Automate video analysis
Looking to leverage Computer Vision as part of Artificial Intelligence initiative on Azure, but unsure about how to move forward? Without human supervision, Computer Vision allows AI to “see” your business all the time, in-store movement of your customers, increased production quality, smart city surveillance – Computer Vision is valuable in different use cases, from edge to cloud.
Accelerate PoC engagement
We offer you a consulting package of 2 month Proof of Concept engagement to solve a Computer Vision challenge. We are able to deliver a prototype of a solution using our iterative and experimental approach to development and benchmarking of Machine Learning models.
Semantives Data Science Team accelerates PoC engagement with custom Deep Learning models, pre-built and pre-trained models to decrease time to value and focus on your specific business use case for Computer Vision.
- “Four O’s” challenges in Computer Vision we solve:
- Object detection
- Object classification
- Object segmentation
Expertise that makes the difference
Get more details
Find estimated pricing, and more details about Computer Vision Proof of Concept before contacting with us.
We are a laureate of
Deloitte Technology Fast 50 is a programme that recognises and profiles the fastest growing public or private technology companies in Central Europe. Semantive has reported a revenue growth of 1 027% over 4 years.
in Central Europe
Pricing and length of PoC engagement is affected by data availability, complexity of a Computer Vision challenge and how much dedicated development is required.
The engagement is structured towards quick results enabling assessment of business case to either continue or abort and move on to a different AI challenge as part of an AI portfolio.
Outcomes of this engagement include:
- Documented solution approach
- Packaged model and deployed to Azure Machine Learning in customer subscription
- Recommendations & Roadmap with next steps
Interested in case study?
Visual Inspection of products
Customer challenge: Automate quality inspection process of semi-finished products during the production process and recognize the broken ones.
Solution provided: A pipeline of custom deep learning models for detecting products and then marking defects with a feedback loop and logging to production system.
Drop us a line
We will contact you as soon as possible.