AI for manufacturing that actually ships on the shop floor.
We embed engineers inside Indian and GCC manufacturers for 4 weeks, map every line, every handoff, every SAP field. Then we ship working AI every month. ₹15L saved per month is not a slide it is what Tempsens measured after 90 days.
faster quote turnaround at Tempsens
cost savings measured in 90 days
ROI within first year
Why "just buy AI software" fails on the shop floor
No process map exists
You cannot automate what you have not documented. Most factories run on tribal knowledge the senior operator who "just knows" when a bearing is about to fail. AI trained without that context hallucinates confidently.
Data lives in 6 disconnected systems
SCADA logs in one silo, SAP in another, quality records in Excel, maintenance in a WhatsApp group. AI needs a single source of truth not six partial ones.
Operators were never in the room
The pilot was scoped by IT, approved by the CTO, and deployed without a single line supervisor’s input. The model works in the lab. Nobody trusts it on the floor.
Success was measured in "accuracy" not ₹
A 94% accurate defect model sounds impressive until you realize it fires 200 false alerts per shift. The metric that matters is cost saved, rework avoided, throughput gained not F1 score.
Every metric is a problem we solved.
Real numbers from live manufacturing deployments.
Quoting takes 72 hours
SAP master data is 8% wrong
False-positive alert fatigue
Defects caught after shipping
What your team actually says.
"I spend 3 hours a day chasing quotes that should take 10 minutes."
Sales Head
"Our reject rate is 4.2% and we catch it after dispatch."
Quality Manager
"SAP says we have 200 units. The warehouse has 140."
Plant Head
"Maintenance is reactive. We replace after failure, not before."
Maintenance Lead
"We have SCADA data from 3 years. Nobody has looked at it."
CTO / IT Head
"My team spends 60% of the week on data entry, not engineering."
Engineering Manager
Use cases that move the needle.
01Automated Quoting for Custom Builds
Upload RFQ specs and get accurate quotes in minutes not days. AI cross-references BOMs, material costs, and historical pricing.
02Vision-Based Surface Defect Detection
Computer vision on the production line catches surface defects, dimensional drift, and assembly errors in real time.
03Predictive Maintenance with Alert-Trust Scoring
AI scores each SCADA alert by accuracy history and context operators see only alerts that matter.
04Demand Sensing from Distributor POS
ML models ingest distributor point-of-sale data to forecast demand 6–8 weeks out, adjusting production schedules automatically.
05SAP Master-Data Cleanup Agent
Continuous AI audit of material masters, BOMs, and vendor records flags duplicates, corrects UoM errors, validates pricing.
06RFQ-to-BOM Automation
AI reads incoming RFQs, extracts technical specifications, and maps them to existing BOMs or flags gaps for engineering review.
Four pillars. Translated for Manufacturing.
An Engineer on Your Shop Floor
Our Forward Deployed Engineer joins your morning production meetings, walks your lines, and maps every process into a detailed SOP before a single model is trained. They speak OPC-UA, understand SAP MM/PP, and know why Operator #3 overrides the PLC every Tuesday.
Manufacturing-Specific R&D
Defect detection on brushed aluminium is not the same as on injection-moulded plastic. Our Research Engineers run 2-week sprints on real factory problems lighting variance, conveyor vibration, sensor drift so your model works in production, not just in a Jupyter notebook.
A Working Release Every 30 Days
Mid-month staging on your test line. End-of-month production deployment. Every release is peer-reviewed, regression-tested, and comes with a before-and-after impact report. No 6-month "phase 1" that never ships.
We Own the ₹ Number
We don't bill hours. Every month you get a measurable impact report: ₹ saved, hours recovered, defect rate delta, OEE improvement. If the numbers aren't moving, you'll know and so will we.
What happens in the first 30 days.
Process Walk & Data Inventory
Our engineer walks every line, every shift. Maps material flow, operator decisions, handoffs, and data sources. Interviews plant heads, line supervisors, quality, and maintenance.
SOP Documentation & Gap Analysis
Converts tribal knowledge into documented SOPs. Identifies data gaps, integration points (SAP, SCADA, MES), and process bottlenecks where AI has highest ROI.
AI Opportunity Scoring & Mockups
Scores each opportunity by impact (₹), feasibility, and data readiness. Builds working mockups for the top 3 use cases. Validates with operators and plant leadership.
Strategy Deck & Roadmap Delivery
Delivers a prioritised 12-month AI roadmap, detailed cost-benefit analysis, integration architecture, and solution mockups. You keep everything even if you don't proceed.
What you walk away with
We speak your regulatory language.
Regulations & Certifications
- ISO 9001:2015 — Quality management systems
- ISO 14001 — Environmental management
- ISO 45001 — Occupational health & safety
- IATF 16949 — Automotive quality (where applicable)
- BIS Standards — Bureau of Indian Standards compliance
Data & Protocol Standards
- OPC-UA
- MQTT
- MTConnect
- ISA-95 / IEC 62264
- ANSI/ISA-88 (Batch Control)
Enterprise Systems We Integrate
- SAP ECC / S4HANA (MM, PP, QM, PM, SD)
- Siemens SCADA / WinCC
- Rockwell FactoryTalk
- Ignition by Inductive Automation
- MES (Apriso, AVEVA, Custom)
- Minitab / SPC tools
Questions we hear on the shop floor.
Book the 4-Week Manufacturing Audit
4+ years in Manufacturing. SAP-integrated. OPC-UA native.
See how it worked for Tempsens
92% faster quoting, ₹15L/month savings, 585% ROI in year one.
We embedded a Forward Deployed Engineer inside Tempsens for 4 weeks, mapped their SAP + quoting workflow, and shipped an AI quote engine in 90 days. Read exactly what we built and how.