Not just models — complete OT+IT integration. We combine deep learning with PLC automation and IIoT to deliver AI systems that operate at line speed, talk to your existing Siemens controllers, and generate measurable ROI from day one.
We deploy deep learning vision systems directly on your production line — operating at full line speed with no throughput penalty. Our custom-trained PyTorch models, running on NVIDIA Jetson edge hardware, detect surface defects, dimensional deviations, weld quality issues, and assembly errors that manual inspection routinely misses.
Crucially, we integrate the reject signal directly into your Siemens PLC reject logic — no manual intervention, no island system. The AI becomes part of your existing automation architecture.
Unplanned downtime is the most expensive event in manufacturing — typically ₹2-10L per hour depending on line value. Our predictive maintenance system uses vibration, temperature, current draw, and acoustic signals to predict failures days before they happen, giving you time to schedule maintenance without stopping production.
The ML models learn each machine's normal signature from your historical OPC UA data, then flag anomalies that precede failure patterns. Alert thresholds adapt automatically over time.
Beyond inspection and maintenance, AI can continuously optimize your process parameters — injection mold temperatures, welding currents, conveyor speeds, robot path timings — to maximize output quality while minimizing cycle time and energy consumption.
We build closed-loop AI controllers that read live sensor data from your SCADA, compute optimal setpoints, and write them back to the PLC automatically. The result: a self-tuning factory that improves every shift.
We don't build with toy frameworks. Every component is production-grade, validated for 24/7 industrial operation under vibration, temperature, and EMI conditions.
Custom model training, quantization for edge, and ONNX export for hardware-agnostic deployment.
Basler, Cognex, and IDS cameras — from 2MP area scan to 20MP line scan for high-speed inspection.
Orin NX and AGX for edge inference — up to 100 TOPS with fanless enclosures rated for shop-floor IP67.
Standard industrial protocols ensuring your AI system speaks the same language as your existing OT infrastructure.
Time-series dashboards for real-time AI output, defect trends, OEE, and maintenance health scores.
All inference runs on-premise — no production data leaves your facility. Cloud optional for analytics only.
Native PLC integration — AI outputs feed directly into your existing S7-1200/1500 logic with no middleware.
Every system undergoes Factory Acceptance Testing in our lab, then Site Acceptance Testing at your plant.
Enter your current production data to see how much an AI Vision QC system could save your plant annually. Based on real results from our deployments.
All inputs are estimates — we'll refine them together in a free consultation.
Enter your production data on the left to see your estimated annual savings from AI Vision QC.
A direct comparison across the dimensions that matter to your plant manager, quality director, and CFO.
| Dimension | Human Visual QC | AI Vision System |
|---|---|---|
| Inspection speed | 3–8 parts/min (fatigue-limited) | Up to 1,200 parts/min |
| Consistency | Varies by inspector, shift, fatigue level | 100% consistent, every unit, every shift |
| Defect escape rate | 2–5% miss rate on routine defects | <0.1% miss rate (94% improvement typical) |
| Repeatability | Inter-inspector variation: ±15–25% | ± <1% (deterministic model output) |
| Operating cost | ₹2–5L/year per QC operator (salary + training) | Amortized over 5–7 years; minimal recurring opex |
| Night shift / 3-shift operation | Higher miss rate, staffing cost 1.3–1.5× day rate | Identical performance 24/7, 365 days |
| Data & traceability | Paper records, limited digital audit trail | Full image archive, defect database, ISO-ready reports |
| Scalability | Headcount grows linearly with volume | One system handles multiple lines; marginal cost near zero |
| Regulatory compliance | Difficult to demonstrate GMP/IATF process control | Electronic records, digital signatures, full process evidence |
| New defect types | Training takes weeks; quality varies | Model retrained in 1–3 days with new image samples |
Deployed AI Vision on a high-speed stamping line. Defect escape rate dropped 94% in 3 months. Customer warranty claims down 70%. System paid for itself in 8 months.
We offer a free half-day plant visit where our engineers assess your line, identify the top 3 defect categories for AI, and produce a preliminary ROI estimate — at no cost, no obligation.
