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Most industrial operations are running on a Digital Shadow. Their ERP says one thing. Their P&IDs say another. Their O&M manuals haven't been opened since commissioning. Their CMMS hasn't matched reality since the last acquisition. The result: reliability programs stall, SAP S/4HANA migrations derail, digital twin initiatives fail, and AI copilots hallucinate — because the data foundation underneath everything is wrong. Data Renew is the Industrial Data Refinery — an AI-native platform that transforms crude engineering data into high-octane asset intelligence. We do three things: Cleanse — Standardise and deduplicate material and asset master data to ISO 14224, UNSPSC, and PIDX. Eliminate the duplicates, ghost assets, and unclassified records that block every downstream initiative. Build — Extract asset hierarchies, bills of materials, and maintenance strategies directly from engineering documents: P&IDs, SLDs, O&M manuals, datasheets, calibration certificates. Turn the PDF Graveyard into structured, CMMS-ready intelligence. Reconcile — Compare your ERP/CMMS data against engineering source documents. Find the gaps, the ghosts, and the mismatches before they derail your migration or your safety case. The platform is built on a proprietary ISO 14224-aligned taxonomy covering 4,000+ material classes and 1,600+ asset classes across Oil & Gas, Mining, Power Utilities, Water & Wastewater, Chemicals, Pharma, Steel & Metals, Cement, Pulp & Paper, and Food & Beverage. Results our clients have seen: 83% cost reduction in data processing, 70% faster project delivery, 98% classification accuracy, and full ROI within 3 months. If your operations run on asset data that doesn't reflect reality — let's talk. 📧 info@datarenew.net

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Debashree Chatterjee is the Co-Founder of DataRenew.

1 people are employed at DataRenew.

DataRenew is based in Bengaluru, Karnataka.

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