Orion Digital Solutions

AI & Data Science

In the fast-paced realm of today’s technology and the complex landscape of modern business, companies will struggle to keep up without the reinforcement the support of AI. Let us guide you in unlocking your full potential of your data with the power of AI.

Our AI & Data Science Services

AI Strategy

Tailored guidance for integrating AI solutions into your business model, fostering innovation and growth.​

AI Discovery

Uncover transformative AI opportunities within your operations, enhancing efficiency and competitiveness.​


Rapid creation of AI prototypes to visualize concepts and refine strategies before full-scale implementation.​

Analytics & Insights

Collaborative sessions led by business and technical experts, analyzing data to offer actionable, data-driven recommendations for resolving business challenges.​

Data Strategy & Governance

Customized approaches to manage, process, and leverage data assets effectively for informed decision-making.​

AI Solution Development

Seamless transition from AI prototypes to full-fledged systems, ensuring optimized performance and scalability.​

Cloud & Big Data

Harness the power of cloud and big data technologies for efficient storage, processing, and analysis.​

Generative AI & GPT

Unlock creativity and automation with cutting-edge generative AI models like GPT, redefining possibilities.​


Azure ML

AI & Data Science Use Cases

AI Based Stock Replenishment

Built a replenishment AI prediction model based on historical distributor consumption, improved seasonality factors, and additional market/customer specific statistics that further boost prediction accuracy. Through applying inventory management models and distributor stock, the tool recommends the optimized orders for each distributor coupled with an operational dashboard that helps replenishment planners provide context to replenishment predictions and enable final decision making.

Customer Segmentation

Customer segmentation can help businesses better understand their customers’ needs and preferences, which can lead to more effective marketing and sales campaigns. Orion AI boosts businesses with the ability to analyze large amounts of customer data and behaviors to segment their customers into clusters using state-of -the-art machine learning techniques. This helps businesses identify hidden patterns and insights that would be difficult to find using traditional methods.

Sales Forecasting and Prediction

Our Cutting-Edge Forecasting Solution: Redefines sales projection dynamics. Harnessing advanced techniques, we predict sales trends with precision. Through advanced ML Models, we anticipate market shifts and demand patterns. Our platform empowers informed decision-making, enabling proactive inventory management and resource allocation. Visualize future market scenarios through intuitive dashboards, aligning strategies for optimal growth.

Intelligent Document Processing

Our Intelligent Document Processing Solution leverages cutting-edge AI technologies to empower businesses. Through automated data extraction, classification, and analysis, we streamline document management, enhancing both efficiency and accuracy. By harnessing ABBYY and Azure, we implement advanced OCR solutions that revolutionize document processing. We seamlessly integrate document processing with RPA for a more efficient and holistic automation system.

Human-Like Chatbots

Our Human-Like Chatbot Service harnesses the latest LLM models and cutting-edge technology to empower businesses. Through context-aware, personalized interactions, we enhance customer satisfaction and streamline operations. With continuous learning, our chatbots evolve to meet your company’s changing needs. Experience the future of customer engagement today.

Audio Transcription & Sentiment Analysis for Call Center Quality Assurance

This AI-based call quality assurance solution has been designed to optimize the process of call reviewing and reporting, making it nearly real-time. By using state-of-the-art natural language processing techniques, the solution can listen to calls and generate profiling reports for agents. These reports can be used to guide performance measurement and training.

