Jev Lab — Nijal-AI

Jev-inspired PID autotuning repository that applies the typed choice/score/noul interface with calibrated probabilities to Simulink models. Ships a Python CLI with discover, matlab, and doctor commands, a 200 KB numeric head, and explicit abstention. Not affiliated with TypeSafe AI.

A self-hosted server that removes ads from podcasts before you hit play: it transcribes locally with faster-whisper or Parakeet, detects and cuts ad segments with your choice of LLM or System One, and learns sponsors across episodes.

A local deep-research tool that turns your own PDF, DOCX, PPTX, image, TXT, or Markdown files into a structured report, using TypeSafe's Jev to rerank Qdrant chunks and verify evidence coverage while an LLM plans and writes.

An experimental Sutro CLI that evaluates CSV, Parquet, and JSONL data with Jev, asks you to label ambiguous and random audit rows, and uses GEPA to propose improved function definitions.

A Python framework where an authoring LLM writes a task-specific Jev harness, then optionally evolves it using reward reflection and GEPA over full trajectories.

An independent open-source pipeline that gives Jev vision: it detects and tracks objects in images, video, and RGB-D camera feeds, then asks Jev a typed question about each relevant object and prints the chosen answer with its confidence.