Launching NKTg AI: Tackling LLM hallucinations with physics-based semantics

Hello Indie Hackers! 👋

I'm excited to share a deep-dive update on NKTg AI (https://nktg.org/), an advanced platform designed to completely eliminate LLM hallucinations and data privacy risks at the architectural level.

Unlike traditional statistical LLMs that rely on probabilities and often fabricate information, NKTg AI is built as a specialized Language Decoding System. It utilizes physical algorithms (AMP/DAMP structural genetic codes and variable inertia algorithms) to measure semantic energy and extract the pure "Core Content" without altering the author's original intent.

To give users maximum flexibility, the platform operates across 3 powerful models tailored for different needs:

1. NKTg AI (Core Engine): Measures semantic energy to extract high-density action sentences (AMP > 55%) or structural conditions (DAMP > 55%) for ultimate analytical objectivity.

2. LLM Local (WebAssembly): Runs 100% client-side directly in your browser. Your data never leaves your device, ensuring zero data leakage, low latency, and full offline capability (requires 16GB+ RAM and WebGPU).

3. LLM Cloud: A zero-cost cloud interface that offloads heavy generation to the cloud, requiring no high-end hardware or model downloads.

Whether you're handling complex legal contracts, financial audits, or deep research, NKTg AI bridges the gap between absolute data integrity and natural AI fluency.

Check out nktg.org, and I'd love to hear your thoughts or connect with fellow founders working on privacy-first AI! 🚀