> For the complete documentation index, see [llms.txt](https://hero-5.gitbook.io/hero-paper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://hero-5.gitbook.io/hero-paper/tech-stack/apta-technical-report.md).

# Apta Technical Report

* **Purpose of APTA**: APTA is a conversational AI architecture that is being used as the foundation to build an AI assistant tailored for the crypto domain, designed to provide accurate, insightful, and up-to-date responses by combining market data, fundamental knowledge, and recent media articles.
* **Technology**: APTA's architecture, known as preemptive agentic flow, bridges LLMs with bespoke AI models or "experts," including retrieval-augmented systems, to address common LLM limitations like outdated information and limited reasoning. To reduce latency for complex queries, APTA anticipates system use cases and pre-computes complex intermediaries, enabling rapid delivery of advanced analytics while preserving a seamless user experience.
* **Query Reformulation**: APTA reformulates user queries by considering both the current request and conversation history, ensuring context-aware, accurate responses.
* **Expert Selection**: APTA routes user queries to specific expert systems tailored to the task at hand, ensuring specialized and precise answers, particularly in areas requiring domain expertise.
* **Modular Response Framework**: The system combines input from multiple experts and presents a cohesive, synthesized response to the user, leveraging different AI modules and experts simultaneously.

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Apta technical report
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