AI purchasing agent: material ordered from incoming enquiries
For each new enquiry it works out what material is missing, asks suppliers, reads their quotes and prepares the order. A buyer confirms it.
Estimating, purchasing and scheduling sit with the few people who know how the shop really runs. We build systems that take the repeatable part off their desk – from pricing a drawing to ordering the material.
Fig. 03 – Metal products & metalworkingWhat's changing
The pressures we hear from machining, sheet metal and welding shops, whatever the machine list looks like.
Every inquiry needs an estimator who also runs the shop. Deals are lost to whoever answers first, not to whoever is cheapest.
Machine load becomes visible when the week has already gone wrong, and promised dates were set before anyone checked.
In small batches it is setup time, nesting and offcuts that decide the margin – not how fast the spindle turns.
Similar parts are quoted from scratch because finding what was made two years ago takes longer than re-estimating it.
Across the value chain
We work wherever the data already exists. Most shops start at one stage and extend once it pays for itself.
A price from a drawing set in minutes, not days.
Routings and programs reused from what the shop has already made.
Dates promised against the machines and people you actually have.
Measurement results that feed back into setup instead of into a folder.
Material, outsourcing and offcuts decided on data rather than habit.
Selected systems
For each new enquiry it works out what material is missing, asks suppliers, reads their quotes and prepares the order. A buyer confirms it.
Reads the drawing set, proposes operations and times, and hands the estimator a costed draft.
Schedules built from real machine load and material availability, updated when the day changes.
Counting and checking parts at the machine, with results kept per job.
AI-Technolog and the AI purchasing agent are built into the systems we deliver for metalworking firms.
Contact
Thirty minutes with a founder. No pitch – a conversation about your process, your data and whether a system would pay for itself.
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