Industrial and operational teams
Inspect products, assets, environments, processes, and events using repeatable visual evidence.
Detection, recognition, inspection, extraction, tracking, and visual intelligence
Computer vision development
Rokad develops computer-vision systems for images and video, from data and model design through edge or cloud deployment, review workflows, and monitoring.
Designed for / 01
A focused delivery model for the organisations that need it.
Computer vision must be designed around the camera, environment, visual variation, error cost, review process, and deployment hardware. Rokad builds detection, classification, segmentation, tracking, OCR-related, inspection, and visual analytics systems with data operations and production integration.
Product companies using cameras or imagery
Add recognition, measurement, guidance, search, moderation, or visual interaction to a software or connected product.
Organisations processing visual records manually
Automate extraction, classification, triage, comparison, and review across large image or video volumes.
Challenges / 02
The problems this service is built to solve.
Lab images do not represent the field
Lighting, angle, distance, motion, background, hardware, wear, weather, and operator behaviour change model performance.
Labels are expensive or inconsistent
The system needs a practical annotation strategy, quality review, class definitions, edge cases, and active-learning loop.
Inference must fit device and network constraints
Latency, power, bandwidth, privacy, camera, compute, model size, updates, and offline operation affect the entire architecture.
Capabilities / 03
What Rokad can deliver.
01
Vision feasibility, camera, environment, task, and error assessment
02
Image and video classification, detection, segmentation, tracking, and similarity
03
Visual inspection, measurement, OCR coordination, document image, and scene analysis
04
Data collection, annotation, quality review, augmentation, and active learning
05
Model selection, training, fine-tuning, optimisation, and evaluation
06
Cloud, edge, mobile, or embedded inference and device integration
07
Review interfaces, alerts, evidence, monitoring, retraining, and managed operation
Solution components / 04
The system behind the visible product.
Imaging system
Camera, optics, placement, lighting, capture timing, resolution, calibration, storage, and environmental constraints.
Visual data operation
Collection, consent, labelling, taxonomy, quality, versioning, difficult examples, augmentation, and retention.
Model and inference
Architecture, training, thresholds, latency, compression, hardware acceleration, serving, and fallback.
Operational workflow
Alerts, review, evidence, correction, escalation, action, analytics, feedback, and system integration.
Use cases / 05
Where this capability creates practical leverage.
Visual quality inspection
Detect defects, deviations, missing components, surface issues, assembly errors, or packaging problems.
Asset and scene monitoring
Identify objects, conditions, occupancy, movement, safety events, or changes across defined environments.
Document and image processing
Classify visual records, locate regions, improve OCR, extract evidence, compare images, and route review.
Visual product capability
Enable search, guidance, recognition, measurement, moderation, augmented workflows, or user-generated image analysis.
Architecture and integration / 06
Designed to fit the wider technology environment.
Capture before model
Improve camera, lighting, placement, calibration, and process consistency before compensating with model complexity.
Edge-cloud split
Place capture, preprocessing, inference, storage, review, analytics, and training where latency, privacy, bandwidth, and hardware allow.
Human review boundary
Route uncertain, high-risk, novel, or policy-relevant cases to review while collecting corrections for future evaluation.
Quality and control / 07
Production requirements are part of the build.
Measured behaviour
Representative evaluation data, quality criteria, failure modes, and release thresholds are defined before expanding production use.
Controlled actions
Permissions, policy checks, approval gates, audit trails, fallbacks, and escalation paths govern consequential AI behaviour.
Observable operation
Inputs, outputs, retrieval, tool calls, latency, cost, model versions, and quality trends are monitored appropriately.
Delivery / 08
A controlled path from requirement to operation.
Discover
Clarify the business outcome, users, workflows, constraints, dependencies, risks, and measurable acceptance criteria.
Architect
Define the system boundaries, data, integrations, security, operating model, delivery sequence, and technical decisions.
Build and validate
Deliver in controlled increments with stakeholder review, automated testing, documentation, and production-quality engineering.
Deploy and improve
Launch safely, establish observability and support, then improve the system using operational evidence and user feedback.
Typical deliverables
Vision feasibility, environment, camera, data, and error assessment
Capture, annotation, model, inference, and workflow architecture
Data collection, labelling, quality, and versioning pipeline
Trained and evaluated vision model or integrated model system
Cloud, edge, mobile, or embedded inference implementation
Review, monitoring, feedback, retraining, and operating documentation
Engagement models / 09
Use the delivery structure that matches the work.
Fixed-scope delivery
A defined outcome, scope, acceptance criteria, milestones, and commercial structure for a bounded project.
Dedicated product team
A stable cross-functional team delivering an evolving roadmap with shared product and engineering ownership.
Embedded specialists
Specialist engineers working inside an existing product, technology, data, design, or operations team.
Managed evolution
Ongoing reliability, security, maintenance, feature delivery, and roadmap execution after launch.
Related capabilities / 10
Continue through the wider product and technology system.
01
Machine learning
Build the wider prediction, data, and model lifecycle.
02
MLOps
Operate visual datasets, models, deployments, monitoring, and retraining.
03
AI integration
Connect visual intelligence to products and operational workflows.
01
Product engineering and prototyping
Integrated software, embedded, electronics, CAD, prototyping, and connected-product development.
02
Mobile app development
Cross-platform, iOS, Android, and enterprise mobile products.
03
Managed technology services
Ongoing maintenance, cloud, security, reliability, support, and continuous engineering.
FAQ
Computer vision development
Scope, ownership, assumptions, delivery, security, and long-term operation are clarified before work begins.
01Do we need custom model training?
Do we need custom model training?
Not always. We compare existing APIs, foundation models, open models, fine-tuning, classical vision, and custom training based on task specificity, data, accuracy, latency, privacy, and cost.
02Can computer vision run without a constant internet connection?
Can computer vision run without a constant internet connection?
Yes. Edge or device inference can support offline and low-latency operation, subject to hardware, model size, update, storage, and power constraints.
03How much labelled data is required?
How much labelled data is required?
It depends on task complexity, variation, class balance, pre-trained model suitability, error tolerance, and capture consistency. We use pilots and learning curves to estimate the data requirement.
04Can operators review uncertain results?
Can operators review uncertain results?
Yes. We can provide confidence-based routing, evidence views, correction interfaces, escalation, audit history, and feedback into future evaluation or training.
AI development
Design the visual system around the real environment, not an ideal dataset.
Rokad can assess capture, data, model, hardware, review, and operational requirements before production development.
Contact / 05
Bring us the difficult technology problem.
Tell us what you need to build, improve, procure, deploy, or operate. We will respond with a practical next step.