Vision-based Hypermarkets Analytics Tool

Utilizes advanced computer vision for customer behavior insights and store operations. Tracks footfall, movement, and interactions, aiding layout optimization. Generates heat maps, predicts stock shortages, and features an intuitive dashboard for accessible insights

AI & Data Science Across Industries

  • Customer Segmentation
  • Stock Level Prediction
  • Sales Forecasting
  • AI Based Item Search
  • Customer Behavior Detection
  • AI Based Replenishment
  • Automatic Documents Processing
  • Supply Chain E2E Visibility
  • Shipping Delays Prediction
  • Sales Forecasting
  • Predictive Maintenance
  • Demand Forecasting
  • Intelligent Scheduling
  • Digital Twin
  • Plant Simulation
  • Credit Scoring
  • eKYC
  • Fraud Detection
  • Intelligent CRM
  • Compliance
  • Predictive Maintenance
  • Network Optimization
  • Virtual Assistants
  • Customer Churn Analysis
  • Data Driven Marketing and Sales


Planning & Design

Data Source Evaluation and Model Design
Examining data sources for consistency, availability, and accuracy to enable the development of data models.

Data Integration
Implement data pipelines and integrations to enable analytics and data science capabilities. Implement, improve or migrate data warehouse solution to consolidate disparate data sources under one roof and enhance company-wide decision-making.

Implementation & Delivery

Factory Delivery Model
Deliver hundreds of automations through program-scale delivery model working on continuous pipeline discovery and requirement documentation across multiple teams & functions and feeding into our global factory delivery team which handles development, testing, validation & deployment of automated processes.

Staff Augmentation Delivery Model
Our certified solution engineers and solution designers can be offered to our clients to work within their Agile delivery teams, leveraging the best practices from Orion’s delivery methodology

Service Operations

L1 Support Services
Monitoring dashboard periodic data refresh,
identifying inconsistencies, and performing data reloads where possible to ensure data consistency.

L2 Support Services
Incident root causing, bug fixing, testing and deployment back to production.


Artificial Intelligence, often abbreviated as AI, is a multidisciplinary field of computer science that focuses on creating machines, software, or systems capable of performing tasks that typically require human intelligence. These tasks include problem-solving, learning from experience, understanding natural language, recognizing patterns, and making decisions. AI technologies aim to simulate human-like cognitive functions and can be applied in various domains to automate processes, analyze data, and provide insights to improve decision-making and efficiency.

AI and Data Science have diverse applications, including recommendation systems (like Netflix or Amazon), autonomous vehicles, fraud detection, healthcare diagnostics, and chatbots for customer support. Check our AI & Data Science Across Industries section for more cases.

AI and Data Science solutions require relevant, high-quality data. The specific data needed depends on the project but often includes historical data, structured and unstructured data, and domain-specific information.

Assess your readiness by considering factors such as available data, budget, expertise, and the alignment of AI with your business goals. Start with a clear AI strategy, pilot projects, and training programs to ensure successful implementation. We can help you to do this assessment through our experienced consulting and tech team.

AI can enhance customer experiences by personalizing recommendations, automating customer support through chatbots, improving product or service quality through predictive analytics, and offering real-time insights into customer behavior and preferences.

Challenges include data quality, lack of AI talent, ethical considerations, regulatory compliance, and company culture. It's crucial to assess the company's situation very well to know the actual stage you are in in order to determine the best strategic plan to adopt and integrate AI successfully.

The post-implementation phase is crucial for the successful adoption of a business intelligence application.

First, it is important to ensure that all users are trained on how to use the application. This includes both the technical aspects of the application and how to interpret the data that is provided by the application. Second, an adopter should establish clear goals and KPIs for the application. This will help ensure that the application is being used to its full potential and that it is providing the most value to the business. Finally, regular maintenance and support activities help ensure low incident occurrence, proactive issue resolution, and reduced total cost of ownership.

Our experienced BI technology experts help organizations maintain BI applications and elevate existing BI solutions including analytics, reporting, ETL, and others. We are well-versed in a wide range of business intelligence platforms and databases to provide individual maintenance cadence for unique needs.

The life cycle of an AI project typically begins with identifying a specific business problem or opportunity. Next, a Proof of Concept (PoC) is built to validate the feasibility of the AI solution. After PoC success, data collection and preprocessing occur, followed by model training and validation. Deployment of the AI model in the production environment is the next step. Continuous monitoring, fine-tuning, and maintenance are essential to ensure the AI system's effectiveness and relevance over time. Finally, the AI project concludes with performance evaluation and ongoing optimization to address evolving business needs.

