Synaplan
Open-source AI platform for companies: self-hosted AI agents, GDPR-compliant chatbot widget, RAG knowledge base, WhatsApp and Outlook AI, MCP, multi-model routing. Docker, Kubernetes or hosted in Germ
翻訳待ち
Staffbox: an on-site agentic worker on a Mac mini. Open stack: Hermes Agent, Ollama, a Markdown vault, install and benchmark scripts.
翻訳待ち
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Your first agentic worker. One box, on your network, with a brain you own and a score you can check.
Staffbox is an open stack for running an agentic AI worker on a Mac mini inside a small company's own network. It runs an open-source agent on local open-weight models. Its memory is a brain: a plain Markdown vault the company owns and can open in Obsidian. The company's existing IT provider installs and manages the box. The worker goes live on a workflow only after a scorecard on that company's own past requests meets a pass mark agreed in advance.Read the full README ↗Staffbox runs Hermes Agent on local open-weight models on a Mac mini to draft quotes and replies from a company's own price list, and on a 16 GB Mac mini it scored 351 of 360 messy generated requests with 0 wrong totals in 475 graded answers.
The proof, all on fictional demo companies and graded by machine (no customer site has run it yet):
qwen3:8b with the brain and quote action v2.4, 6 October 2026: Fieldstone IT 40/40, Peachtree Cabinet Works 39/40, messy requests 19/20 and 15/15, generated requests 351/360. Of the 11 misses, 10 declined and asked the customer and 1 was a routing miss. Files: Fieldstone · Peachtree · messy 20 · messy 15 · generated 204 · generated 156.qwen3:8b scored 1/40 on Fieldstone IT; with the brain and the quote action, 40/40. A cloud model (Gemini Pro) with the same brain matched on clean requests (39/40) but scored 14/20 on messy ones, where the local 8B model with the quote action scored 19/20. Details: Scorecard and evals/results.evals/results/.Staffbox is an open stack for running an agentic AI worker on a Mac mini inside a small company's own network. It runs an open-source agent on local open-weight models. Its memory is a brain: a plain Markdown vault the company owns and can open in Obsidian. The company's existing IT provider installs and manages the box. The worker goes live on a workflow only after a scorecard on that company's own past requests meets a pass mark agreed in advance. It writes drafts only: there is no sending code, and a person sends.
This repository is the stack. The managed service, the hardware program and the partner channel are what Staffbox, Inc. sells around it.
git clone https://github.com/Staffbox-ai/staffbox && cd staffbox
bin/staffbox check examples/peachtree-cabinet-works/vault # is the brain healthy?
bin/staffbox context examples/peachtree-cabinet-works/vault "How long does a painted order take?" # what the worker reads
bin/staffbox quote examples/peachtree-cabinet-works/vault "30 shaker doors 24x30 in maple, painted" # the quote action, no model
bin/staffbox ask examples/fieldstone-it/vault "A user is locked out of MFA. What do we do first?" --model qwen3:8b
bin/staffbox eval examples/fieldstone-it/vault examples/fieldstone-it/tests.jsonl --model qwen3:8b --modes brain,brain+quote
Python 3 standard library only, so there's nothing to install. ask and eval need Ollama running a model.
To install a full unit (Ollama, Hermes Agent, the worker profile and the brain) on a Mac mini, follow docs/install.md. The one command:
xcode-select --install # click Install on the Mac's screen once; about 10 minutes
git clone https://github.com/Staffbox-ai/staffbox ~/staffbox-src && ~/staffbox-src/scripts/install.sh
Two demo brains, both fictional, each with a 40-question test set (16 quotes, 10 policy or runbook questions, 8 emails to route, and 6 questions the brain cannot answer, where the right answer is "not in the vault" plus who to ask):
examples/peachtree-cabinet-works: a Georgia cabinet-door maker. Price list, species and finish surcharges, volume discounts, five policies, three SOPs.examples/fieldstone-it: an IT provider. Hardware price list with setup fees, labor rates, response times, backups, patching, approvals, onboarding, offboarding and MFA runbooks, three client notes with their own rules, and inbox queues.Hermes Agent refuses local model windows below 64K tokens, and Ollama's default window is 4K on machines with less than 24 GiB of GPU memory (Ollama docs). The repo fix is in docs/hermes-64k-context.md. The longer guides on staffbox.ai:
| Guide | What it answers |
|---|---|
| Hermes Agent for business | What Hermes Agent gives and what Staffbox adds |
| Hermes Agent 64K context | qwen3, Ollama and what we know about the 64K minimum |
| Hermes Agent with Ollama | The Ollama settings that worked for us |
| Best local model for Hermes Agent | Local models compared by their scores on quoting |
| Is Hermes Agent safe for company data? | What we turn off, and why |
| Install Hermes Agent on a Mac mini | The Staffbox installer, step by step |
Staffbox is not affiliated with Nous Research. Hermes Agent is Nous Research's open-source project (MIT).
This is the beginning of the README. Read the rest at the original. Read the full README ↗