Industrial Edge AI & Computer Vision
Real-time defect detection, predictive maintenance, and anomaly classification on resource-constrained MCUs/SoCs. Deployed in high-speed production lines (30-60 FPS) with zero cloud dependencies.
Deploy ML, computer vision, and predictive analytics directly on embedded processors — achieving sub-50ms response times where cloud latency, bandwidth constraints, and data privacy make traditional solutions impossible. Built for manufacturing, energy, and data center environments operating at scale.
IoTantra specializes in industrial-grade Edge AI systems for large-scale manufacturing, energy infrastructure, and data center operations. Led by Karthik Suryadevara, a firmware and embedded systems architect with 15+ years deploying mission-critical IoT and machine learning solutions in harsh industrial environments.
Unlike generic IoT consultancies or cloud-first vendors, every engagement is founder-led with deep technical involvement — from architecture and firmware optimization to edge ML model deployment and enterprise integration. Purpose-built for environments where milliseconds matter and failure is not an option.
Full-stack expertise from silicon to enterprise — purpose-built for industrial deployments at scale.
Real-time defect detection, predictive maintenance, and anomaly classification on resource-constrained MCUs/SoCs. Deployed in high-speed production lines (30-60 FPS) with zero cloud dependencies.
Safety-rated embedded systems on STM32, ARM Cortex-M, and industrial SoCs. FreeRTOS/Zephyr optimization for deterministic response, power efficiency, and 99.99%+ uptime in 24/7 operations.
Large-scale deployments using LoRa, BLE mesh, Wi-Fi 6, Wi-SUN, and HaLow. Proven in harsh RF environments — connecting 100+ nodes across kilometers with guaranteed reliability.
Secure bi-directional flows between edge devices and enterprise systems. MQTT, OPC-UA, Modbus, HTTPS/TLS with end-to-end encryption — compliant with IT/OT security standards.
On-premise MCP servers connecting operational data to Large Language Models. Enable natural-language queries, intelligent alerts, and automated decision support — without cloud data exposure.
Proven Edge AI systems delivering measurable ROI — from preventing equipment failures costing ₹lakhs per hour to optimizing energy spend and ensuring regulatory compliance in mission-critical operations.
Vision inspection systems, predictive maintenance for rotating equipment, line optimization with edge analytics. Deployed across automotive, pharma, electronics, and heavy industries.
Pest detection, crop and pond health monitoring, irrigation and feed optimization. Solar-powered edge AI systems operating completely off-grid in remote locations.
Substation monitoring, grid anomaly detection, renewable energy forecasting. Real-time edge intelligence for utilities, substations, and distributed energy resources at scale.
Real-time perception, sensor fusion, safety-rated control systems. Navigation and object detection on embedded platforms for AGVs, industrial robots, and autonomous inspection vehicles.
Vibration, thermal, and current signature analysis on 50-200+ assets. Forecast failures 24-72 hours in advance — preventing unplanned downtime costing ₹5L-₹20L per hour.
Real-time edge AI for HVAC, lighting, and server cooling optimization. Achieve 15-25% energy reduction on multi-crore annual spend with verified ESG metrics and compliance reporting.
30-60 FPS defect detection on production lines with <0.5% escape rate. Edge processing eliminates bandwidth bottlenecks and ensures data privacy for sensitive products.
100+ substations with edge analytics for real-time anomaly detection and predictive failure analysis. Prevent multi-crore outages while meeting smart grid compliance mandates.
Edge-based anomaly detection for HVAC, power, and environmental systems. Evidence-backed alerts with suggested remediation actions — ensuring uptime and compliance in regulated environments.
On-premise MCP servers enabling natural-language queries over operational data. Accelerate decision-making, automate compliance reporting, and provide intelligent alerts — with zero cloud data exposure.
Automated checks that compare review text sentiment with numeric ratings, flag mismatches, and keep an audit trail. Deployable on-prem for privacy — ensuring equitable people processes.
On-prem agents that scan logs/configs to surface drift, suspicious access and policy violations — every alert includes evidence for audit teams. Continuous compliance monitoring at scale.
Detect energy anomalies and provide event-level suggestions to support verified ESG reporting and cost savings. Real-time tracking with auditable metrics for sustainability goals.
Typical engagement scope varies based on deployment scale, integration complexity, and operational requirements:
Not sure where to start? Let's discuss your requirements — I'll help you determine the right approach.
Tell me about your operational challenges, constraints, or project ideas — I'll respond within one business day with an initial assessment. All engagements are founder-led, privacy-first, and tailored to your environment (on-prem, cloud, or hybrid).