Memoars vs TensorSharp

Memoars is a user-owned, encrypted memory layer that carries approved context across AI assistants while keeping you in control of what is learned, changed, and forgotten.

TensorSharp is a native .NET GGUF inference engine with a CLI, Web UI, compatible APIs, Agent Skills, and optional sandboxed model-authored code.

About Memoars

Memoars is a user-owned, encrypted memory layer that carries approved context across AI assistants while keeping you in control of what is learned, changed, and forgotten. Only encrypted memory content is written to your bucket. Memory content is ciphertext, while organization, workspace, identity, grant, version, usage, transcript, and proposal metadata may be visible to the coordinator. On an opt-in run, the dreamer will review this lifecycle and propose what to keep, update or merge. Running memoars against your own bucket is free and complete: one agent, one machine, fully encrypted.

About TensorSharp

TensorSharp is a native .NET GGUF inference engine with a CLI, Web UI, compatible APIs, Agent Skills, and optional sandboxed model-authored code. TensorSharp Wiki, Local GGUF inference and agentic work for .NET Skip to content. Everything runs on your own hardware : your laptop, workstation, or server. Inference and agent work stay local by default, there are no per-token fees, and the same engine powers a quick command-line test, a shared internal chatbot, and a production REST endpoint.