The AI Retrieval Specifications Bundle defines the foundational systems and components required for building intelligent applications that can discover, retrieve, organize, and apply knowledge. These specifications address critical retrieval capabilities including Retrieval-Augmented Generation (RAG), semantic search, vector similarity matching, knowledge graphs, persistent memory, evidence retrieval, and contextual information management. Together, they provide structured approaches for connecting AI models with reliable knowledge sources while improving accuracy, transparency, and relevance.
Designed for scalable and trustworthy AI architectures, these specifications support applications that require long-term memory, source-grounded responses, legal and technical intelligence, provenance tracking, and multi-agent collaboration. By standardizing retrieval layers and knowledge infrastructure, they enable developers and organizations to build AI systems that can reason over verified information, maintain context, and deliver more dependable results across diverse domains.
All specifications are released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+) and may be used freely with required attribution. Attribution-free deployments require a Specification Branding License, with fees based on usage, scope, and deployment size.
The Open Arsenal specifications are designed as foundations, not disposable products. They define reusable architectures that can be implemented, extended, combined, modified, and adapted to changing technologies and real-world requirements. Modular design allows individual capabilities to evolve without forcing an entire system to be replaced, while vendor-neutral architecture helps preserve independence and interoperability.
Long-term infrastructure requires long-term thinking. Open-source licensing encourages examination, reuse, modification, and collaboration, while perpetual commercial licensing can provide organizations with lasting rights to deploy a specification without making foundational infrastructure dependent on recurring licensing renewals. The objective is to create technological foundations that can remain useful as companies, technologies, platforms, and business models change.
Arq
https://roxanneardary.com/arq/
Architecture intelligence specification that models software systems as living knowledge graphs, enabling structural retrieval and relationship-based knowledge discovery.
AuthorityCore
https://roxanneardary.com/authoritycore/
Governance and reasoning specification that incorporates evidence-constrained retrieval, jurisdiction-aware knowledge retrieval, and human-in-the-loop validation for trustworthy AI systems.
AuthTrace AI
https://roxanneardary.com/authtrace-ai/
Provenance and authorship retrieval specification that identifies content origins, tracks knowledge assets, and enables semantic lineage analysis.
Axis Juris
https://roxanneardary.com/axisjuris/
Legal knowledge graph specification for retrieving and analyzing statutes, regulations, case law, and legal relationships through structured knowledge retrieval.
Cognitive Orchestration Stack (COS)
https://roxanneardary.com/cognitive-orchestration-stack/
Multi-agent cognitive architecture specification that combines memory systems, contextual retrieval, and reasoning layers to support long-horizon intelligent workflows.
CommonGrid
https://roxanneardary.com/commongrid/
Open data retrieval specification that transforms web content into structured datasets and enables discovery and composition of repositories using open-source knowledge retrieval.
LatticeOS
https://roxanneardary.com/latticeos/
Multi-agent orchestration specification featuring integrated memory, contextual retrieval, and knowledge management layers for coordinated AI systems.
LexChangeFeed
https://roxanneardary.com/lexchangefeed/
Real-time legal intelligence and retrieval specification that tracks legislative and regulatory changes and delivers searchable legal knowledge updates.
LexCrosscheck
https://roxanneardary.com/lexcrosscheck/
LexCrosscheck is an open source legal research and retrieval specification designed to improve citation accuracy, source verification, and jurisdictional analysis. It provides a structured framework for human-reviewed legal research, conflict detection, case analysis, and source-grounded legal writing.
LicenseTrace
https://roxanneardary.com/licensetrace/
Semantic provenance and knowledge asset retrieval specification for tracking licensing information, content lineage, and attribution histories.
MindCache
https://roxanneardary.com/mindcache/
Persistent multi-agent memory and retrieval specification for long-term state management, snippet retrieval, versioned memory, semantic search, and collaborative intelligence using structured and vector-based retrieval systems.
PublicStack AI
https://roxanneardary.com/publicstackai/
Public knowledge retrieval and repository intelligence specification that aggregates, structures, and retrieves information from open-source ecosystems and public data sources.
RAGBase
https://roxanneardary.com/ragbase/
Schema-enforced infrastructure specification for Retrieval-Augmented Generation (RAG) systems, supporting modular retrieval components including chunking strategies, embedding models, vector databases, and retrieval pipelines.
SynapCache
https://roxanneardary.com/synapcache/
Context-aware caching and retrieval specification featuring semantic search, vector similarity matching, memory indexing, and intelligent context retrieval for AI applications.
VeritasCode
https://roxanneardary.com/veritascode/
Retrieval-first legal intelligence specification designed for evidence-based legal analysis, statutory retrieval, conflict identification, and source-grounded reasoning.
VoxPersona
https://roxanneardary.com/voxpersona/
Retrieval-based intelligence specification that searches approved knowledge bases and content repositories, extracts relevant information, and generates source-grounded responses across multiple content formats.
A Specification Branding License can be purchased for the basket of AI Retrieval Specs
Purchasing a Specification Basket grants the purchaser a perpetual license for attribution-free use of every existing specification included within that category, as well as any additional specifications subsequently added to the category.
AI Retrieval Specification Basket Pricing:
| Network Size | # of Users | One-Time Price | Duration |
| Small | 1 – 20 | $90,000 | Perpetual License |
| Medium | 21- 1000 | $170,000 | Perpetual License |
| Large | 1001 + | Custom Quote | Custom Quote |
