Precomputed Intelligence
Same question, fundamentally different approaches to answering it
Simulate Traditional (4+ queries)
Simulate GitNexus (1 query)
Reset
Traditional Graph RAG
LLM explores raw graph iteratively
"What depends on UserService?"
Query 1: Find callers
Query 2: Map to files
Query 3: Filter tests
Query 4: Assess risk
Partial answer (maybe)
4+
queries
GitNexus Precomputed
Tools return structured, complete answers
"What depends on UserService?"
impact(target: "UserService",
direction: "upstream")
Complete structured answer
Depth 1 (WILL BREAK): 5 callers, 90%+
Depth 2 (LIKELY AFFECTED): 3 callers
Clusters: Auth, API, Controller
Processes: LoginFlow, RegistrationFlow
Confidence scores on every edge
1
query
Interactive Comparison:
Click "Simulate Traditional" or "Simulate GitNexus" to see each approach animate. Hover over any element for details.