2 posts about AWS Bedrock by 1 contributor.
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Prompt engineering is a powerful tool, but it is not a panacea. In enterprise tax management, the cost of error is too high to rely on prompts alone. By building a multi-agent system with LangGraph, we can isolate failures: if retrieval is poor, we fix the vector store; if reasoning is weak, we upgrade the model; if compliance is risky, we add guardrails. This architectural approach ensures that our AI copilot is not just smart, but also safe, accurate, and auditable. The next step is to integrate real-time regulatory feeds and rigorous evaluation pipelines to evolve this POC into a production-grade platform.
Choosing LLM inference backends: AWS Bedrock, SageMaker, or K8s. Learn the organizational decision framework and a practical LangGraph implementation.
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