How we support companies and improve processes through Artificial Intelligence
What we do
Cognitive Computing (CC)
Also known as Augmented Intelligence, it refers to any process acquisition, collection and comprehension of data made by a human being, accompanied by technologies and decision support tools.
Artificial Intelligence (AI)
The science and development of “smart machines”, mimicking human intelligence processes on machines: the behaviors are created beforehand based on predefined logics, but the end result is still part of human interpretation / decision.
Machine Learning (ML)
The science and “art” of programming computers that can learn from data and define logics to obtain the output from data itself. The logic is not made by humans but is generated by machines.
Deep Learning (DL)
A specific subset of Machine Learning that takes full advantage of the structure of neural networks, in order to create a hierarchy of levels and elaborate a bigger quantity of tagged data.
What are the benefits of Artificial Intelligence
It increases competitiveness
AI is a new skill that will allow companies to take strength, becoming more winning and competitive.
It will become a commodity
AI will become an integral part of corporate processes: 15% of customer experience services will be based on Artificial Intelligence by 2021.
It promises to increase profits
Many digital native companies have already invested in Artificial Intelligence, providing relevant case studies that generated high economic return.
We can simplify users’ tasks by understanding voice commands and speeding up management activities.
Estract data through face or image recognition in order to confront them with other information or to verify the user’s identity.
We design virtual assistants that are able to:
- interact with the user through natural language
- respond automatically to the user’s requests
- gather information to be forwared to human agents.
We develop predictive engines that allow users to manage their tasks and gather insights, based on statistic analysis of the existing data.
Artificial Intelligence, Design Thinking and Agile Methodology
An Artificial Intelligence project does not end with the implementation of the system, but keeps on evolving through continuous updates and training of the engine.
Order Entry System for gas stations
Oil & Gas
We integrated a system based on voice recognition and text-to-speech technology with a semantic network inside of an order entry app for gas stations.
The system is available through voice input (by calling the phone number of the service) or via Telegram through a dedicated chatbot.
Our system allows to:
- Insert, delete and modifiy fuel orders
- Read messages for the manager
- Gather up-to-date market prices in real time
Semantic engine for intent categorization of incoming calls in contact centers
We developed a semantic engine integrated with a neural network, trained to gather the customers’ requests through voice recognition and forward the call to the specific assistant, managing and tagging the main macro-interactions (such as purchases, modifications, complaints, communications, spam) automatically.
Face recognition system
Fashion & Retail
Our system is integrated with a neural network that can:
- recognize new and registered customers
- define sex and age
- understand the customers’ moods and emotions.
Based on the data collected by the system, it is possible to generate deeper analyses, in order to create new offers and customized sales insights.
Image recognition system
The engine is built with several neural networks that can automatically read digital and mechanical energy meters.
The engine identifies the meter type, receives the image, extracts the meter reading data and provides the output to the user.
The engine allows the employees to manage the HR processes and information through Whatsapp, Telegram or Google Assistant.
The users can authenticate through their phone number and view their own payslips, request information about their leaves of absence and holidays, receive customized alerts and other services.
Sales Force Automation system based on predictive engine
Fashion & Retail
The system can support sales agents by showing targeted insights to improve efficiency and revenues. This application is based on:
- A semantic analysis engine that can indentify the sentiment of the feedback notes (positive, neutral or negative) inserted by the agent, categorizing and tagging them automatically through algorythms
- A predictive network based on market trends and based on parameters such as country, brand and area where the sales agent is operating
- An engine that generates a smart agenda for clients visits and forecast which client will be more likely to have a successful
Reporting and task management system based on voice input
Construction and Engineering
The system allows the workforce to keep track their own timesheet and check the tasks scheduled on the following days. The app is available by phone number or Telegram* and can be integrated through APIs with the most common project management platforms.
*: requires user authentication
Image recognition service to analyze interbank documents
The sistem is built with an OCR engine and a neural network that recognizes the text inside an image and compares it with predefined tags contained in an interbank file.
We trained the neural network to identify the tags through OCR, connect them with the other known information and extract the data inside the customer’s e-banking app.