Integrating Ultima VII with SurrealDB Agent Memory: the testing
How Ultima VII was integrated with SurrealDB Agent Memory via Exult code changes to emit events and a Rust app using egui between the game and Agent Memory.
33 stories
How Ultima VII was integrated with SurrealDB Agent Memory via Exult code changes to emit events and a Rust app using egui between the game and Agent Memory.
A folder of Markdown meeting notes becomes a self-maintaining knowledge graph in SurrealDB with CocoIndex and Pydantic AI, fenced in by a database role.
SurrealDB imports Snowflake tables directly. Move warehouse data into a context layer where facts, relationships, vectors and agent memory live in one engine.
The SurrealMCP server lets you add one URL to any AI tool, sign in with your Surreal ID, and deploy, query, and look after your SurrealDB Cloud account.
Why tri-temporal belief history is needed for agent memory to properly simulate human memory and how to work with SurrealDB Agent Memory to best use it.
A practical guide to eight embedding models — text-embedding-3-small/large, gemini-embedding-001, embeddinggemma-300m, qwen3-embedding, and more.
Why Ultima VII through the Exult open-source game engine ended up being the perfect testing platform for SurrealDB Agent Memory
An AI agent triaging insurance claims needs semantic, graph, and document data. Do it in one SurrealDB database.
AI agents an be talked into modifying your data with a single polite request. SurrealDB's role-based access control lives in the data layer the LLM can't reach.
How a high-end fashion house can model clients, artisans, products, and waitlists as one graph — with vector recommendations and full-text search built in.
Model a financial services ontology in SurrealDB: map ownership, custody, and transactions as a graph and resolve beneficial-ownership chains in one query.
Model your security assets as a graph in SurrealDB and use the VERSION clause to time-travel through incidents. Schemas, seed data, and queries included.
Vector search and graph traversal in a single SurrealDB query. How single-engine hybrid retrieval makes RAG agents more accurate.
Define a custom SurrealQL function to call any embedding API, then run semantic search, graph traversal and field shaping in one query
Guest author Cyril Scetbon on streaming graph pattern matching: detecting when a pattern is satisfied in real time, incrementally, as new edges are added.
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