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.
Provider-agnostic MCP control plane for managing connections, routing requests, and policy enforcement across AI vendors.
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.
ai-infrastructure-development, ai-application-development etc
End-to-end AI deployment decision system combining real model benchmarking, system-level optimization, and infrastructure-aware trade-off analysis (latency, cost, energy, carbon).
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.
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