How Krugle Squad works

Krugle Squad features two modes: one in which you convey objectives to members (AI agents) via chat and entrust them to handle tasks autonomously, and another in which members (AI agents) autonomously execute tasks based on pre-designed blueprints. During execution, they also coordinate autonomously with other members.

Krugle Squad’s Goal
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  Resolving the labor shortage
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  Manage members, skills, tools, and blueprints at the corporate level.

How Krugle Biblio works

Krugle Biblio preprocesses data sources (code and surrounding documentation) to make them readable for LLMs.
It collects these by purpose and creates cross-sectional vector and knowledge indexes within the collections (code and surrounding information).
Agentic RAG analyzes prompts and further searches these embedded indexes to provide answers.

Krugle unique preprocessing and Agentic RAG integration flow

Krugle Biblio is not just an Agentic RAG; it dramatically improves answer accuracy by searching a pre-processed collection (code and surrounding information).

Krugle Biblio’s Goal
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  Leverage unstructured data as AI knowledge!
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  Dramatically reduce the effort required for RAG and prompt tuning!
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  Use it just like an LLM trained on your company’s proprietary data!
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  Convert files that LLMs typically struggle with—such as Excel spreadsheets—into RAG-ready data using proprietary preprocessing!
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  Cross-sectionally link code and surrounding documentation for impact analysis!
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  Easily integrate with applications using industry-standard APIs!