llm-token-visualizer 0.2.0

Flag low-confidence spans in LLM output from token logprobs, and render per-token confidence as terminal, HTML or Markdown
Documentation

Sponsors & Partners
Thank you for your interest in supporting the LLM Hallucination Detector project — a next-generation, production-grade framework designed to secure and enhance the reliability of Large Language Models.

Why Sponsor?
Early Mover Advantage: The toolkit has already gained 7+ GitHub stars and hundreds of clones in a short time — an indicator of strong market interest and rapid adoption.

 Strategic Value: Hallucination detection is a critical missing piece in AI safety and deployment, making this project highly relevant for any organization developing or deploying LLM-based products.

⚙Production Ready: Written in Rust, Python, and C++, this framework is designed for scalability, real-time integration, and enterprise deployment.

 Future Roadmap: Plans include advanced neural architectures, multi-language support, live monitoring dashboards, and eventually model & weight releases under controlled licenses.

What We Offer to Sponsors
Early access to private builds, weights, and models not yet publicly released

Customized feature development aligned with your business needs

Co-marketing and branding opportunities with a cutting-edge open-source AI safety project

 Direct input into roadmap and priority features

 Potential for acquisition discussions or exclusive partnerships

Contact
If you are interested in sponsoring, investing, or partnering, please reach out directly:

Matt Busel
Email: mattbusel@gmail.com

Supporters