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Private AI for small businesses, from setups people actually run.

A filterable database of real, sourced self-hosted AI builds: the hardware, the software stack, the models, what works, what doesn't, and how to start. Keep client data on your own machines.

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Fresh private and local AI news for small businesses, checked daily. Every item links to its source.

Latest stable versions (checked Oct 17, 2026): Ollama v0.40.5, Open WebUI v0.12.3, AnythingLLM v1.18.0

Showing 30 of 30 setups

Documented build

Mac Studio M2 Max (64GB) as a private coding assistant

A freelancer working on client code ran a fully local stack for 3 months: Ollama + Qwen2.5-Coder-32B via Continue.dev, with Open WebUI for longer chats.

SoloCoding$3k+Sensitivity: High

Source: r/LocalLLaMA

Documented build

Headless Ubuntu box with RTX 3090 serving code completion to laptops

A developer runs Ollama on a headless Ubuntu desktop with an RTX 3090 and connects laptops via the Continue VS Code plugin. The 32B model was too heavy in practice, so 7B is used.

Solo2-10 peopleCoding$1k-3kSensitivity: High

Source: Arul Selvam Periyasamy (blog)

Field report (bug thread)

Keeping Continue + Qwen 7B within VRAM on Ubuntu

A GitHub issue documents that Continue used ~9.5GB VRAM vs ~6GB for the same model in the Ollama CLI, fixed by lowering contextLength and maxTokens.

Solo2-10 peopleCodingUse existing hardwareSensitivity: Standard

Source: GitHub continuedev/continue #6609

Documented build

Mac mini M4 (16GB) personal RAG assistant reachable from your phone

AnythingLLM + Ollama (llama3.1:8b) on a Mac mini M4, exposed through a Cloudflare Tunnel protected by Cloudflare Access, queried from Telegram via n8n.

SoloDocument search / chat with filesUnder $1kSensitivity: Standard

Source: Ovidiu Eftimie (Substack)

Tested workflow

Starter document Q&A on one computer (AnythingLLM + Qwen2.5 3B)

A careful workflow for chatting with documents on a single machine, including a hallucination test (ask a question the document can't answer).

SoloDocument search / chat with filesUse existing hardwareSensitivity: High

Source: localai.computer

Official recipe

IBM Granite + AnythingLLM local RAG on a laptop

IBM's Granite community recipe for running a basic local RAG over a PDF (e.g. a budget document) on your laptop.

Solo2-10 peopleDocument search / chat with filesUse existing hardwareSensitivity: High

Source: IBM Granite Community (GitHub)

Guide (recommended spec)

Law office bookshelf server: Mac mini M4 Pro 48GB + AnythingLLM per matter

A local legal stack guide: a silent Mac mini M4 Pro with 48GB unified memory running Ollama with one AnythingLLM workspace per matter, plus encryption and a written AI policy.

Solo2-10 peopleDocument search / chat with filesWriting assistant$1k-3kSensitivity: Very high

Source: runlocalai.co

Community discussion

4-person litigation firm weighing a Mac Studio M3 Ultra

A 1-attorney/1-paralegal/2-admin firm asked if a Mac Studio M3 Ultra could handle file sorting and first-pass record review. Replies say hardware is the easy part; PDF/OCR ingestion and guardrails are the real work.

2-10 peopleDocument search / chat with files$3k+Sensitivity: Very high

Source: r/LocalLLM

Documented build

RTX 3060 server: private call transcription with faster-whisper

Audio uploaded from a phone PWA is transcribed on a local RTX 3060 (12GB) with faster-whisper int8, sharing the card with an embedding model and Gemma.

Solo2-10 peopleTranscriptionUnder $1kSensitivity: High

Source: DEV Community (hannune)

Open-source project

Central GPU Whisper API for a small team (Docker)

whisper_api offloads transcription to one GPU server shared by several people; the author suggests the RTX 3060 12GB as the cheapest option for high-quality models.

2-10 people11-50 peopleTranscriptionUnder $1kSensitivity: High

Source: MayNiklas/whisper_api (GitHub)

Documented build (video)

Proxmox + NVIDIA A4000 'AI Basecamp' reachable anywhere via Tailscale

Tailscale's Alex Kretzschmar passes an NVIDIA A4000 through to a NixOS VM on Proxmox, runs Ollama + Open WebUI in Docker, and exposes it privately with Tailscale Serve (TLS, no reverse proxy).

Solo2-10 peopleWriting assistantCodingDocument search / chat with files$1k-3kSensitivity: High

Source: Tailscale blog

Company case study

Customer support bot over company docs (Open WebUI + Llama 3 8B)

Hosting provider HOSTKEY built a tech-support assistant for its front-line team: cleaned Markdown docs, Open WebUI RAG (ChromaDB), a custom model with a strict system prompt.

11-50 peopleCustomer supportDocument search / chat with filesUnder $1kSensitivity: Standard

Source: HOSTKEY blog

Community advice

Startup moving off OpenAI API: used dual RTX 3090 build

A small startup asked for the cheapest way to self-host; a top suggestion was to buy used and build around 2x 24GB RTX 3090s for a 32B model.

