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Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

Limon is a sandbox developed as a research project written in python, which automatically collects, analyzes, and reports on the run time indicators of Linux malware. It allows one to inspect Linux malware before execution, during execution, and after execution (post-mortem analysis) by performing static, dynamic and memory analysis using open source tools

[LIBERO-MAX] A paired benchmark for robot-policy robustness to controlled changes introduced during execution.

RAFCON (RMC advanced flow control) uses hierarchical state machines, featuring concurrent state execution, to represent robot programs. It ships with a graphical user interface supporting the creation of state machines and contains IDE like debugging mechanisms. Alternatively, state machines can programmatically be generated using RAFCON's API.

AI-assisted Windows and Chrome GUI delegation for Codex: task contracts, local execution, Jev semantic decisions, recovery and outcome verification.