company
Neo4j is a graph database company whose platform models connected data for use cases like fraud detection, knowledge graphs, and network analysis.
No evidence-backed relationships are recorded.
A Strands hook recorder writes each agent step into Neo4j through Neo4j Labs' agent-memory SDK. The audit query that finds every decision touching a bad source depends on a dict lookup keyed by tool name.
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Microsoft and Omdia put the average security operations centre at close to 3,000 alerts a day with 42% never investigated, while a 2026 benchmark scored the best frontier model at 3.8% on finding malicious events in raw Windows logs.
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A dev.to design guide moves JSON documents and vector search into one PostgreSQL instance, and the evidence it offers is operational: deleted ETL pipelines and sync bugs, with no query timings on either side.
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Neo4j's first product since closing the GraphAware deal in August turns financial crime work into four workflow stages running over one graph joined from the separate systems a bank already has.
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A dev.to post on five Cypher patterns for agent memory lands hardest on the write path. Agents re-extract the same entity from many documents, and a MERGE keyed on a mutable name creates a fresh node each time the string changes.
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An independent rebuild of the SQLite side says the gap is real, but the published tables measure two different queries on two different graphs, so the depth at which SQLite's plan collapses on your data is a number you have to take yourself.
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A comparison of Mem0, Zep and LangChain's memory classes puts the split at adjudication rather than storage. Mem0 pays two model calls per message to get it.
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A consultant's two client failures, a supplier filter and a 10kg shipping quote, both broke on a numeric comparison that top-k similarity does not perform.
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One paper reports 85.2% correctness on about 2.2k tokens against 72.5% on 16.3k for chunk-based RAG, while agentic failure attribution drops to 0.00 accuracy past the first hop.
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A vendor-commissioned test capped every engine at 512 MB. Neo4j Community cleared 10 concurrent clients and returned four of 744 operations at 40, which no latency table would have shown.
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The UK graph vendor's first outside round backs a bet that enterprises have stopped shopping for smarter models and started paying to fix their own data.
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