At a glance
The philosophical difference
Supermemory builds memory by extracting and structuring information from your connected sources, then serving it back through search, a knowledge graph, and entity profiles. Extraction does the work: you connect a source and the memory layer derives the structure. Worlds takes the opposite stance. Memory is curated, not accumulated. You decide which facts matter, assert them as RDF triples, and the engine keeps them in an append-only ledger. Nothing is inferred; everything is stated. The tradeoff is effort against control. Extraction-based memory is cheap to start and useful for loosely-structured recall. Curated graphs cost more to maintain and return exactly what you stored, with a path back to every source.When Worlds fits
- The fact must be true, not merely similar: compliance, safety, operations.
- You need to resolve contradictions at the data layer instead of leaving the model to guess between conflicting chunks.
- You want a deterministic query language (SPARQL) over your knowledge, not just retrieval.
- You need a chronological record of when facts changed and who asserted them.
When Worlds does not fit
- You want zero-effort memory from messy, unstructured sources with no curation budget.
- Your use case is loose recall (“what did we talk about last week”) where an extracted summary is enough.
- You are prototyping and have no graph vocabulary in mind yet.