Adaptive agentic intelligence framework using Strands Agents
aws ·
The Adaptive Agentic Intelligence Framework (AAIF) utilizes Strands Agents to optimize AI processing by routing requests based on complexity rather than sending all queries to a single large model. This architecture employs a small language model, specifically llama3.2:1b, as a local orchestrator to classify tasks and direct them to either local or cloud-based resources. Routine operations, such as retrieving IoT telemetry or analyzing camera feeds, are handled locally via Ollama to ensure low latency and data privacy. Complex analytical tasks requiring broader reasoning are delegated to frontier models hosted on Amazon Bedrock. The framework supports flexible deployment scenarios, including fully cloud-based, hybrid edge-cloud, or air-gapped environments, allowing organizations to balance cost and performance. By keeping approximately 80% of traffic local, AAIF significantly reduces API costs while maintaining efficient response times for standard queries. The implementation also highlights future scalability through Model Context Protocol servers for distributed tool calling. Finally, the authors emphasize integrating responsible AI controls, such as Bedrock Guardrails, across both local and cloud inference paths to ensure safety.
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