
freederia
RAG-ready research records for AI agents
8 followers
RAG-ready research records for AI agents
8 followers
Freederia is a large-scale synthetic research archive and x402 API for AI agents, RAG builders, and technical-intelligence workflows. Search public metadata, preview free HTML records, then retrieve complete structured JSON packages—record, manifest, quality report, ontology graph, sources, and ledger files—through paid API access.



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Framer AI AgentsDesign and publish professional sites with AI
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Freederia is a structured synthetic research archive and paid API for AI agents, RAG builders, search systems, and technical-intelligence workflows.
Each Freederia record is designed as a machine-readable research package, not just a plain article. A package may include record.json, manifest.json, quality.json, ontology.json, ledger events, source or basis files, Markdown/HTML bodies, evidence boundaries, failure boundaries, validation roadmaps, critical variables, and ontology nodes and edges.
The workflow is simple:
Discover public metadata
→ select relevant records
→ retrieve full structured JSON packages through official API routes
Public pages and catalog metadata are used for discovery, preview, search indexing, and candidate selection. Full machine-scale package retrieval is handled through paid API access, including x402 and RapidAPI where applicable.
Freederia is useful for RAG ingestion testing, AI-agent retrieval evaluation, ontology construction, research-data pipeline testing, technical-intelligence extraction, validation-roadmap analysis, and metadata-to-package retrieval workflows.
Most records should be treated as synthetic exploratory research seeds, source-traceable research scaffolds, problem-anchored technical records, or technical-intelligence planning artifacts. They are not independent empirical proof unless explicitly marked as verified.
Core links:
Archive: https://freederia.com/
Explore: https://freederia.com/explore/
API Access: https://freederia.com/api-access/
llms.txt: https://freederia.com/llms.txt
llms-full.txt: https://freederia.com/llms-full.txt
Catalog: https://freederia.com/catalog/index.json
Agent API: https://agents.freederia.com/
Direct API: https://api.freederia.com/
RapidAPI: https://rapidapi.com/freederia/api/freederia-research-data-api
Example metadata search:
https://agents.freederia.com/v1/catalog/search?q=aerospace&limit=20
Example paid package route:
https://agents.freederia.com/v1/package?prefix={r2_record_prefix}
Example sample pack route:
https://agents.freederia.com/v1/sample-pack?include=all_json_package_files&limit=100
Freederia is built for developers and agents that need structured research-like material for retrieval, grounding, ontology workflows, and downstream reasoning tests.
GPT-4o
Whoa, this is actually kinda genius imo! The focus on *structured* knowledge for training next-gen AI – not just throwing more data at the problem – is so smart. Ngl, that's truely the future, right? So, how's the data structured exactly? Like, what kind of blueprints are we talking about here?