

Highlight 1
Efficient Knowledge Core Creation - TrustGraph's one-time graph building process for reusable knowledge cores significantly reduces redundant work.
Highlight 2
Versatile Integration - The app's compatibility with a range of AI models and APIs broadens its applicability to various use cases.
Highlight 3
Comprehensive Monitoring - The inclusion of a Grafana dashboard for real-time performance monitoring enhances user insights.

Improvement 1
User Documentation - More comprehensive and user-friendly documentation could accelerate onboarding for new users.
Improvement 2
UI/UX Enhancements - The interface could benefit from a more intuitive design to facilitate ease of use for non-technical users.
Improvement 3
Community Engagement - Increased efforts to build community-driven shared knowledge cores could enhance the platform’s utility and collaborative opportunities.
Product Functionality
Consider adding more interactive tutorials or walkthroughs to help users navigate the system more effectively.
UI & UX
Improve the interface design by adopting a more modern aesthetic and enhancing navigation to make it user-friendly.
SEO or Marketing
Optimize the website for search engine visibility by focusing on relevant keywords related to AI infrastructure and knowledge graphs.
MultiLanguage Support
Implement multi-language support to cater to a global audience, enhancing accessibility for non-English speaking users.
- 1
What types of documents can I ingest into TrustGraph?
TrustGraph supports batch ingestion of PDF, TXT, and MD files.
- 2
How does TrustGraph ensure data accuracy?
TrustGraph prioritizes 'accuracy first' AI generation, employing real-time observability and model agnostic approaches to enhance intelligence extraction.
- 3
Can I deploy TrustGraph on my server?
Yes, TrustGraph can be deployed using either Docker or Kubernetes, allowing for flexible deployment on your infrastructure.