Software for manufacturers, traceability without spreadsheets.

Large customers pass traceability and quality obligations down the supply chain. Meeting them with spreadsheets works until an audit, at which point somebody spends a fortnight reconstructing records that should have been produced automatically.

The risk is not only the audit. It is that the contract depends on passing it.

In many manufacturers the process detail lives with one experienced person. That is a continuity risk as much as an efficiency one, and capturing it in software is often justified on succession grounds before productivity is even discussed.

A traceability and quality documentation layer over existing systems sits in the middle of the £8,000 to £30,000 range, because it touches the shop floor and the office. Document reading, where customer specifications and certificates arrive as attachments, is custom AI work at £8,000 to £25,000.

An audit at £2,500 to £6,000 is the sensible first step where an ERP exists, since the practical question is what the ERP is failing to do rather than what to replace it with.

Time to produce a specific traceability record for a job completed months ago. That single number captures both the administrative cost and the audit risk, and it is easy to test today.

Then hours per week spent reformatting data into customer templates, and the number of quality escapes traced to a documentation gap rather than a process failure. The second is uncomfortable to measure and it is where the strongest business case usually sits.

A 30-minute call to hear how the operation runs today, then a paid discovery step: interviews with the people doing the work, a look at the systems and data you already hold, and a ranked list of what would pay back, each with a price, a timeline and the monthly running cost once live. In most manufacturer engagements the first thing built is document intake for orders, specifications and supplier paperwork, so the office stops retyping what the customer already sent, because it is measurable inside a month and it funds the rest.

The build runs in weekly demos against your real inputs, including the messy ones. Integration with the systems you already run comes before anything clever, because that is where most of the value and most of the risk sits. Go-live is followed by handover: the code, the provider accounts and the credentials in your name, a runbook, documentation and a recorded walkthrough, plus a session for the people who will use it daily. Every price is fixed in writing before work starts, with a list of what is not included.

Product safety and conformity marking, health and safety on the shop floor, environmental permits where they apply, and the quality system many customers require all generate records that must be complete and traceable. Software cannot hold the certification, but it can keep the technical file current, log the inspections, chase the supplier declarations and make the traceability record a query rather than a search through folders. Commercial data is often more sensitive than personal data in manufacturing, which is why anything that reads drawings, specifications or pricing runs under a data processing agreement on a business plan and, where a customer requires it, in the UK.

Our published prices apply to every sector: an AI adoption audit at £2,500 to £6,000 fixed, credited in full against any build; a first AI implementation at £4,000 to £15,000; a custom AI system at £8,000 to £25,000; applications at £8,000 to £30,000 per phase; websites at £4,000 to £16,000; training from £1,200. For a manufacturer that usually means order and specification intake as the first implementation, then quoting, scheduling or quality tooling as a custom system, with your ERP or job system kept as the record.

The running cost is stated before go-live, per feature, and it scales with volume rather than headcount. From operating our own AI products, the model is rarely the expensive part; the channels around it, telephony and messaging, usually are, and a well-designed workflow sends most of its work to the small, cheap models. Every system we build reports cost per feature from day one and has spending ceilings that were tested by watching them fire.

A manufacturer’s office spends its day translating what customers send, purchase orders, drawings, emails, into what the job system needs. Document intelligence that reads what arrives and writes it once removes the retyping and the errors that become remakes. Quoting is the second win: a quote assembled from the specification, the material prices and your own history goes out the same day. The shop-floor question, where is job 4127 and when will it ship, answered by a system rather than a walk to the floor, is the third. Machine data and predictive maintenance are real but come after the office work, because the office work pays back sooner.