Outsourcing – custom Machine Learning software | CVisionLab

 

computer vision in production

 

Custom
Machine Learning
and Deep Learning
Outsource services

 

 

Outsourcing is not a silver bullet to break down walls blocking you from progress.
But we can help you to find a solution to some of them.

Share your targets with us

 

 

 

Outsourcing

Hiring an AI expert can cost a fortune.
This is why at CVisionLab we truly believe that our Computer Vision and Deep Learning professionals could not just serve you but to become a part of the problem solving chain.

 

Costs reduction

Costs reduction

We are investing in proper ML infrastructure, staff training, and have relevant HR and project management support. This way you pay only for engineering time and enjoy lower operating costs. Plus, we provide computational power for training of models per project.

 

Lower risks

Lower risks

We are commited to quality of deliverables, time frames and budget. 85% of our customers are loyal clients. We have a 98% project success rate. Since 2015, customers accepted 48 000 hours and 136 projects.

 

Higher efficiency with computer vision

Higher efficiency

You can focus on your core business while we are taking care of the Computer Vision part of it. Our clients enjoy transparent development processes consistent with their timelines as well.

 

Cutting-edge in AI

Peace of mind

We will help you to strike the right balance between long-term goals and short-term result. CVisionLab develops AI solutions of cutting-edge, so you don’t need to worry about keeping up with innovations.

 

Annotated Data by CVisionLab

Annotated Data

We have anotation specialits who can easily and substantialy label thousands of images for your project.

 

GPU Economy with CVisionLab

GPU Economy

Our clients are granted with adequate GPU per project. No need to shop around for desirable and required instances on other top rated sevices.

 

 

Workflow

Our typical project consist of stages we describe below.
Depending on specificity of each task some parts might be longer, shorter or skipped.

 

Baseline

 

 

 

 

Preparing Rough Proposal for the Development (Exploration)

Input: research and project constraints.
Deliverable: scope of work, schedule, budget and client’s kick-off meeting.
Time frame: 1-2 weeks.

 

Initial Review of the Task (Audit)

Start: internal kick-off meeting with Team leaders.
Deliverable: assessment of what can be done based on our experience solving similar tasks and current modern solutions.
Time frame: 3-5 days.

 

Preparing Rough Proposal for the Development (Exploration)

Input: research and project constraints.
Deliverable: scope of work, schedule, budget and client’s kick-off meeting.
Time frame: 1-2 weeks.

 

Research and Technology Selection

Input: detailed understanding of a project objectives, their feasibility and performance requirements.
Deliverable: review/testing of most promising approaches, discusion and approval of a testing protocol that will be used for quality evaluation during further development, prepare detail plan for further development.
Time frame: 1-3 weeks.

Proof of Concept

 

Product Pilot and Technology Validation

Input: technology and hypotesys.
Deliverable: realization of the certain idea to demonstrate feasibility.
Time frame: 4-8 weeks.

 

Product Pilot and Technology Validation

Input: technology and hypotesys.
Deliverable: realization of the certain idea to demonstrate feasibility.
Time frame: 4-8 weeks.

MVP

 

 

Development Improvements of the Product to Make it Production Ready

Input: initial prototype.
Deliverable: Average team may vary but 2 roles are permanent
• Team lead, who shares vision and provide technician exportation and quality of code.
• Project manager, helps you to find and check several routines questions in the project and provide a short and useful report each week.
Time frame: Duration of this stage significantly depends on the tasks and results achieved during the development of the initial prototype.

Following this cycle allows us to take full responsibility for development of Computer Vision product approved by the client and make sure that everything will be completed as expected and on time.

 

 

 

Our competences

There are so many popular Deep Learning software tools. Certainly we know their prons and cons.
But our strong side is that we can and do contributes to open source projects.

 

TensorFlow

mxnet

PyTorch


 

OpenCV

NymPy

Point Cloud Library

scikit-learn

nvidia CUDA

 

 

 

Clients about us

 

Duplicate image detection

Alexander and his team built us a phenomenally effective duplicate image detection system, tuned to the corpus of the image found on our site and our own unique conception of what constitutes a “duplicate”. Would work with the team again on projects requiring vision expertise.

Niel Berkman, President
We Heart It

 

Remove text from video

Alex has excellent knowledge of all areas of computer vision, most of it goes over my head, but he was able to understand our requirements and get a good solution built. We then moved on to a second iteration and Alex understood the what was needed and had the changes made quickly. Will use for all future computer vision needs, I would highly recommend speak to Alex about your computer vision needs.

Colin Lamond, CTO
Copla Ltd

 

Pattern recognition

I worked with Alexandra during a very challenging R&D project. Results which we achieved were accepted by investors. We haven’t reached all goals due to the limited time we have. I’m looking forward to work with Alexandra again.

Jakub Folga, PM
Atos

 

From 1 hour to 2 minutes

Vladimir is super talented and was able to add value in existing software he had to learn, as well as develop new software from scratch. Just as one example, he made an improvement that cut the processing time of complex 3D modules from 1 hour to 2 minutes. I hope to work with him again in the future.

Shlomi Avigdor, CEO
ORCA Dental AI

 

 

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