[KongchangAI]
ProductHACKING GG / VALGRAPH

VALOGRAPH

A real-time tactical analysis AI assistant built on a graph database and LLMs, providing multi-hop relational reasoning and persistent memory for VALORANT players.

Timeline (last 90 days)

Oct 19

VALOGRAPH (HACKING GG) is a real-time tactical graph command center and persistent AI memory engine built on FalkorDB Cloud and Groq for VALORANT tactical analysis.

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Oct 19

The VALOGRAPH project was completed at the WeMakeDevs x FalkorDB Graph Hacks hackathon.

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Oct 19

VALOGRAPH's FalkorDB cloud database contains 145+ nodes, 116+ edges, and 32 tactical properties (such as acs, kd, kda, atk_wr, def_wr, fire_rate, cost, pen, playstyle).

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Oct 19

VALOGRAPH's graph model uses the core node types: Player, Agent, Skill, Weapon, Map, Match, and Memory.

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Oct 19

VALOGRAPH uses the edge (Agent)-[:HAS_SKILL]->(Skill) to connect agents with their skills, (Player)-[:PLAYS]->(Agent) and (Player)-[:PLAYED]->(Match) to track compositions and match history, and (Player)-[:REMEMBERS]->(Memory) to store persistent AI coach insights across sessions.

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Oct 19

VALOGRAPH executes parameterized OpenCypher queries with a response time of about 1.36 milliseconds.

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Oct 19

Storing a player's Q&A history and playstyle tags as graph nodes linked to riot_id gives the AI long-term memory across matches; compared with stuffing conversation history into the context window, graph memory turns player preferences into queryable structured facts.

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