A plant manager who knows which line will go down 3 weeks before it does. A quality director who catches defect patterns before a single unit ships. A VP whose entire factory floor — across every plant, every shift — is visible right now, not in next week's report. This is what AI-powered manufacturing intelligence delivers.
Unplanned downtime costs industrial manufacturers an estimated $50 billion annually — yet AI-driven predictive maintenance can reduce machine failures by up to 70% and extend equipment life by 20–40%. Deloitte — Industry 4.0 & Manufacturing →
See How It Works →From the production floor to the boardroom — every layer of your manufacturing operation becomes measurable, manageable, and predictable.
Traditional SCADA and MES systems collect data. AI agents act on it — continuously, autonomously, and in real time. Think of it less like a dashboard and more like hiring a team of tireless process engineers who monitor every machine, every sensor, and every production run simultaneously — and escalate the right thing to the right person before it becomes a problem.
A structured rollout that integrates with your existing plant infrastructure — from day one to full multi-site deployment.
Integrate with existing SCADA, MES, ERP, and IoT sensors. Plug into your cameras, PLCs, and cloud infrastructure. No rip-and-replace required.
Models trained on your production history, machine specs, quality standards, and shift patterns. Live within 6 weeks. No generic templates.
Deploy to every plant and production line. Dashboards for every role — from floor operator to VP Operations to the boardroom.
Connect to the industrial platforms, cloud infrastructure, and AI models your teams already rely on — without replacing a single system.
ERP
Automation
Cloud
Cloud
Process Control
AI Models
AI Safety
Automation
AI monitors vibration, temperature, pressure, and cycle data from every machine — detecting failure signatures 2–4 weeks before breakdown. Maintenance becomes planned, not panic. Your production lines stay running.
↗ Deloitte — Industry 4.0 & Predictive MaintenanceAI inspects every unit on the line — detecting surface defects, dimensional errors, and assembly faults in milliseconds. Root cause traced automatically. Scrap rates and end-of-line rejects drop from the first week of go-live.
↗ McKinsey — AI in Quality ManagementAI surfaces which line is constraining output, which station is causing the slowdown, and exactly what to do about it — in real time. Stop guessing. Start optimising with data that updates every 60 seconds.
↗ World Economic Forum — AI in ManufacturingEvery plant, every production line, every shift — visible in one dashboard. AI surfaces what needs your attention before it becomes a crisis. From floor operator to VP Operations, everyone sees exactly what they need.
↗ PwC — Industry 4.0: Building the Digital EnterpriseManufacturers that have deployed AI-driven intelligence are reporting consistent, measurable improvements within the first 6–12 months of go-live.
Engineers and operators from IIT Delhi, NIT Rourkela — Hero Group, Zomato, EY — who've built and scaled operations in industrial environments and are now building multimodal AI that makes manufacturing organisations truly intelligent.
B.Tech, NIT Rourkela '13 · EY, AI Monk, Dvara E-diary · $2M raised
B.Tech, NIT Rourkela '12 · Hero Group · EasyLokal ~$100K (Techstars) → WayCool · Zomato 1.5M txns/month
B.Tech, IIT Delhi '12 · Hero Group $200M+ · Jangid Motors $5M ARR · Oye! Rickshaw 100k+ txns/day, $12M raised (Matrix, Xiaomi)