Services

Our Artificial Intelligence Services

Our AI experts handle your hyperparameter tuning, optimizing your unique machine-learning model optimization requirements.

Hyperparameter Model Tuning

Our AI experts handle your hyperparameter tuning, optimizing your unique machine-learning model optimization requirements.

PoC of AI Solutions

Developing the proof of concept (PoC) is prima facie in adopting an AI solution and understanding the potential of your idea.

Services

We make digital tech work for you the way it should

We constitute a hand-picked team that has exceptional market eminence at the niche services we provide, giving your business the potential to digitally renovate in par with the value of its brand.

Design

Solve your creative challenges with a human-centered design thinking approach

Managed Services

Sit back and relax while we manage your every IT need

Cloud

The journey of a thousand files started with a single Cloud

Automation

Turn every chore you touch to an automated solution

Internet of Things

Seize the unimaginable with IoT

Application Services

Set your business on ‘auto-evolve’ with Application Services

Our AI Development Process

1. Identifying the problem
2. Preparing the data
3. Training the model
4. The Suited AI Model
5. Evaluating the model
6. AI Deployment
7. Monitoring and maintenance

Identifying the problem

The first step of building your custom AI solutions begins with identifying the problems

or opportunities that the system can solve. Our team runs a thorough analysis to examine the pain points of the project and create a business case. Analyzing the current practices and data sets is necessary to identify areas for implementing automation and development.

Preparing the data

Once we define the problem, the next step is to collect and prepare the data for the AI system to process, learn, and make decisions. The phase includes collecting data from various sources, which comprises structured databases, unstructured text, images, videos, or sensor data. We then clean and preprocess the data to remove noise, handle missing values, normalize it, and convert it to a suitable format for the AI system to use.

Training the model

Once we decide upon the AI model, we can train them using the prepared data set. The training phase includes iterating on the model’s architecture and fine-tuning the model hyperparameters to maximize effectiveness and optimize the operating accuracy. Our team ensures to regularize the model to prevent any overfitting. We then use the prepared datasets to train the model to generate insights and forecasts.

The Suited AI Model

It’s critical to determine the optimal model, algorithm, and techniques to implement an AI solution for a particular business problem. Our team chooses machine learning algorithms, deep learning models, or rule-based systems to tackle your challenges. We consider various factors like model complexity, interpretability, and scalability while choosing the model. We help you pick the suited algorithm to deliver the expected results from a myriad of options, such as supervised or unsupervised learning, deep learning, or reinforcement learning.

Evaluating the model

On training the model, it’s time to put it to the test. We evaluate the model using the trained dataset to ensure it delivers the desired performance metrics’ accuracy and compliance. The performance metrics depend on the distinct problem but may contain accuracy, precision, recall, F1-score, or others. Model evaluation is vital as it reveals potential biases, issues, and other items that could make the AI system less effective. We then make necessary adjustments and run the assessment again, ensuring the model generalizes and works with new, unseen data.

AI Deployment

Once we complete training and testing the AI model, we deploy the decision-making and insight-delivering system into the target environment or application. The deployment phase includes setting up the solution infrastructure, integrating the system with others, and configuring the application to work in sync with the existing business process. We implement APIs or interfaces for interaction, monitor the model’s performance in real-world use, and handle updates as needed.

Monitoring and maintenance

Even after the deployment, the AI model requires continuous monitoring and evaluation of its performance, making the essential adjustments to keep it precise, effective, and unbiased. We regularly update the model with new datasets, retrain the model when required, and bring necessary changes to the configuration. It’s also critical for timely intervention and solving bugs and issues that arise over time.

Case Studies

Let our work do the talking

Learn about the instances where we were able to create an impact, raising the bar on the standards we set for ourselves.

View all cases

InspireU — Saudi Telecom Company

Building a user-centric digital startup accelerator for Saudi Telecom Corp

View case study

Vessel Monitoring — Smec Marine

Remote fleet management for SMEC Marine using IoT, edge & cloud

View case study

QHSE— Majid Al Futtaim

Ensuring < 1% accident rate with a customized EHS application

View case study

IaaS Automation — Vodafone Global

3-minute infrastructure provisioning at Vodafone Global using Camunda automation

View case study

Clients

PiServe is right behind our clients and their success

Our clientele, who range from Fortune Global 500 corporations to technology disruptors across various industries, desire the finesse we possess and the standard at which we deliver.

HOW ARTIFICIAL INTELLIGENCE BENEFITTED BUSINESS

Automation and operational efficiency

AI fosters predictive analytics, permitting businesses to foresee trends, behaviors, and future events. AI’spredictive capability plays an invaluable role in various applications.
AI lays its power on upply chain management, helping businesses forecast demand more accurately. Analyzing historical sales data, market trends, and external factors like weather patterns permits enterprises to optimize inventory levels and reduce excess stock or stockouts.
AI-powered route optimization and predictive maintenance ability revolutionize the transportation industry. AI algorithms examine traffic patterns, weather conditions, and performance data of vehicles to recommend the most efficient routes for delivery trucks. Predictive maintenance algorithms predict the chance and the likeliness of the ailure of equipment and vehicles, aiding businesses to perform maintenance before costly breakdowns occur.
AI predictive models in healthcare help medical personnel identify patients at risk of specific diseases or medical conditions. Through a thorough analysis of patient data and medical histories, AI systems predict who is most likely to develop certain conditions, encouraging early intervention and enhanced patient outcomes.

