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Goals

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Goals​

The Decision Intelligence Agent implementation is designed to achieve the following objectives:

  • RESTful API Interface: Provide /simulate, /analyze, /overview, and /history endpoints that enable external systems and users to interact with DIA's decision-making capabilities. These endpoints serve as the primary interface for requesting simulations, querying analysis results, viewing system overview, and accessing historical decision records. See the API Endpoints documentation for detailed endpoint specifications.

  • Event-Driven Architecture: Subscribe to Kafka topics for model events and training results, enabling DIA to react in real-time to changes in the system. This asynchronous event processing allows DIA to maintain situational awareness without blocking operations or requiring constant polling.

  • Persistent Decision Storage: Persist decisions and simulation outputs to Postgres for structured querying and to S3 for raw logs and audit trails. This dual-storage approach ensures both operational efficiency (Postgres for fast queries) and compliance requirements (S3 for immutable audit logs).

  • Semantic Memory: Store embeddings in Chroma / Pinecone for similarity-based recall, enabling DIA to find relevant historical decisions and patterns based on semantic similarity rather than exact keyword matches. This allows the system to learn from past experiences and apply similar reasoning to new scenarios.

  • Governance Integration: Integrate with GA (Governance Agent) for validation and to attach policy tokens to decision records. This ensures all decisions comply with organizational policies and provides an audit trail linking decisions to specific governance rules.