2-10 peopleCustomer supportWriting assistant$1k-3kSensitivity: High

Source: r/ollama

Open-source project

~50-user team AI stack on one RTX A6000 (vLLM + LiteLLM + Open WebUI)

An administrator guide for a self-hosted team platform: vLLM serves Gemma 4 31B on a single 48GB RTX A6000, LiteLLM handles keys and rate limits, Open WebUI is the chat/RAG front end, with PII redaction and monitoring.

11-50 peopleDocument search / chat with filesWriting assistantCoding$3k+Sensitivity: High

Source: GitHub

Community discussion

40-person company: 2x RTX PRO 6000 Blackwell server as an internal ChatGPT replacement

A commenter describes their 40-user company setup: a Gigabyte 2U server with two RTX 6000 Blackwell cards running Qwen 3.6 27B behind Open WebUI connected to Active Directory, plus coding, meeting-transcription and contract-RAG add-ons.

11-50 peopleWriting assistantCodingTranscriptionDocument search / chat with files$3k+Sensitivity: High

Source: r/LocalLLaMA

Community discussion

Employee LLM server on ~6x RTX 3090 with Open WebUI + LDAP

A business owner plans an on-prem LLM server for employees on a machine with about six RTX 3090s: Ollama, Open WebUI with LDAP logins, nginx for HTTPS, and a token-protected API for internal developers. Main open question: per-department knowledge-base access.

11-50 peopleDocument search / chat with filesWriting assistant$3k+Sensitivity: Very high

Source: r/OpenWebUI

Company case study

Dev agency tests on-prem AI assistant on Framework Desktop (Ollama + Vulkan)

Kalmia, a software company, runs LLMs on a Framework Desktop (Ryzen AI Max+ 395, 128GB) and found Ollama with the Vulkan backend the most stable option; ROCm and vLLM were not yet reliable on this APU.

2-10 people11-50 peopleDocument search / chat with filesCustomer support$1k-3kSensitivity: High

Source: Kalmia blog

Step-by-step build

Strix Halo (Ryzen AI Max+ 395, 128GB) on Ubuntu with ROCm + llama.cpp: full guide

A complete Ubuntu guide for Ryzen AI Max+ 395 machines (Framework Desktop, GMKtec EVO-X2): BIOS, kernel, ROCm via prebuilt toolbox containers, and llama.cpp with full offload, making ~115-120GB available for models.

Solo2-10 peopleWriting assistantCodingDocument search / chat with files$3k+Sensitivity: High

Source: GitHub

Tested guide

Mac Studio M3 Ultra (512GB) running DeepSeek V3 671B locally

Hardware Corner benchmarked DeepSeek-V3-0324 (4-bit, MLX) on a 512GB M3 Ultra Mac Studio: ~21 tok/s at tiny context, falling to ~5.8 tok/s at ~16K tokens, with 466GB peak memory.

Solo2-10 peopleDocument search / chat with filesWriting assistant$3k+Sensitivity: Very high

Source: Hardware Corner

Tested guide

NVIDIA DGX Spark with Ollama: official performance numbers

Ollama tested the DGX Spark (GB10, 128GB unified memory) on release firmware: gpt-oss 20B at ~58 tok/s and gpt-oss 120B at ~41 tok/s decode, while dense 70B q4 managed ~4.4 tok/s.

Solo2-10 peopleCodingWriting assistantDocument search / chat with files$3k+Sensitivity: High

Source: Ollama blog

Tested guide

RTX 5090 (32GB) server with Ollama + Open WebUI, benchmarked vs RTX 4090

HOSTKEY swapped a 4090 for an RTX 5090 in an i9-14900K / 128GB server running Ollama and Open WebUI. Gemma3 27B ran at 48 tok/s on the 5090 vs 7 tok/s on the 4090, which spilled to CPU.

2-10 peopleCodingWriting assistantDocument search / chat with files$3k+Sensitivity: High

Source: Hugging Face blog (HOSTKEY)

Open-source project

Private writing assistant inside LibreOffice Writer (Ollama)

An open-source LibreOffice Writer extension that sends selected text to a local Ollama or LM Studio server to rewrite, summarize, fix grammar, translate or continue writing, with an editable preview before applying.

Solo2-10 peopleWriting assistantUse existing hardwareSensitivity: High

Source: GitHub

Open-source project

Fully local Obsidian writing + notes assistant (Vault Brain, Gemma 4 on Ollama)

An Obsidian plugin that runs every AI feature against local Ollama: chat with your vault, semantic search, voice memo to structured notes, and selection actions like Improve, Fix grammar and Summarize.

SoloWriting assistantDocument search / chat with filesTranscriptionUse existing hardwareSensitivity: High

Source: GitHub

Step-by-step build

Customer support chatbot on a $15-25/month VPS (Ollama + n8n)

A small-business guide to a self-hosted support bot: Ollama with Llama 3.2 3B answers from an FAQ knowledge base inside an n8n workflow, escalates to a human when unsure, and works from a web widget or support inbox.

Solo2-10 peopleCustomer supportUnder $1kSensitivity: Standard

Source: ARDOT Consulting blog

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