Awesome Jev: early projects and use cases
A community-curated list gathers early Jev projects and ideas for developers who already have API access.
xmemory shares its approach to choosing the right model for each step, and reports testing TypeSafe's Jev as a judge for extracted data: it recovered 81% of the accuracy gap while sending only 38% of the data (truncated).
The right model for the right step. That’s how we build memory at xmemory – benchmarking for quality, cost, and latency. We tested @typesafeai's Jev as a judge of extracted data. It recovered 81% of the accuracy gap between a fast and a slow extractor while sending only 38% of