Or WhatsApp us directly: +91 94040 30215
Not just models — complete OT+IT integration. We combine deep learning with PLC automation and IIoT to deliver AI systems that operate at line speed, talk to your existing Siemens controllers, and generate measurable ROI from day one.
We deploy deep learning vision systems directly on your production line — operating at full line speed with no throughput penalty. Our custom-trained PyTorch models, running on NVIDIA Jetson edge hardware, detect surface defects, dimensional deviations, weld quality issues, and assembly errors that manual inspection routinely misses.
Crucially, we integrate the reject signal directly into your Siemens PLC reject logic — no manual intervention, no island system. The AI becomes part of your existing automation architecture.
Unplanned downtime is the most expensive event in manufacturing — typically ₹2-10L per hour depending on line value. Our predictive maintenance system uses vibration, temperature, current draw, and acoustic signals to predict failures days before they happen, giving you time to schedule maintenance without stopping production.
The ML models learn each machine's normal signature from your historical OPC UA data, then flag anomalies that precede failure patterns. Alert thresholds adapt automatically over time.
Beyond inspection and maintenance, AI can continuously optimize your process parameters — injection mold temperatures, welding currents, conveyor speeds, robot path timings — to maximize output quality while minimizing cycle time and energy consumption.
We build closed-loop AI controllers that read live sensor data from your SCADA, compute optimal setpoints, and write them back to the PLC automatically. The result: a self-tuning factory that improves every shift.
We don't build with toy frameworks. Every component is production-grade, validated for 24/7 industrial operation under vibration, temperature, and EMI conditions.
Custom model training, quantization for edge, and ONNX export for hardware-agnostic deployment.
Basler, Cognex, and IDS cameras — from 2MP area scan to 20MP line scan for high-speed inspection.
Orin NX and AGX for edge inference — up to 100 TOPS with fanless enclosures rated for shop-floor IP67.
Standard industrial protocols ensuring your AI system speaks the same language as your existing OT infrastructure.
Time-series dashboards for real-time AI output, defect trends, OEE, and maintenance health scores.
All inference runs on-premise — no production data leaves your facility. Cloud optional for analytics only.
Native PLC integration — AI outputs feed directly into your existing S7-1200/1500 logic with no middleware.
Every system undergoes Factory Acceptance Testing in our lab, then Site Acceptance Testing at your plant.
Enter your current production data to see how much an AI Vision QC system could save your plant annually. Based on real results from our deployments.
All inputs are estimates — we'll refine them together in a free consultation.
Enter your production data on the left to see your estimated annual savings from AI Vision QC.
These are estimates based on industry averages and our case study results. Actual savings depend on defect complexity, line speed, and integration scope.
A direct comparison across the dimensions that matter to your plant manager, quality director, and CFO.
| Dimension | Human Visual QC | AI Vision System |
|---|---|---|
| Inspection speed | 3–8 parts/min (fatigue-limited) | Up to 1,200 parts/min |
| Consistency | Varies by inspector, shift, fatigue level | 100% consistent, every unit, every shift |
| Defect escape rate | 2–5% miss rate on routine defects | <0.1% miss rate (94% improvement typical) |
| Repeatability | Inter-inspector variation: ±15–25% | ± <1% (deterministic model output) |
| Operating cost | ₹2–5L/year per QC operator (salary + training) | Amortized over 5–7 years; minimal recurring opex |
| Night shift / 3-shift operation | Higher miss rate, staffing cost 1.3–1.5× day rate | Identical performance 24/7, 365 days |
| Data & traceability | Paper records, limited digital audit trail | Full image archive, defect database, ISO-ready reports |
| Scalability | Headcount grows linearly with volume | One system handles multiple lines; marginal cost near zero |
| Regulatory compliance | Difficult to demonstrate GMP/IATF process control | Electronic records, digital signatures, full process evidence |
| New defect types | Training takes weeks; quality varies | Model retrained in 1–3 days with new image samples |
Deployed AI Vision on a high-speed stamping line. Defect escape rate dropped 94% in 3 months. Customer warranty claims down 70%. System paid for itself in 8 months.
We offer a free half-day plant visit where our engineers assess your line, identify the top 3 defect categories for AI, and produce a preliminary ROI estimate — at no cost, no obligation.
Or WhatsApp us directly: +91 94040 30215