Three signals, one query.
A single query spans graph links, semantic vector matches, and wiki context. The candidates merge, and on paid plans a premium reranker sharpens which memories surface first.
Graph, vector, and wiki signals, merged — with a premium reranker on paid plans.
One query fans out to graph, vector, and wiki signals, then merges and reranks them into a single ordered result.
Every signal searched in one pass
Most memory tools make you pick a lane: a vector store, or a graph, or full-text. Hybrid retrieval searches all three at once. Graph links, semantic vector matches, and long-form wiki context are queried together, so a single ask reaches everything your agents know.
- Graph + vector + wiki — every signal searched in one pass
- Merged, not siloed — results come back as one ranked set
- One ask, full context — no separate calls to stitch together
An extra ranking pass on Pro and above
Merging is only half the story — order matters. On paid plans, a premium reranker takes a second pass over the merged candidates to sharpen which memories surface first, so the most relevant context lands at the top of the result.
- Premium reranker — an extra ranking pass on Pro and above
- Sharper top results — the most relevant memories surface first
More capabilities
Five capabilities, one shared memory. Here are the other four.
One query, all the context.
Start free to try hybrid retrieval, then upgrade for the premium reranker when you need sharper results.
No credit card required · Free plan available · Bring your own OpenAI key