Custom
AI & Machine Vision
Development
Consulting
Hiring an AI expert can cost a fortune. This is why we truly believe that our Computer Vision and AI professionals could not just serve you but to become a part of the problem solving chain.
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
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
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.
Peace of mind
We will help you to strike the right balance between long-term goals and short-term result. Proml develops AI solutions of cutting-edge, so you don’t need to worry about keeping up with innovations.
Annotated Data
We have anotation specialits who can easily and substantialy label thousands of images for your project.
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 services.
Workflow
Our typical project consist of stages we describe below.
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.
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 (Exploration)
Input: research and project constraints.
Deliverable: scope of work, schedule, budget and 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.
Product Pilot and Technology Validation
Input: technology and hypotesys.
Deliverable: realization of the certain idea to demonstrate feasibility.
Time frame: 4-8 weeks.
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.
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.
