Custodian Labs vs TensorSharp

from custodian_labs import Custodian model = Custodian( model="gpt-4o", system_prompt="You are a helpful assistant.

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

About Custodian Labs

from custodian_labs import Custodian model = Custodian( model="gpt-4o", system_prompt="You are a helpful assistant. The proprietary Guardian Layer is the guardrail that detects PII and puts you in control of how it's handled before it reaches any model. Give your agent long-term memory and document retrieval without configuring embeddings or vector DBs. Your agent logic stays exactly as it is; only the model underneath changes. No database to provision, no vector store to connect, no hosting to manage.

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.