Manual visual inspection missing defects your team can't catch at production speed?
Camera footage and scanned documents generating data nobody can process at scale?
Computer Vision Development Services
Most visual data in your business goes unanalysed. Cameras capture footage nobody watches. Documents pile up waiting for manual entry. Quality checks are done by people standing at a line, catching maybe 80% of defects on a good day.
We build computer vision systems that process visual data automatically -- real-time object detection, document extraction, quality inspection, and video analytics -- for production environments where accuracy and throughput actually matter.
Production computer vision systems -- not demos, not pilots that never ship
Object detection, classification, OCR, and video analytics built around your use case
Deployed in real environments -- manufacturing lines, logistics, healthcare, retail
100+ products shipped including AI and automation systems with visual processing
RaftLabs builds custom computer vision systems -- object detection, image classification, OCR, video analytics, and visual quality inspection -- for production environments in manufacturing, logistics, healthcare, and retail. We combine pre-trained models with custom training on your data, and build the inference pipeline and integration layer that delivers structured output to your downstream systems. Fixed cost, production-ready.
Computer vision that runs in production, not just demos
Every computer vision demo looks impressive on clean, well-lit, carefully chosen images. Production systems deal with motion blur, variable lighting, partial occlusion, document scans at an angle, and conditions that weren't in the training data.
The hard part isn't getting a model to 85% accuracy on a benchmark. It's getting to 95%+ on your specific products, your specific documents, your specific environment -- and keeping it there as conditions change.
We've shipped OCR systems processing thousands of industrial documents a month and AI systems analysing patient monitoring data. That's the production-grade computer vision we build.
What we build
Object detection and classification
Detection and classification of objects, defects, or anomalies in images and video. Real-time inference for production line monitoring, security systems, or inventory tracking. Multi-class detection models trained on your specific products and defect types. Confidence scoring and exception handling for borderline cases. The detection system that works at your production throughput, not just in a lab.
Document OCR and extraction
Extraction of structured data from documents -- invoices, forms, ID documents, certificates, and shipping labels. Template-based extraction for known document formats and AI-based extraction for variable layouts. Pre-processing for challenging scans: deskewing, contrast enhancement, noise removal. Confidence scoring and human review queues for low-confidence extractions. We've shipped industrial OCR systems processing thousands of documents a month.
Quality inspection systems
Visual quality control for manufacturing and processing environments. Defect detection trained on your specific product types and defect categories. Real-time inspection at line speed with pass/fail output and defect classification. Integration with your MES or production system for automated routing. The inspection system that catches defects at production speed, not just under controlled conditions.
Video analytics
Analysis of video streams for operational intelligence. Object tracking across frames, crowd density estimation, entry/exit counting, and behaviour recognition. Processing of live feeds or recorded footage depending on use case. Alerting on specific events -- perimeter breach, queue threshold, or unusual behaviour. Structured event data delivered to your operations dashboard or security system.
Medical image analysis
Computer vision for healthcare and diagnostic imaging. Classification and segmentation models for medical images -- X-rays, scans, microscopy, and patient monitoring footage. Built with clinical accuracy requirements and appropriate validation against ground-truth labelled datasets. Integration with your clinical system for structured reporting output. We've built AI systems for remote patient monitoring that reduced clinical decision time by 20%.
Custom model training and fine-tuning
Custom model training and fine-tuning on your domain data when pre-trained models don't reach your accuracy target. Data collection strategy, labelling pipeline setup, training infrastructure, and model evaluation. Ongoing model improvement as new data becomes available. Transfer learning from foundation models where appropriate to reduce data requirements. The model that knows your specific products, defects, and documents -- not a generic one.
Tell us what you need to see, detect, or extract.
Use case, environment, and accuracy requirements. We'll design the system and give you a fixed cost.
Frequently asked questions
Computer vision development is the process of building software that can interpret and act on visual data -- images, video, and documents. This includes training or fine-tuning models to recognise specific objects, defects, or text in your domain, and building the pipeline that ingests visual data, runs inference, and delivers structured output to your systems. Unlike a generic computer vision API, a custom system is trained on your specific products, documents, or environment, and integrated into your existing workflow. We build computer vision systems for document extraction, quality inspection, object tracking, and video analytics.
Accuracy depends on data quality, consistency of conditions, and how well the model is trained for your specific use case. For controlled industrial environments (consistent lighting, known product types), defect detection systems reach 95%+ accuracy. For document OCR on clean digital files, accuracy is 97-99%. For variable conditions (outdoor footage, inconsistent lighting, mixed document formats), accuracy improves with domain-specific training data. We run a discovery phase to assess your specific conditions and set realistic accuracy targets before development starts.
Both, depending on what achieves the target accuracy most efficiently. For many use cases, fine-tuning a pre-trained foundation model (like YOLO, EfficientDet, or a vision transformer) on your domain data is faster and more cost-effective than training from scratch. For highly specialised domains -- unusual defect types, proprietary document formats, or very specific object classes -- custom model training gives better results. We assess the tradeoff during scoping and recommend the approach that gets you to production accuracy in the available timeline.
We've built vision systems for: document processing (invoice OCR, form extraction, ID verification), manufacturing quality control (defect detection on production lines), logistics (label reading, package dimension estimation), healthcare (medical image processing, patient monitoring), and retail (shelf monitoring, customer flow analysis). The extraction and detection requirements differ significantly by industry -- we design the model and pipeline around your specific use case.
A focused computer vision system -- one use case, model training on your data, inference pipeline, and integration to one target system -- typically runs $25,000--$60,000. Multi-use-case platforms with real-time video processing, exception workflows, and multiple output integrations run $60,000--$150,000. Cost is driven by the complexity of the visual task, the amount of training data required, and the inference throughput needed. We scope every project before pricing it.