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Read More →OpenMalo builds custom computer vision systems for Australian businesses — from real-time object detection and automated quality control to intelligent OCR, facial recognition, and video analytics. Our Melbourne computer vision team has delivered 35+ production CV systems for Australian manufacturers, logistics operators, retailers, and security organisations — processing millions of images and video frames daily.
Yes — we build automated visual quality control systems that detect surface defects, dimensional anomalies, and assembly errors with greater consistency and speed than manual inspection. Our YOLOv10 and EfficientDet models achieve 95–99% detection accuracy on manufacturing defect datasets, operating at line speed.
Yes — we deploy object detection and counting models on warehouse CCTV and IP camera feeds for real-time inventory visibility, pick accuracy verification, and throughput monitoring. Models run at 30fps+ on NVIDIA GPU hardware, or at reduced frame rates on edge AI devices for cost-efficient warehouse deployment.
AI-powered OCR using transformer-based document understanding models (TrOCR, LayoutLMv3, or AWS Textract) achieves 96–99% accuracy on structured documents and 90–95% on handwritten text — significantly better than traditional rule-based OCR, particularly for Australian bank statements, government forms, and handwritten field data.
Yes — we build video analytics systems for person counting, perimeter breach detection, PPE compliance monitoring, and queue length measurement on live or recorded CCTV footage. Systems run on edge hardware (NVIDIA Jetson) or cloud GPU instances, with configurable alert thresholds and integration with existing VMS platforms.
Yes — we build Automatic Number Plate Recognition (ANPR) systems optimised for Australian number plate formats across all states. Combined with vehicle type and colour classification, these systems are deployed for parking management, access control, traffic analytics, and logistics yard management.
We optimise and quantise models for deployment on NVIDIA Jetson Orin, Google Coral TPU, and Intel OpenVINO edge AI platforms — enabling real-time inference at the point of capture without cloud round-trip latency. Edge deployment is essential for manufacturing quality control, logistics, and security applications with millisecond response requirements.
We implement automatic face blurring or silhouetting for general surveillance analytics, age-gating consent for biometric systems, and data minimisation by discarding raw video after analysis. All biometric data processing complies with the Australian Privacy Act 1988 and relevant state surveillance device legislation.
Computer vision systems are exposed via REST APIs delivering structured JSON outputs (bounding boxes, class labels, confidence scores, counts). We integrate with SCADA systems, WMS platforms, CCTV VMS software, ERP systems, and Slack/Teams for real-time alerting — fitting into your existing operational technology stack.
OpenMalo's computer vision engineers have delivered 35+ production CV systems for Australian manufacturers, logistics operators, retailers, and government agencies. Our Melbourne team has deep experience with the full computer vision stack — from dataset collection and labelling through model training, optimisation, and deployment on both cloud GPU infrastructure and edge AI hardware. We have built systems processing 50 million frames per day in production, and we understand the engineering discipline required to make computer vision work reliably in Australian industrial environments.
We work across the full range of CV tasks: object detection and instance segmentation (YOLOv10, Detectron2), image classification (EfficientNet, ViT), document understanding and OCR (LayoutLMv3, TrOCR), face analysis (InsightFace), and video understanding (TimeSformer, SlowFast). Models are optimised for production with TensorRT or ONNX Runtime quantisation, achieving 5–10× inference speedups with minimal accuracy loss. Post-launch support and model retraining starts from AUD $2,000/month.
Tell us about your project and we'll respond within 24 hours.
Real-time defect detection, dimensional inspection, and assembly verification for manufacturing production lines — YOLOv10 and EfficientDet models achieving 95–99% detection accuracy at line speed on GPU or edge AI hardware.
Learn More →AI-powered document data extraction from invoices, forms, ID documents, receipts, and handwritten records — using LayoutLMv3 and TrOCR achieving 96–99% field extraction accuracy on Australian document formats.
Learn More →Real-time object detection, counting, and tracking on warehouse camera feeds for inventory visibility, pick verification, pallet identification, and dock management — integrated with your WMS or ERP platform.
Learn More →Video analytics for person counting, perimeter intrusion detection, PPE compliance monitoring, queue length measurement, and crowd density analysis — running on edge hardware or cloud with VMS integration and real-time alerting.
Learn More →Automatic Number Plate Recognition optimised for all Australian state plate formats — integrated with access control systems, parking management platforms, logistics yard software, and traffic analytics dashboards.
Learn More →Independent audit of existing computer vision systems for accuracy, throughput, and resilience to distribution shift — with a remediation plan and ongoing retraining service using new production samples from AUD $2,000/month.
Learn More →Industry-leading tools and frameworks chosen for performance, scalability, and long-term maintainability.
We define the computer vision task (detection, classification, segmentation, OCR), assess your existing image or video data quality and volume, identify annotation requirements, and specify hardware constraints for deployment — producing a feasibility report with accuracy projections.
We design the annotation schema, manage the labelling pipeline (in-house or via a labelling service), and train candidate architectures with transfer learning from ImageNet or COCO pre-trained weights — benchmarking multiple models and selecting the best accuracy-latency trade-off.
Production model is quantised and optimised with TensorRT or ONNX Runtime for target hardware. Integration API is developed and tested end-to-end. Performance is validated on representative production samples measuring accuracy, throughput, and latency SLAs.
Model is deployed to edge hardware (Jetson, Coral) or cloud GPU infrastructure with monitoring for accuracy drift, hardware utilisation, and alert generation. We deliver a documented retraining schedule and provide ongoing support for production incidents.
Consistently rated as a top technology company in Australia — backed by verified client reviews on Clutch and GoodFirms.
We sign an NDA before any discussion. All IP belongs to you — no shared code, no reuse on completion.
Access to project management tools, weekly progress reports, and live sprint demos throughout delivery.
Melbourne and Sydney offices with real people you can meet in your time zone. Invoiced in AUD.
Agile delivery with fortnightly demos so you see progress, give feedback, and stay in control at every sprint.
We don't just deliver and disappear. Structured post-launch support and ongoing development partnerships available.
"OpenMalo delivered exactly what we needed — on time, on budget, and with a level of quality that exceeded our expectations. The team communicated brilliantly throughout."
"The technical quality and attention to detail from the OpenMalo team is outstanding. Our users love the end product and our business metrics improved significantly post-launch."
"Fast, reliable, and professional. OpenMalo understood our requirements immediately and delivered a solution that has genuinely transformed how we operate. Highly recommended."
Custom ML models for prediction, classification, and anomaly detection to complement your CV systems.
Explore →Natural language processing for document intelligence alongside your visual OCR and document AI pipeline.
Explore →Multi-modal AI combining computer vision with LLM-powered document understanding and content generation.
Explore →Strategic AI assessment to identify the right computer vision use cases and ROI before development.
Explore →AWS, Azure, and GCP GPU infrastructure for scalable computer vision model training and deployment.
Explore →Production-grade REST APIs to expose computer vision predictions to your existing systems.
Explore →Get a free computer vision consultation from our Melbourne team — we respond within 24 hours with a feasibility assessment and hardware specification for your use case.
Local teams across Australia backed by a global delivery centre — giving you the best of both worlds.
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