Private LLMs & RAG AI Agents

What it is

Private LLM AI Agents are conversational AI systems built on open-weight or licensed models, deployed entirely within the customer's environment. Retrieval-augmented generation (RAG) grounds responses in your knowledge base, your documents, your data — without exposing that data to a third-party API.

When you'd use it

• Customer support deflection with order-aware or account-aware retrieval
• Internal copilots for compliance, legal, finance, HR, and operations
• Domain expert assistants trained on your documentation, runbooks, or research
• Agentic workflows where the LLM both answers and takes action

Technical depth

The architecture pattern we ship combines:

• Open-weight model (Llama, Mistral, Qwen, or similar) optionally fine-tuned
• Hybrid retrieval: vector search + lexical search + reranking
• Citations and provenance for every generated response
• Guardrails: PII redaction, content safety, refusal policy
• Evaluation harness: factuality, faithfulness, response quality
• Observability: latency, cost, hallucination rate, user feedback signal

Why this matters for regulated industries

Off-the-shelf model APIs are not compatible with HIPAA, FERPA, attorney-client privilege, or air-gapped security operations. Private deployment isn't a nice-to-have; it's the only deployment shape some customers will accept.