What we need to see
The questions your team asks repeatedly, source systems and a simple list of who can see or change each record.
Internal AI assistant · Fabricators
Every fabrication shop has the same daily question: where is job X right now? The answer's in the MES, in the production schedule, on the shop floor, on a clipboard, or in someone's head. We built an internal AI assistant for Kingsland that takes the question in plain English, voice or text, and answers from the live data, then lets staff take actions like starting a task, logging a defect, or moving a job stage.
Tell us the task, your current tools and where the work gets stuck. We will help you choose a sensible first scope.

Shop-floor staff are the people closest to the work but furthest from the systems. The MES, the schedule, the customer notes, all on a desk that's nowhere near the bay. They walk over, ask, get a partial answer, go back. Multiply across the day across the team and it's hours of friction. Customer-service staff hit the same wall from the other side: every status query means walking to the shop or pinging someone.
The work in context · Illustrative scenes

Use representative inputs from the business to scope internal ai assistant. Agree what the system prepares and what a person needs to check.

Test normal work, missing information and failures with the team, then hand over clear review steps and practical guidance.
See the business context and the work delivered. Your own scope, inputs and results will depend on the workflow we agree with you.
Explore the delivered workRead-only by default. Write access for specific actions: start/stop a task, move a job stage, log a defect, raise a quality issue. Every write confirms before executing.
Designed for noisy shop floors and bay-side use. Voice-first, big touch targets. Same assistant works on desktop for office staff, different interface, same brain.
The assistant queries the MES when asked, it doesn't cache. "Where's job 1647?" gets the current answer, including the current production stage, who's working on it, and the next scheduled step.
Tuned on your past quotes, jobs, and customer notes. "How do we usually handle that with Acme?" pulls relevant historical context, what we've quoted, what we've delivered, what their preferences are.
We check your software version, available API or export, access permissions and any supplier fees before quoting. If a reliable connection is not available, we will explain the practical alternatives.
The questions your team asks repeatedly, source systems and a simple list of who can see or change each record.
Test useful answers, source accuracy and permission boundaries with real staff before enabling actions.
Start read-only. Require confirmation for agreed changes and retain an audit trail and manual route.
£5,000-£18,000 for build, ~£300-£800/month for hosting + model usage
From £5,000excluding VAT
Internal AI assistant for fabricators
No. ChatGPT plus a system prompt is a chatbot. What we build is connected to your live MES and job data, can take real actions, has audit logs, has role-based permissions, and runs in your environment. Different problem, different solution.
Yes, when it's designed for them. Voice-first, big touch targets, plain-English answers, integrated into the workflow they already follow. The tech is the easy part, the UX is what makes adoption stick.
The assistant only answers from retrieved live data. If it can't find the answer in your MES, it says so. For action-taking, every action confirms before executing, even if the assistant misunderstands, the human has the final say.
Role-based. Operators see job status and can log defects but can't change pricing or schedules. Estimators see customer history and quotes but can't move production stages. Managers see everything. We configure roles to match your real org.
Build is one-off. Ongoing: ~£300-£800/month for hosting and AI model usage at typical shop-floor query volumes. That covers the model API, the hosting, and tuning as your data grows.
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