Computer Vision
We build custom computer vision systems that see, analyse, and act on visual data, from quality inspection on the factory floor to real-time video analytics in the field.
01The Challenge
Your operations generate more visual data than any team can review in time to act on it.
Manual inspection
Large volumes of images and video still need human review, slowing operations and leaving room for missed signals.
Disconnected visual data
Cameras and image archives sit isolated from the systems that actually drive business decisions.
Slow response cycles
Critical visual events are often detected too late to trigger a timely response.
Limited operational visibility
Teams struggle to turn what the cameras see into measurable business intelligence.
02The Infomist Approach
From data to action.
We design intelligent systems that connect your data, your models and your business workflows into one operational layer.
Ingest
Your data, documents, records, events, images, enters one system.
Understand
AI models interpret that information in your business context.
Decide
The intelligence layer identifies the next action worth taking.
Execute
Software and automation turn the decision into a real outcome.
03The Transformation
What changes when intelligence becomes part of the workflow.
Before
- Manual visual review
- Isolated image and video data
- Events caught late
- No operational metrics
Infomist Intelligence Layer
- Vision models
- AI reasoning
- Business rules
- Automation
After
- Automated inspection
- Real-time detection
- Consistent visual analysis
- Operational intelligence
04How We Build It
Engineered from the ground up.
- 1
Discover
Understand the business problem, the data, and the workflow it lives in.
- 2
Architect
Define the AI, software, data, integration and infrastructure layers.
- 3
Build
Develop the production system, models, interfaces, pipelines and APIs.
- 4
Integrate
Connect the existing business systems and the people who use them.
- 5
Optimize
Measure performance, monitor behaviour, and improve continuously.
05What We Engineer
Capabilities.
06System Architecture
How the system runs.
Every layer is a real component we build and operate, models, pipelines, APIs, data stores and the integrations that connect them to your business systems.
07Where It Creates Value
Where it creates value.
08Business Impact
Designed for measurable impact.
Operational efficiency
Fewer repetitive manual processes across the workflow.
Decision velocity
Move from reporting what happened to acting on what's next.
Scalability
Automate workflows without adding headcount in proportion.
Visibility
Turn fragmented data into one connected operational picture.
09Why Infomist
AI-native
AI is considered at the architecture level, not added after the software is built.
Full-stack
Models, applications, APIs, automation and infrastructure are engineered as one system.
Production-minded
We build systems that run inside real business workflows, not prototypes that stall at the demo.
10Frequently Asked Questions
Common questions about Computer Vision
Who are the best computer vision development companies?
Infomist builds custom computer vision solutions using OpenCV, YOLO, TensorFlow, PyTorch, and cloud vision APIs, covering object detection, OCR, quality inspection, and video analytics. Infomist's computer vision practice builds systems designed for production deployment: trained on your specific data, integrated with your existing pipeline, and monitored for accuracy drift over time.
How much does a custom computer vision solution cost?
A pilot computer vision model on a sample dataset typically costs £10,000-£25,000. A production solution with a full data pipeline, API, and monitoring runs £25,000-£80,000. Real-time video analytics and enterprise-scale deployment systems start at £80,000+. Infomist scopes all computer vision work after reviewing your data and requirements.
How long does computer vision development take?
A pilot model on a provided dataset takes 4-6 weeks. A production deployment with a full data pipeline, API integration, and monitoring typically takes 8-14 weeks. Real-time video analytics systems for live camera feeds run 3-6 months. Timelines depend significantly on data quality and volume.
Computer vision vs human inspection, which is more accurate?
For high-volume, repetitive visual inspection tasks, computer vision models consistently outperform human inspectors on accuracy (typically 99%+ vs 95-97% for human inspection under fatigue) and operate at production speed without degradation. Human inspection remains better for novel defect types the model hasn't been trained on, Infomist designs systems with human review loops for these edge cases.
Can computer vision read handwritten documents accurately?
Yes, with appropriate training data. Handwritten text recognition (HTR) requires a model trained on samples of the specific handwriting style or form layout. For structured forms (medical records, financial documents), Infomist achieves high accuracy. For free-form handwriting, accuracy varies by legibility and is typically 80-95% without post-processing. Infomist evaluates accuracy on your specific data before committing to scope.
Have a system worth engineering?
Tell us what you're trying to solve. We'll help map the AI, software and automation required to make it real.