Ejupi Labs Open-source archive

Ejupi Labs / Open-source product archive

Seven open-source products, one maintained archive.

Public work spanning local AI, machine learning, automation, network tools, numerical methods, operations and consent-based support. Each record provides context, then links directly to the product and source.

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Product archive

Products in the public record.

Each entry states what the product is for, identifies its core technology and provides the two routes needed to evaluate it.

  2. Machine learning

    ELIZA Lab

    An inspectable open-set machine-learning lab for training, calibration and abstention, backed by frozen inputs and reproducible artifacts.

    • Rust
    • Open-set ML
    • Calibration
    Product — ELIZA Lab Source — ELIZA Lab

  4. Network protocol

    DIG

    A bounded Gopher client with a CLI, a local web inspector and a same-origin gateway that keeps selectors, routing and response limits visible.

    • Node.js
    • Gopher
    • Network policy
    Product — DIG Source — DIG

  6. Operations workspace

    VECTOR

    A self-hosted placement operations platform with scoped roles, persistent records, completion controls and an append-only audit trail.

    • Node.js
    • SQLite
    • Operations
    Product — VECTOR Source — VECTOR

Editorial standard

How to read the archive.

The index is intentionally concise. Detail remains close at hand without turning the index into a substitute for the product or code.

01

Product context

Purpose and operating boundaries appear before implementation detail.

02

Direct routes

Product and Source stay visible and consistently placed in every record.

03

Inspectable evidence

Limits, tests and release status remain documented where they can be verified.