Hey everyone 
We’re exploring LangGraph as part of a secure AI orchestration system called Aura — an on-prem, compliance-ready runtime designed for enterprises (currently piloted with banks).
The core idea:
“Meta-orchestration with guardrails.”
Aura simulates, validates, and executes AI workflows under strict governance — every flow is versioned, dual-approved, and reversible.
We’re looking to collaborate with developers who have experience in:
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LangGraph / multi-agent runtime design
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Secure local deployments (no cloud dependencies)
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Building YAML-based flow specs for orchestration
If this overlaps with your interests or your current work, I’d love to share notes, benchmarks, or ideas on improving LangGraph for regulated or privacy-critical settings.
Thanks for the space — this project deeply aligns with LangChain’s mission to make agentic systems reliable and production-ready.
— Eduardo