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
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.
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.
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?
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.