BeardTrain collects everything your crew does — every question answered, every job stepped through, every document signed — and turns it into a fine-tuned AI that knows your shop. Runs on your hardware. Answers to you.
Scout answers NEC questions. Field logs job steps. Hub transcribes voice. BeardSign processes documents. Every interaction is a training candidate.
When your crew thumbs down a response, Claude-p analyzes why it was wrong, what the correct answer is, and what the model should learn.
Nothing enters the knowledge base without your sign-off. You review Claude's analysis, edit the correct answer if needed, and approve or reject.
Approved corrections feed into ShareGPT JSONL format. Your Qwen3 8B runs a fine-tuning pass on your Mac Mini. The model that comes out knows your trade.
NEC code questions, voltage drop calculations, wire sizing, GFCI requirements, panel sizing. Every chat is a training pair. Auto-logged on every response.
● LiveWhisper-transcribed voice notes, parts lookups, step completions, inspection results. Real field procedures from real jobs, not textbook procedures.
● LiveVoice-to-task conversion, dispatcher interactions, crew approvals. Teaches the model how real intake conversations flow in an electrical contracting shop.
● LiveCertificate of completion language, work order descriptions, scope of work drafts. Trains the model on how trades documents are actually written.
● LiveCommand sequences, error fixes, deployment patterns. The model learns your exact VPS stack — PM2, nginx, SQLite, Node — from real sessions.
● LiveDeal conversations, proposal language, client interactions. Teaches the model the BD side of running an electrical contractor and energy development firm.
● LiveWhen you ask ChatGPT about a job, that conversation leaves your shop. It becomes training data for OpenAI's next model. Your client names, your pricing, your scope of work — none of it is confidential anymore.
BeardTrain is built on the opposite premise. Your data stays on your server. Your model runs on your hardware. When you fine-tune Qwen3 8B on your job history, that model knows things no public AI ever will — because it was trained on information no one else has.
One-time build cost. No monthly AI bill. No data leaving the building.
Any user can thumbs down a response in BeardPowered AI. One tap on the job site.
Claude-p analyzes the Q&A pair: what was wrong, what the correct answer is, what the model should learn. Takes 10–30 seconds. Runs silent.
The BeardTrain dashboard shows you the wrong answer, Claude's analysis, and the proposed correct answer. You can edit before approving.
Approved corrections surface immediately in RAG (future answers get it right now) and queue for the next fine-tuning run (the model learns it permanently).
When enough approved data accumulates, run a fine-tuning pass on Qwen3 8B locally. The model that comes out is smarter than the one that went in.
Claude is the reviewer, not the arbiter. It surfaces what it thinks is wrong and what the correct answer should be. You have the final say — every time.
This matters because NEC code changes, local AHJ interpretations vary, and field practice sometimes differs from what the codebook says. The people who know the difference are your journeymen — not an AI.
The result: a model that knows your trade the way your best journeyman does — because it was trained on your best journeyman's answers, verified by you before they became permanent.
Every question your electricians ask, every job they log, every document they sign — it's all training data for a model that will outperform any general AI on your specific trade. BeardTrain makes that possible without a data science team.
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