Production AI for Manufacturing
Industrial AI for Indian Manufacturers
AI Guru builds and deploys industrial AI for manufacturers. MillMind — our paper-mill operations AI, built for JMC Paper Tech — is in production today, used by 60–80% of mill staff every day.
Predictive maintenance, quality control, energy optimisation, AI over your equipment manuals, plain-language chat for operators — every system we ship is anchored in real plant deployments, not slideware.
What we mean by Industrial AI
Industrial AI is AI applied to the production floor and plant operations — chat-based assistants that answer operator questions, vision systems that catch defects on the line, pattern detection on sensor and equipment data, and AI that reads your equipment manuals and SOPs.
It is not generic enterprise AI applied to a factory. Industrial AI works close to physical equipment, integrates with the systems your plant already runs on (SCADA, MES, ERP), respects OT/IT separation, and is measured against operational KPIs — uptime, yield, specific energy consumption, defect rate, OEE.
Capabilities
Six areas we ship in production today.
Predictive Maintenance
AI watches your equipment and sensor data and flags failures before they cause unplanned downtime. The line stops because you planned it — not because something broke.
Quality Control
AI vision on the line catches defects in real time. Alongside it, AI reads your quality incident logs and helps trace each defect back to its root cause.
Energy & Process Optimization
AI recommendations on operating parameters — reduce specific energy consumption, improve yield, stabilise throughput.
Document & Manual Intelligence
AI that reads your equipment manuals, SOPs, and historical reports and answers operator questions in seconds — no more 30-minute searches through PDFs and filing cabinets.
Conversational Operations
Operators and managers ask questions in plain language — equipment specs, production data, KPIs — and get answers, without learning a new dashboard.
Production Analytics
Ask in plain language — “how did Line 2 run last shift?” — and get the answer. The AI translates your question into the right query behind the scenes.
Built and Deployed
MillMind — paper-mill operations AI, in production
Built by AI Guru for JMC Paper Tech. MillMind replaces 30-minute manual searches and morning-report dashboards with plain-language chat — operators and managers ask about equipment specs, production data, and operating procedures and get answers in seconds. Three things in one system: a chat assistant for operators, AI that reads the mill's equipment manuals, and a plain-language way to ask questions of production data.
Who leads this work
Bhavik Vajariya
Head of India Operations, AI Guru·View on LinkedIn
AI Guru's industrial AI practice is led by Bhavik Vajariya, Head of India Operations. Nearly a decade on Indian manufacturing shop floors before AI — including 8 years at JMC Paper Tech, the same paper company where MillMind is deployed today.
He served as Site In-charge for the revival of Nepa Limited's historic paper mill — Asia's first, a Government of India enterprise — commissioning two paper machines to trial production. He then led JMC's project portfolio with single-project values up to ₹150 Cr across India and overseas, and co-built MillMind with the AI Guru team.
He's the engineer who sits between the operator on the floor and the AI we build.
Industries we serve
Industrial AI is sector-specific. Every engagement is scoped to the customer's process and equipment context.
| Industry | Example focus areas |
|---|---|
| Paper & Pulp | Mill operations, energy, quality, maintenance |
| Cement | Kiln optimisation, predictive maintenance, energy |
| Textile | Loom monitoring, defect detection, demand planning |
| Automotive | Plant-floor quality, supplier risk, predictive parts |
| Chemicals | Batch optimisation, safety incident analysis, compliance |
| Metals | Furnace control, yield, energy and emissions |
| Pharma Manufacturing | Batch quality, equipment OEE, GMP documentation |
| Food Processing | Quality, line balance, traceability, demand forecasting |
How we work with manufacturers
Three connected practices. Most engagements start in one and extend into the others as capability matures.
Build
Production deployments
20 AI products in production across 9 industries. Every system built to ship, not pilot.
See all 20 products →Train
AI for Industrial training
Dedicated program for VP Ops, Plant Heads, Quality and Maintenance teams, and manufacturing IT. Tailored to your process and equipment context.
See the program →Govern
Plant-safe AI governance
AI risk, OT/IT separation, safety oversight, and audit evidence for manufacturing environments. Designed to fit existing plant safety and compliance regimes.
Governance →Frequently Asked Questions
What does AI Guru mean by Industrial AI?+
Industrial AI is AI applied to the production floor and plant operations — chat-based assistants that answer operator questions, vision systems that catch defects on the line, pattern detection on sensor and equipment data, and AI that reads your equipment manuals and SOPs. It covers predictive maintenance, quality control, energy optimization, document and manual search, plant chat for operators, and plain-language analytics on production data.
Which industries do you serve?+
Paper and pulp, cement, textile, automotive, chemicals, metals, pharma manufacturing, and food processing. Every engagement is anchored in the customer's specific process and equipment context — we do not deploy generic templates.
Do you actually build industrial AI systems, or only train teams?+
We build and deploy. MillMind, built for JMC Paper Tech, is in production today at paper mills — 60–80% of mill staff use it daily, equipment lookup is reduced from 30–60 minutes to under 1 minute, and analysis from hours to under 2 minutes. Training programs are anchored in real systems we have shipped, not slideware.
Can you work with our existing plant systems and data?+
Yes. Most industrial AI deployments require integrating with SCADA, MES, ERP, document management systems, and equipment manuals (often unsearchable PDFs). We do this routinely. Engagements start with a discovery of the existing data and system landscape before any AI is proposed.
What is the typical deployment timeline?+
MillMind reached 60–80% daily staff adoption within 90 days. A typical first-deployment timeline is 60–120 days from contract to production use, depending on data readiness and integration scope. We share a phased plan with measurable milestones at the proposal stage.
Do you offer industrial AI training for our plant teams?+
Yes — see our dedicated AI for Industrial program. Built for VP Operations, Plant Heads, Quality and Maintenance teams, and manufacturing IT — covering AI for predictive maintenance, quality control, process optimization, document intelligence, and conversational operations. Customised to your specific plant and process context.
How do you handle safety, OT/IT separation, and plant cybersecurity?+
All engagements respect the customer's OT/IT segregation model. AI components operate in the IT layer with read-only or controlled access to OT data through approved gateways. Sensitive plant data does not leave the customer environment unless explicitly approved. Signed DPAs and security questionnaires are routine.
Talk to us about your plant
Most engagements start with a 30-minute discovery call to scope your equipment, data, and operational KPIs. We send a phased proposal within a week.