Temporal Knowledge Graphs for Brand Intelligence
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Dec 17, 2025 at 4:30 AM EST
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The core insight: most monitoring tools treat every data point as independent. Sentiment score today. Mentions this week. AI visibility score. But brands exist in time — events cause other events, perception shifts have reasons, and patterns repeat.
We combined two existing technologies: 1. A temporal knowledge graph (Graphiti + Neo4j) that stores signals with timestamps and typed relationships 2. Contextual document search (Gemini Files) for brand-specific RAG
The graph lets you query things like "show me everything that affected our Trust pillar in Q2" and get a causal chain, not just a list of mentions.
Not claiming this is novel technology — graph DBs and RAG are well-understood. What's new is applying them specifically to brand intelligence with the temporal dimension as a first-class citizen.
Happy to answer questions about the architecture or trade-offs we encountered.