ZeroSweep: TypeSafe Jev Triage Engine & Benchmark
An autonomous triage engine and benchmark powered by TypeSafe AI's Jev System One model, demonstrating high-speed email classification with calibrated confidence.
OPEN SOURCE · CURATED REPOSITORIES
Curated Jev SDKs, tools, demos, integrations, benchmarks, and research projects. Repository metrics come from GitHub; titles, summaries, and categories are editorial.
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An autonomous triage engine and benchmark powered by TypeSafe AI's Jev System One model, demonstrating high-speed email classification with calibrated confidence.
Independent benchmark data comparing TypeSafe AI's Jev (System One model) against LLMs on decision score, accuracy, calibration, cost, and latency for typed tasks.
Benchmarks Jev (typesafe/jev-1.13) via OpenRouter's decisions endpoint, measuring typed decision cost, latency, and accuracy on 100 support tickets against Claude, GPT, and Gemini.
JevDash is a Pygame-based 2D platformer benchmark that evaluates TypeSafe AI's Jev model in real-time control scenarios, with Vercel AI Gateway integration.
A reproducible Tetris decision benchmark that calls TypeSafe Jev / System One and Claude Haiku on identical boards, demonstrating Jev Choice integration via Vercel AI Gateway or the TypeSafe API.
Real-world benchmark of TypeSafe's Jev for robot fleets and edge hardware, with 300 measured API calls, cost analysis, and reproducible scripts.
Pre-registered benchmark testing whether TypeSafe Jev's confidence scores reliably decide search, evidence, and citation support for a 2B local model; includes harness, audit tool, and open end-to-end results.
A free RAG reranking and decision-layer benchmark for TypeSafe Jev 1.13, using frozen candidate pools, paired bootstrap CIs, and calibration, comparing against NVIDIA cross-encoder and no-reranking baselines.
This project builds small multimodal models for direct decisions and benchmarks them against TypeSafe Jev and Laya in its model card.
First independent head-to-head benchmark of System One decision models Laya and Jev on byte-identical inputs, reporting accuracy, ECE, gating, and latency.
Local benchmark comparing TypeSafe Jev and Laya-MLX for structured issue classification. Uses the Jev API with Noul scores.
Reproducible benchmark evaluating Jev as a semantic prior for intracortical inner-speech BCI decoding. Reports Jev's input-efficiency signal in synthetic interactions and neural decoding limits on public data.