How to build agentic AI when your data can’t leave the network

Companies with strict data privacy requirements can now build AI systems using small language models that run locally instead of sending sensitive information to cloud services like GPT or Claude. By separating different AI tasks across specialized models under 3 billion parameters—using smaller models for classification and larger ones for reasoning—organizations can create secure, on-premise AI assistants that handle confidential documents without data ever leaving their networks.