Intellyx for Automotive Manufacturing

Yes. Intellyx generates part-level QR traceability records that link production batch data, machine parameters, inspection results, and operator information for every part produced. These records are stored in the platform and can be retrieved and exported on demand during an OEM or third-party audit. The traceability chain covers raw material receipt, production process, quality inspection, and dispatch, which satisfies the core traceability requirement of IATF 16949 Clause 8.5.2. Customers who have used this capability report passing OEM audits that previously identified traceability as a major non-conformance.

Intellyx integrates with ERP systems used by the supplier (SAP, Tally, ERPNext) to pull production and quality data. Direct integration with OEM customer portals (such as the Maruti, Tata, or Mahindra supplier portals) is not currently a standard Intellyx feature. However, the quality and traceability data generated by Intellyx can be exported in standard formats for manual or semi-automated upload to customer portals. If your specific OEM customer portal uses a supported API, Perimattic will assess custom integration feasibility during the scoping phase.

Intellyx is specifically designed for Indian manufacturers who do not have large IT or automation teams. The platform is operated through a simple web dashboard and WhatsApp. No specialised software skills are required from production staff. Perimattic handles the full deployment, configuration, and training as part of the onboarding process. Post-deployment support is available via WhatsApp and phone. Many Intellyx customers are family-owned Tier-2 and Tier-3 suppliers with production teams of 50–500 people. The modular structure means you can start with the one or two modules that address your highest priority problems and expand over time.

Intellyx supports multi-SKU production environments where the same line produces many different part numbers across shifts. OEE targets, Vision QC defect profiles, and production parameters can be configured separately for each product and automatically loaded when a changeover occurs. The system tracks changeover time as a separate OEE Availability loss category, enabling systematic improvement of changeover performance. For Vision QC, separate AI models are trained for each product family, and the active model is switched automatically or by operator selection during changeover.