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Manufacturing, textiles

A weaving factory got its own software and live data from every machine

A textile weaving company, a leader in its segment, running five separate, outdated software products (ERP, machine management and more) with no live monitoring of its machines.

Scale
5 legacy products replaced by 1 custom platform, every machine, real-time sensors
Engagement
First prototype in 2 weeks, full solution delivered in 3 months

The challenge

The company ran five separate, outdated products for ERP, machine management and the rest of the business, and did not know it could have software of its own. It learned about machine problems only when production stopped.

The factory ran five separate, outdated products for ERP, machine management and the rest of the business, and only learned about machine problems when production stopped. A working prototype took two weeks, which showed management that software built for the factory was within reach, and the full solution was delivered in three months.

Raspberry Pi computers on the weaving machines read temperature, humidity and vibration sensors in real time, housed in custom industrial enclosures with custom electronics installed on each machine. The readings feed live dashboards and alerts, and the five legacy products became one platform the company owns. The result was millions of dollars saved in software and production costs within a single year.

What our team delivered

  • Replaced all five legacy products (ERP, machine management and the rest) with one custom platform the company owns
  • Integrated the weaving machines with Raspberry Pi computers for real-time monitoring of every sensor
  • Temperature, humidity and vibration sensing on the machines, feeding live dashboards and alerts
  • Custom industrial-grade enclosures for the hardware, and custom electronic installation on each machine
  • Factory automation built on that live data, with the software updated as new needs arose
  • A working prototype in two weeks; the complete solution designed, built and delivered in three months

Result

Millions of dollars saved in software and production costs within a single year, and custom software the company owns outright.

Incidents resolved five times faster

Mean time to resolve (MTTR) for incidents, by quarter, for a 250‑seat organisation. The first four quarters are an in-house on-call rota; the last four are under a managed service with a 24/7 operations centre, runbooks and monitoring. Illustrative figures.

Incidents resolved five times fasterBar chart of mean time to resolve incidents in hours, by quarter. Year 1, in-house: 9.5, 10.2, 9.1, 9.8. Year 2, managed service: 5.1, 3.2, 2.4, 1.9. Average 9.7 hours before, 1.9 hours in the last quarter, 80 percent lower.Mean time to resolve, hoursIn-house on-callManaged service04812hours9.5 hQ110.2 hQ29.1 hQ39.8 hQ45.1 hQ13.2 hQ22.4 hQ31.9 hQ4Year 1Year 2Managed service starts9.7 h → 1.9 h80% lower MTTR

Super Intelligence data flow

Every request is classified by sensitivity, so confidential data stays on models inside your walls while routine work can use the best frontier AI.

Super Intelligence data flowEmail, documents, phone calls, ERP and CRM records and sensor data enter a secure gateway that classifies each request by sensitivity. Sensitive requests are answered by local models inside the firewall, internal ones by a private cloud, and general ones by frontier models from leading US AI labs. Results flow back into ERP, CRM, dashboards and to people.SOURCESGATEWAYMODEL TIERSYOUR SYSTEMSEmailDocumentsPhone callsERP / CRMSensorsSecuregatewaysorts bysensitivityLocal modelsIn your firewallPrivate cloudYour own tenantFrontier modelsleading US AI labsERPCRMDashboardsPeopleSensitive: stays localInternal: private cloudGeneral: frontier model

Automated data entry

Bots read invoices, forms and emails, check every field, and post clean records to your books, with a person reviewing only the uncertain cases.

Automated data entryInvoices, forms and emails are picked up by three bots working in parallel. Each bot reads the document and extracts its fields one by one, a validation step checks them against business rules, low-confidence items go to a person for review, and approved records are posted to the ERP and accounting system. Manual keying shrinks as the bots take over.INCOMINGBOTS EXTRACTCHECKPOSTEDInvoices, formsand emailsBot 1Bot 2Bot 3Validaterules andconfidenceERP / ledgerauto-postedHuman reviewlow confidenceDOCUMENTS POSTEDNo typing.1,201234567890123456789Manual keyingBots

Frequently asked questions

Direct answers to the questions we hear most. Something else on your mind?

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How do the machines report their condition?

The weaving machines were integrated with Raspberry Pi computers for real-time monitoring of every sensor. Temperature, humidity and vibration sensing feeds live dashboards and alerts. Before this, the company learned about machine problems only when production stopped.

What did the custom platform replace?

It replaced five separate, outdated products for ERP, machine management and the rest of the business with one platform the company owns outright. Factory automation is built on the live data and updated as new needs arise.

How long did it take?

A working prototype was ready in two weeks, and the complete solution was designed, built and delivered in three months. The hardware included custom industrial-grade enclosures and custom electronic installation on each machine.

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