MEDIA PREVIEW
Overview & Result
JEV is insanely fast. We gave it a massive dataset based on thousands of outreach messages and asked: Which intent signals generated the most booked demos? 40 seconds later, we had the answer. Cost: less than $0.20. JEV can also rank leads, measure prospect-message fit, and uncover what actually drives campaign performance. Coming soon to @GojiberryAI + MCP.
How Jev fits in the loop
- Ingest real-time application state and relevant contextual parameters
- Format the decision problem as a bounded Choice or Noul schema
- Query Jev to receive a typed probability distribution in sub-50ms
- Execute downstream actions or route tasks according to the winning choice
How to reproduce
- Inspect the original showcase and source material at https://x.com/pierreeliottlal/status/2100912453999587657
- Verify the bounded prompt and input candidate schema configured for Jev
- Benchmark decision latency and classification accuracy against baseline models
Why this build matters
Demonstrates a real-world, cost-effective implementation of Jev in a search & content classification scenario, replacing expensive generative calls with fast typed decisions.
Reported performance
Reported by authorLatency: Sub-50ms deterministic decision window
Performance metrics and decision latency are reported by the original author and community benchmarks.
Limitations
- Task accuracy is bounded by the precision of the defined candidate choices
- Third-party external dependencies and network latency may affect total workflow duration