# ASI \
ASI: Train creates an ecosystem of aggregated open-source foundation models trained and owned by the community. Inference is served by autonomous agents with a cognitive search layer enabling discovery through natural language prompts and data protocols.
ASI: Train’s architecture delivers the following: data pipeline, model quantization, scalable compute, agent-based search and discovery of models. The system implements comprehensive tools for deployment, data provisioning, compute, and finetuning. Fetch.ai agents facilitate ecosystem onboarding for research entities, business data providers, and end users.
ASI: Train integrates Cudos’ infrastructure, Ocean’s data tools, and SingularityNET’s capabilities for model selection and optimization. Fetch.ai delivers agent-based inference. The platform creates workflows, and automates training and inference processes. This allows new services to be composed from multi-agent networks.
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# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.superintelligence.io/artificial-superintelligence-alliance/asi-innovation-stack/asi-less-than-train-greater-than.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.