This project is a C++ mini–AI infrastructure simulation designed to demonstrate core object-oriented and systems-level design patterns commonly used in AI infrastructure, compute backends, and large-scale frameworks.
IntentMesh is an open protocol and reference architecture for structured negotiation between autonomous software agents.
Zero-intrusion guard for LLM calls in dev: dedupe, cache, and protect AI requests across Node, browser, and Vite.
Provider-agnostic MCP control plane for managing connections, routing requests, and policy enforcement across AI vendors.
End-to-end AI deployment decision system combining real model benchmarking, system-level optimization, and infrastructure-aware trade-off analysis (latency, cost, energy, carbon).
ai-infrastructure-development, ai-application-development etc
Workload-scoped runtime enforcement for AI workloads. Deterministic governance at the workload boundary.
Secure Agent Governed Execution OS
Where enterprise storage meets AI infrastructure. IBM, EMC, SAN, NVMe, GenAI, LLM internals — deep dives, simulators, benchmarks. Open forever.
blAIne governance and infrastructure architecture repository containing AI systems, operational frameworks, governance models, validation methodologies, and supporting program structures.
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