Machine Learning & AI

Have a diverse or large set of data?

i-Neti can leverage machine learning & AI to help you discover new insights,
power business automation and deliver innovative products & services to your clients.

Benefits of Machine Learning

  • Discover new trends and patterns
  • Uncover relationships that expert systems may miss
  • Deliver new & innovative products/services
  • Power business automation
  • Improve efficiency & productivity
  • Decrease operational costs
  • Improve customer retention
  • Maximise business opportunities

Machine Learning Applications

Computer Vision and
Pattern Image Recognition

Relevant to: geodesy, real estate, agribusiness, water resources, transportation companies, and robotics.

Description and fields of application: recognition of buildings on aerial photographs to check development of natural protected areas; recognition of price tags in supermarkets for their relevance monitoring; products availability on shelves for timely replenishment. Pickup of data from video cameras to detect suspicious behavior, to calculate a customer’s route in a store, and to determine focus of attention.

Bankruptcy
Forecasting

Relevant to: banking sector, insurance sector, and verification of counterparties.

Description and fields of application: we use previously structured information for analysis of future behavior of clients. For example, credit, insurance and leasing scoring.

Emotions
Recognition

Relevant to: assessment of satisfaction with services of amusements parks and attractions, assessment of animals’ behavior, and assessment of mood of a crowd.

Description and fields of application: Cognitive services and chat-bots are an essential part here. They are capable of: a) correctly ask a question in text or voice, b) recognize answers, c) determine a tone, d) make preliminary conclusions about a human-interlocutor. For example, such chat-bot can do a primary interview for a mass job, work on the first line of technical support, or collect clients’ feedback on purchase or service.

Steps of Cooperation

~ 1 ~

First, our specialists speak with clients and identify points with the best effort/benefit ratio by using machine learning algorithms.

~ 2 ~

Then we analyze the data that has been accumulated – quantity, integrity, potential of expanding and processing.

~ 3 ~

After analysis, we develop trial models and define lower limits of possible effects. This stage is the most important one – it’s here that we assess the benefits that a business can gain after implementation of our solution.

~ 4 ~

Only at this point does the entire infrastructural team get involved and integrate a developed solution into business-processes.

After a project is implemented on the technical side, the final stage – support – begins. We will improve the accuracy and reliability of the model, increasing business effect and conduct fine tuning of algorithms.

Why i-Neti?

Our goal is to use life-long knowledge and experience in ERP and to develop turnkey working solutions for business.

We provide a full range of services including developing a solution and a corresponding mobile app, adjusting integration with ERP, and making necessary modifications within ERP.

An expert team consisting of a project manager, data scientist and ERP & Web specialists is designated for every project.
i-Neti’s data scientists are active participants of competitions, members of groups of scientists that develop and improve mathematical models.
The team is capable of working with enterprise management systems including Dynamics AX, Dynamics NAV, 1С or even develop a web-service from scratch.
We use proven solutions that not only simplify but accelarate the process of creating effective solutions for business.

Portfolio

Procurement Forecasting in TRUCK Center

Our first project was the analysis of stock balances for a chain of truck service stations. We managed to reduce the amount of stock required by 20% and keep them low in regions with large amounts of illiquid assets.

HRHelper Service

A developed service that can achieve approximately 85% accuracy in resume-based decision-making for selecting candidates for a certain vacancy, provided there is a historical track record of staff-recruitment for this position.

Have big data?

Write or call us and our specialists will evaluate the possibilities of AI & machine learning applications for your business.