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

Description and use

Genrikh is an autonomous AI problem solver that applies the TRIZ ARIZ algorithm with a dual‑loop engine, using local Gemma 2 for privacy and Sentry for traceability, to resolve engineering contradictions at zero marginal cost and 100% IP privacy.

Problem

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

Outcome

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.

Workflow

• 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

Evidence

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.

Source

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

Source

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).

Source