Running TypeSafe AI's Jev Inside Neo4j for Confidence-Aware Sentiment Decisions

This is Part 3 of a series on running sentiment analysis inside Neo4j.

Part 1, Running Sentiment Analysis Inside Neo4j With a Java Plugin, used the VADER lexicon via a pure Java UDF – rule-based, fully local, high throughput.

Part 2, Wasm Inside Neo4j: Building the Example That Didn't Exist, embedded a Wasm runtime inside a Java UDF using wasmtime-java — sandboxed, still local, lower throughput.

Part 3 takes a different approach. Instead of bundling a scoring model inside the plugin JAR, we call TypeSafe AI's Jev from inside a Java UDF. Jev is a System One model – it doesn't generate text. It takes a state (the text to evaluate) and a set of typed questions and returns structured decisions with explicit probability and confidence information. No prompt engineering, no JSON schema coercion, no parsing.