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Architecture and a benchmark

Get the answer, or walk the graph.

Graphify turns your repo into a code knowledge graph the assistant traverses — query a node, follow a path, explain the route. LemonCrow indexes the same structure but searches it in one call, and it's a full runtime rather than a retrieval layer. Graphify is now in LemonCrow's retrieval benchmark too, so below is both: the numbers, and the architecture comparison that explains them.

What it actually scored — same 14 repos as every other tool
Tool MRR p95 p100
LemonCrow +semantic (BGE) 0.727 390ms 1057ms
LemonCrow lexical (default) 0.676 134ms 319ms
Graphify 0.267 585ms 3769ms

Publishes LOCOMO/LongMemEval memory-QA accuracy, not code-search MRR -- first time measured on this benchmark: 0.267 MRR, 0.188 hit@1, vs. LemonCrow's 0.727 (semantic) / 0.676 (lexical). Full architecture comparison on its own page.

Two ways to answer a code question (LemonCrow column highlighted)
LemonCrow Graphify
Core model One call — code_search returns the symbol, its callers and callees, and ranked source. A knowledge graph the assistant traverses — query, path, explain.
The agent loop One shot — ranked results come back in a single call. Multi-hop — the assistant walks typed edges to assemble it.
Scope A full runtime: search, role-scoped agents, skills, hooks, verification, and cost tracking. A retrieval layer: the graph plus its query tools.
Retrieval Ranked by call-graph centrality; lexical by default, optional semantic. Traversal along typed edges — calls, imports, defines, references.
Evidence Published SWE-bench and 14-repo MRR runs, committed to the repo -- Graphify included. Publishes LOCOMO/LongMemEval memory-QA numbers, not code-search MRR -- 0.267 MRR the first time it's run on this benchmark.
Freshness Incremental re-parse of the file that changed. Update a node; the surrounding edges stay intact.
Where Graphify has the edge

No comparison is one-sided. If you want a standalone, fully-open, human-browsable code graph with nothing sent anywhere, Graphify is a strong pick — and here's exactly where it's ahead:

License Apache-2.0 runtime, open-core (proprietary engine). MIT — fully open.
Telemetry Anonymous counts, on by default — one command turns them off. None.
The artifact A local SQLite index the agent searches. A graph.html / graph.json you can open and browse yourself.

The honest take

Same starting point — parse the repo, keep the structure. Graphify hands the assistant a graph to walk and a file you can open; LemonCrow precomputes call-graph centrality so the hop that matters is already ranked into the first result, then wraps it in agents, skills, and hooks. Different bets. Ours is one-shot resolve inside a full runtime, with the benchmarks committed.