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Research pipeline testing whether TypeSafe's Jev (via Vercel AI Gateway) can judge news and market data fast enough to matter. Bitcoin and US stocks, paper trading only.
Evaluation & benchmarks — page 13
Evaluation harnesses, benchmarks and graders. Jev scores or chooses between candidate outputs with an explicit rubric.
320 active projects match this task, ordered by traction.
Evaluate Jev (TypeSafe AI) on Japanese customer-inquiry data: 150-item dataset + comparison script (Jev / LLM / rule-based)
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Experiments with TypeSafe's Jev: triage benchmark vs LLM, and a source study of jev-ultrafast vs Cline's jev-browser
Triage de leads de WhatsApp/CRM con Jev (TypeSafe AI): ruteo por confianza, plantilla n8n y benchmark en español. Sin dependencias. No afiliado.
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Test harness + benchmark for TypeSafe's Jev decision model (noul/choice/score) via OpenRouter's Decisions API
Reproducible Tetris decision benchmark comparing TypeSafe Jev with Claude Haiku
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Probabilistic judgment. Deterministic execution.
Jev-native LLM output judge kit (skill + agents + core)
A writing editor that re-scores 15 typed rubric dimensions on every typing pause — one Jev System One call per pause, ~$0.000004 each.
Meridian | AI context-intake and contraction risk & compliance micro-app with live TypeSafe AI vs OpenAI evaluation
Benchmark for Pi skill routing: BM25 vs TypeSafe Jev across roster sizes 50–500
No project description available.
Typed questions to a model, verdict in code, thresholds from your labels
GitHub Action for agent-written PRs: one comment that says what the PR really does, which hunks need a human, why, and what to verify. About a cent per PR, on TypeSafe Jev.
Early-access test of TypeSafe's Jev on 24 Norwegian hearing responses, next to DeepSeek V4.1 Flash
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Claude Code skill: swap System 2 LLM pipeline components for System 1 TypeSafe Jev decisions via investigation, live three-arm eval, fallback, and an independent judge
Local-first skill router for coding agents. Inspired by TypeSafe Jev; optional swappable judge (not an official Jev product).
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High-concurrency Elixir actor runtime for large-scale semantic graphs, search swarms, and batched model evaluation.
Synthetic smoking-history extraction benchmark comparing TypeSafe Jev and OpenAI structured outputs, with reproducible accuracy, cost, and latency results.
Automation Anywhere custom package wrapping the TypeSafe (Jev) API for typed yes/no, categorical, and scored-scale text evaluation.
Sandbox & benchmark: optimize how you ask Jev (TypeSafe System One) to play falling-block puzzle games, head-to-head against LLMs
Binary LLM-judge bench — compare Jev (TypeSafe System One) against a frontier LLM judge on speed, cost, and agreement with human labels.
Portable benchmark for LLM tier routing, factual-claim verification, and safe interim messages
Smoke test: route prompts to a work or life database with TypeSafe AI (Jev), 30-case eval