Computer Vision Parking Occupancy Detection
Computer vision reads an entire deck in real time, replacing gate estimates with live occupancy by level and row for operators and drivers.
AI Engineering Services
Sunlab Digital offers comprehensive AI engineering services, specializing in Machine Learning, AI Integration, Natural Language Processing (NLP), and Deep Learning to build intelligent solutions.
Our AI Services
Machine Learning Solutions
Custom prediction, classification, anomaly-detection, ranking, and automation models developed and evaluated using client or application-specific data.
Deep Learning Applications
Deep-learning systems for image recognition, signal processing, sequence analysis, anomaly detection, and other applications requiring learned representations.
Computer Vision
Computer vision systems for detection, classification, tracking, counting, inspection, measurement, and site monitoring using representative image or video data.
Natural Language Processing
Text classification, information extraction, search, summarization, routing, retrieval, and assistants grounded in approved documents and data sources.
AI Integration
Integration of models and AI services with existing applications, databases, APIs, permissions, business rules, user interfaces, and human-review workflows.
Deployment and Monitoring
Cloud, private-infrastructure, and edge deployment with versioning, monitoring, logging, performance review, and documented retraining procedures.
How We Work
Data Strategy and Preparation
Define the use case, users, workflow, acceptance criteria, data requirements, privacy constraints, security requirements, deployment environment, and feasibility risks.
Model Development and Training
Prepare data, establish evaluation sets, develop and compare approaches, tune the selected model, and document performance against approved criteria.
Integration and Deployment
Integrate the model with applications and workflows, implement validation and human-review controls, complete testing, and deploy to the approved environment.
Monitoring and Improvement
Monitor production performance, investigate failures and data changes, update evaluation sets, retrain when required, and maintain version and change records.
How We Work
Data Strategy and Preparation
Define the use case, users, workflow, acceptance criteria, data requirements, privacy constraints, security requirements, deployment environment, and feasibility risks.
Model Development and Training
Prepare data, establish evaluation sets, develop and compare approaches, tune the selected model, and document performance against approved criteria.
Integration and Deployment
Integrate the model with applications and workflows, implement validation and human-review controls, complete testing, and deploy to the approved environment.
Monitoring and Improvement
Monitor production performance, investigate failures and data changes, update evaluation sets, retrain when required, and maintain version and change records.
AI Applications
Visual Inspection and Counting
Object detection, classification, tracking, counting, defect inspection, and event detection using fixed or mobile cameras.
Occupancy and Site Monitoring
Computer vision systems for occupancy, utilization, movement, queue, and site-condition monitoring.
Document and Text Processing
Document extraction, classification, summarization, routing, structured data capture, and review workflows.
Forecasting and Prediction
Predictive models for demand, maintenance, scheduling, risk, capacity, anomaly detection, and operational planning.
Knowledge and Retrieval Systems
Search and question-answering systems grounded in approved internal documents, records, and knowledge sources.
Workflow Automation and Agents
AI-assisted workflows that retrieve information, prepare outputs, use approved tools, and route exceptions for human review.
Engagement Models
Feasibility Assessment
Review of the use case, workflow, available data, technical options, evaluation requirements, deployment constraints, and risks, followed by a recommendation and implementation estimate.
Best before funding a pilot or production implementation.
Build and Deploy
Data preparation, model development, evaluation, application integration, deployment, documentation, and handover managed through defined milestones.
Best when the use case is defined and the required data is available or can be collected.
Ongoing Model Support
Production monitoring, incident analysis, evaluation updates, retraining, model releases, and performance reporting for deployed AI systems.
Best for AI systems that require continuing performance review and updates.
Common Questions
How do we know if our data is good enough?
A feasibility assessment reviews data volume, quality, coverage, labeling, access, privacy, and relevance to the intended use case. The result may support immediate development, identify a required data-collection period, or recommend a different technical approach.
Will you use our data to train models for anyone else?
No. Client data is used only for the approved client project. The project documentation identifies any third-party model, hosting, labeling, or data-processing services and defines the applicable access, retention, and confidentiality requirements.
Do we actually need AI for this?
A feasibility assessment compares AI with conventional software, integration, analytics, and process changes. We recommend AI only when it provides a meaningful advantage for the defined requirement.
What happens when the model gets something wrong?
The system is designed around expected error conditions. Depending on the use case, controls may include confidence thresholds, validation rules, exception handling, human review, approval requirements, audit records, and restrictions on irreversible actions.
Don’t see your question? Ask Sunlab, the assistant on this page, or email the team.
Selected Work
AI Agents for PCB Specification and Review
Conductor selects components, reads the datasheets, validates the electrical contracts, and returns a bill of materials and a schematic that can be built.
AI is one of four service areas
Sunlab coordinates hardware, software, AI, and marketing within one delivery team. This reduces handoff delays, clarifies responsibility for cross-disciplinary decisions, and provides one point of contact.
HardwareProduction-ready electronics and connected products, from architecture and PCB design through prototype, validation, and manufacturing handoff.View the ServiceSoftwareCustom web, mobile, platform, and internal software developed around defined business and user requirements.View the ServiceMarketingMarket research, positioning, websites, search, content, campaigns, and analytics for technical products and services.View the Service
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