AI solutions built for manufacturing operations

Implementation costs vary based on scope. A focused pilot targeting one workflow (like quality inspection on a single line) typically runs between 10-25 lakhs over 4-6 weeks. Full-scale deployments across multiple facilities cost more but deliver proportionally higher ROI. We always start with a scoped pilot to prove value before expanding.

Based on our deployments, manufacturers typically see 40-60% reduction in the specific inefficiency being targeted. For quality control, that means fewer defective products reaching customers. For predictive maintenance, that means less unplanned downtime. We measure ROI from day one and share dashboards so you can track impact in real time.

Our average time from kickoff to working system in production is 2 weeks for a focused use case. More complex deployments involving multiple systems integration or custom vision AI models take 4-8 weeks. We ship weekly working demos so you see progress throughout.

Yes. Most Indian manufacturers run a mix of modern and legacy equipment. We build integration layers that connect to existing PLCs, SCADA systems, ERPs like SAP or Tally, and even paper-based workflows through document processing AI. No rip-and-replace required.

Traditional automation follows fixed rules: if X, then Y. AI systems learn patterns from your data and adapt. A traditional system rejects a product if it exceeds a fixed tolerance. An AI system learns what 'defective' looks like from thousands of examples and catches novel defect types the rule-based system would miss.

No. We handle the data engineering, model training, and deployment. Your team needs to provide domain expertise (what good vs bad products look like, which equipment failures matter most) and access to relevant data sources. We train your existing staff to use and monitor the systems we build.