Genrikh: Building a $0-Marginal-Cost Universal AI Problem Solver with Gemma 2, Sentry & ElevenLabs

说明与用途

Genrikh 是一款自主 AI 问题解决器，采用 TRIZ ARIZ 算法和双循环引擎，使用本地 Gemma 2 保障隐私，Sentry 进行追踪，帮助团队在零边际成本和 100% 知识产权隐私的前提下解决工程矛盾。

问题

Solo‑founders and small teams face costly trade‑offs in software, hardware, and micro‑SaaS projects, often requiring expensive infrastructure or senior consultants.

结果

Genrikh resolves three benchmark dilemmas—offline mobile invoicing, wearable health sensor, and 10,000 RPS micro‑SaaS launch—without added cloud cost, extending battery life from 8 h to 34 days and achieving 98% edge cache hit rate.

工作流

• 1. Input problem and parameters via CLI or API
• 2. Loop 1: internal ARIZ reasoning (steps 0‑5) with state lock
• 3. Loop 2: progressive disclosure of Layer 1, Layer 2, and Layer 3 outputs
• 4. Generate audio briefing with ElevenLabs
• 5. Deliver report and optional web dashboard

证据

Genrikh is an autonomous, open‑source AI problem solver that brings classical ARIZ algorithmic rigor to modern engineering, hardware, and business systems—with $0 marginal cost and 100% intellectual property privacy.

来源

We created an automated benchmark suite testing Genrikh across three distinct domains… Benchmark Score: 100% contradictions resolved without introducing middle‑ground trade‑offs.

来源

Genrikh uses Google Gemma 2 running locally via Ollama (http://localhost:11434) as its primary intelligence engine… Zero bytes leave the machine (100% air‑gapped, zero IP leakage).

来源