HOW ARTIFICIAL INTELLIGENCE BENEFITTED BUSINESS

Data-driven decision making

AI has the capability of processing and analyzing bulk amounts of data swiftly and accurately, empowering businesses to make more informed decisions. Machine learning (ML) algorithms, a subset of AI, excel at uncovering patterns, trends, and insights from complex datasets.
For example, in the retail sector, AI algorithms analyze customer purchase history, online behavior, and preferences to craft personalized product recommendations, which eventually leads to increased sales and improved customer satisfaction.
In healthcare, diagnosing diseases by analyzing medical images, such as X-rays and MRI scans, is faster and more effective with AI. Artificial intelligent systems detect anomalies and patterns that human radiologists miss, resulting in earlier and more accurate diagnoses.
In healthcare, diagnosing diseases by analyzing medical images, such as X-rays and MRI scans, is faster and more effective with AI. Artificial intelligent systems detect anomalies and patterns that human radiologists miss, resulting in earlier and more accurate diagnoses.

HOW ARTIFICIAL INTELLIGENCE BENEFITTED BUSINESS

Personalization

AI has revolutionized customer experiences with massive scale personalization. Businesses can offer deep customization on their products, services, and marketing efforts to the preferences and needs of individual customers.
For instance, eCommerce platforms leverage AI-powered recommendation engines that analyze a customer’s past purchases, browsing history, and behavior on the platform to recommend products that are most likely to be appealing. As a result, customers receive a more customized shopping experience, leading to higher conversion rates and augmented customer loyalty.
Driven by natural language processing (NLP) engines, chatbots, and virtual assistants provide personalized customer support. These AI-powered communication agents can conduct natural conversations with customers, answer questions, resolve issues, and guide them with purchasing. This 24×7 support reduces response times and improves customer satisfaction.
AI casts its power in the marketing sector. The technology helps marketing teams handle customers more effectively and enables businesses to send targeted marketing messages and advertisements to the target audience. AI gives marketing teams a precision that improves conversion rates and the return on investment (ROI) for their campaigns.

HOW ARTIFICIAL INTELLIGENCE BENEFITTED BUSINESS

Predictive analytics

AI fosters predictive analytics, permitting businesses to foresee trends, behaviors, and future events. AI’s predictive capability plays an invaluable role in various applications.
AI lays its power on supply chain management, helping businesses forecast demand more accurately. Analyzing historical sales data, market trends, and external factors
like weather patterns permits enterprises to optimize inventory levels and reduce excess stock or stockouts.
AI-powered route optimization and predictive maintenance ability revolutionize the transportation industry. AI algorithms examine traffic patterns, weather conditions,
and performance data of vehicles to recommend the most efficient routes for delivery trucks. Predictive maintenance algorithms predict the chance and the likeliness of the failure of equipment and vehicles, aiding businesses to perform maintenance before costly breakdowns occur.
AI predictive models in healthcare help medical personnel identify patients at risk of specific diseases or medical conditions. Through a thorough analysis of patient data and medical histories, AI systems predict who is most likely to develop certain conditions, encouraging early intervention and enhanced patient outcomes.

TECHNOLOGIES

Technologies

Developing an AI solution according to your needs involves a structured approach to assure its success and effectiveness.
Our expert AI developers ensure the project’s success by following a systematic process in building your artificial intelligence solution.

Natural Language Processing

Natural language processing (NLP) is a branch of artificial intelligence that focuses on powering computer systems to understand, interpret, and generate human language by leveraging a combination of linguistics, computer science, and machine learning techniques to analyze and process text and speech data. From chatbots to virtual assistants, NLP empowers a wide range of applications that engage in conversations with users across platforms.

Computer Vision

Computer vision utilizes AI technology that uses visual information as a data source. Visual feed from surveillance cameras or other media acts as the data input for the AI systems to work on, enabling computers to analyze, understand, and interpret the information. Computer vision includes tasks like object recognition, image classification, and facial recognition.

React Native

React native is an ideal framework to build cross-platform mobile applications. Our developers use the technology to create native mobile app experiences for iOS and Android platforms. React native reduces development time and effort as it requires a single codebase for both platforms. We built highly responsive and dynamic mobile applications with a native look and feel.

Machine Learning

A subset of AI, machine learning (ML) empowers computers to learn and make decisions or predictions without explicit computing. ML uses algorithms and statistical models to study and interpret data, setting systems on a path of learning and self-discovery based on data sets. With great versatility and adaptability, ML revolutionizes how we solve complex problems and extract valuable insights from large datasets.

Java

Java is a powerful programming language that has a solid impact on the software development industry. Java enjoys platform independence, letting programmers write code once and run it anywhere, making it an ideal choice for cross-platform applications.
Java’s impact spans a wide range of scalable and reliable applications, from web and mobile development to enterprise level software and Android app development.

Python

A versatile and user-friendly language, Python is a programmer’s favorite. Python’s simple and readable syntax, along with a vast availability of libraries and frameworks, makes it a perfect choice for web development, artificial intelligence, data analysis, machine learning, and more, empowering developers to tackle complex problems efficiently. With high scalability and adaptability, Python is the favorite of businesses of all sizes.

IoT

The Internet of Things (IoT) encompasses vast systems of devices connected over a network. IoT enables unprecedented levels of automation, efficiency, and real-time monitoring across industries, from smart homes and wearable devices to industrial sensors and autonomous vehicles. IoT generates humongous volumes of data, which we use for attaining actionable insights, enhancing decision-making, and fine tuning processes.