Private LLM · RAG · NVIDIA GPU Server

Your Intranet ChatGPT: On‑Prem LLM + Enterprise RAG

Biogroup Technology LLC focuses on on‑prem LLM servers and NVIDIA GPU AI servers, helping enterprises build RAG knowledge bases and an intranet ChatGPT.

Secure enterprise knowledge Q&A — data stays in your network.

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Explore Solutions

Browse focused pages for enterprise AI adoption, from on-prem LLM to GPU sizing and security.

On-Prem LLM

Private AI chat on your servers with governance and control.

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Enterprise RAG

Turn internal documents into cited, trusted answers.

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Private Intranet ChatGPT

A ChatGPT-like experience inside your network.

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GPU Sizing Guide

Plan capacity with users, latency targets, and models.

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NVIDIA GPU AI Server

Tiers for pilot, team, and enterprise rollouts.

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Pricing & POC

Clear tiering, timelines, and deliverables.

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Security & Governance

SSO, RBAC, audit logs, and enterprise controls.

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Manufacturing

On-prem RAG for SOPs, maintenance, and quality docs.

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Support Copilot

Faster ticket replies with cited SOPs and KB.

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Sales Copilot

RFP answers and proposals from approved assets.

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Legal Copilot

Clause search, summaries, and risk flags.

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Field Service Copilot

SOP-driven troubleshooting and checklists.

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A Great Starting Point: On‑Prem LLM + Enterprise RAG

Build an internal assistant for documents, SOPs, contracts, manuals, and support knowledge.

On‑Prem AI / LLM Server

Internal Documents → AI Assistant

Semantic search, Q&A, and summaries — knowledge no longer trapped in folders and heads.

NVIDIA GPU

GPU Inference at Scale

Accelerate inference and concurrency for multi‑user, always‑on intranet deployments.

Private AI

Intranet ChatGPT Experience

A practical path to launch enterprise AI for internal Q&A and knowledge workflows.

Common Enterprise Use Cases

Knowledge Base / Document Q&A

Find policies, processes, specs, and procedures faster across departments.

Support / After‑Sales

Draft replies, summarize tickets, and follow SOPs consistently with your knowledge base.

Sales / Content Generation

Organize cases, catalogs, talk tracks — generate proposals and FAQs quickly.

GPU‑Centric On‑Prem AI Server (Summary)

Contact us below for a full BOM and pricing range.

Tier Suggested Configuration (Summary) Best For
A Starter Single Box RTX 4090 24GB ×1 | 128GB RAM | NVMe 4TB | 2.5/10GbE (expandable) SMB teams / POC / trial run
B Standard Plan Dual-box inference / multi-model parallel | dedicated index/files node | 10GbE Multi‑department rollout / concurrency
C Enterprise High‑End 48GB GPU × multi-card | long context | high concurrency | enterprise storage/network Strict requirements / high load

FAQ: On-Prem LLM & Enterprise RAG

It means the model runs inside your infrastructure so prompts and data stay within your environment.

For real-time multi-user chat, GPUs are strongly recommended; CPU-only is suitable only for low throughput.

RAG retrieves relevant internal documents and grounds the LLM response with citations for accuracy.

Access is controlled by SSO/RBAC and per-department knowledge permissions, with audit logs.

A typical POC takes 2-3 weeks, with production hardening in 4-8 weeks depending on scope.

Contact

Share your needs and we will suggest an on‑prem LLM/RAG solution and GPU server configuration.

✉️ service@biogrouptec.com

📞 1-510-806-6488

Recommended: document types/size, user count, intranet requirement, CRM/ticket integration.

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