The choice between cloud and on-premise AI implementation depends on factors like data security, scalability, and IT infrastructure. Cloud solutions offer scalability, flexibility, and managed services, making them ideal for many organizations. On-premise solutions offer more control over data but require substantial hardware and maintenance.

Data analytics is a term used to describe the various tools and techniques used to extract insights from the existing data. This includes everything from visualization and machine learning to more traditional methods such as statistical analysis. The technology is constantly evolving, and new tools and techniques are being developed all the time. Our company selects a custom combination of methods and techniques to address the unique needs of a particular client
Data analytics as a service is used for a variety of purposes, from analyzing customer insights to understanding images and videos. It is a way to outsource the data analytics development process to companies that can share their expertise and reduce the costs of hiring an in-house team.
Some of the services that a data analytics company can provide include data mining service, analysis, predictive modeling, and more. They can help organizations to make better decisions by providing insights that would not be apparent from looking at the input alone. Data experts can also help to improve the efficiency of decision-making by automating the process of input analysis.

Many companies are using data analytics and innovation to make better decisions and improve their businesses. Here are some of the benefits that data analytics service providers can deliver for your company:

o Improved decision making: make better decisions by analyzing input and finding patterns.
o Improved customer service: understand your customers better and provide them with better service.
o Improved efficiency: automate tasks and processes, making your company more efficient.
o Improved financial performance: optimize your business to improve your financial performance.

The overriding objective of Big data for development is to uncover trends, patterns, and hidden relationships in vast datasets. Analytical solutions can process any type of data, whether it’s structured or unstructured. They also help devise new business opportunities and the optimum strategic moves.
Big data analytics provides the raw material for AI-enabled systems to surface actionable insights from your data. With this synergy, you can embrace advanced analytics capabilities more easily, including augmented or predictive analytics solutions.
BI adoption is a process of transforming the business into a data-driven organization by integrating effective data processing, analytics, and visualization across the enterprise. It includes using information technology to transform raw data into useful information that can be used to make decisions and take action. Organizations that aim to implement a business intelligence solution have to consolidate multiple databases into one central repository that can be accessed by all employees, making it easier to manage the business and dig up insights.

BI excellence helps companies organize and make sense of their assets so that they can be easily tracked and analyzed. Decision-makers can then drill down and get the input they need quickly, empowering them to act proactively.
Implementing an intelligent data solution also allows companies to accrue the following benefits:

o Improved decision-making. The use of data mining, extraction, and analysis tools can help the business to make better decisions, spot trends and new business opportunities.
o Reduced risk management costs. Businesses that implement BI systems tend to minimize their risk management costs because they can identify potential risks before they occur and act proactively.
o Better customer experience. This can be achieved through enhanced customer relationship management systems that use data analytics techniques to improve sales and marketing strategies and using predictive analytics techniques to predict customer sentiment.

Power BI implementation cost depends on the project complexity, data quality, sources, deadlines, etc. Thus, if the company has a mature infrastructure with consistent data governance practices, the costs will be lower than developing the whole infrastructure from scratch.

With a choice so wide, it can be challenging for companies to land the right tech partner. The main selection criteria include:

o Tech expertise – a diverse set of skills, credentials, and certifications in the field of data, artificial intelligence, and related technologies.
o Projects in your or adjacent domain – a relevant portfolio with similar projects, preferably showcased on a provider’s website.
o Future maintenance and support opportunities – post-production support to address any issues after deployment.
o Strong employer brand – industry awards, positive testimonials, and unequivocal positioning.
o Reliability & transparency – all terms and conditions are documented in a transparent agreement.
o Communication & agility – direct client engagement in the project, regular communication via a single communication channel, and change-friendly project management.

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