The growing digitization and connectivity of all things alongside the massive rise in computing power has made data analytics a critical priority of every business executive today. And many are looking to AI to offload specific cognitive tasks and gain speed, cost-efficiency and agility. However, many lack a comprehensive approach and roadmap to scale enterprise-grade AI for their business.
Apexon provides consulting, engineering, and packaged software solutions covering the entire spectrum of advanced data application and management — business, financial and technical. Our solutions are based on deep mathematical and statistical foundations and state-of-the-art techniques, including deep learning, machine learning, neural networks, and natural language processing.
We tailor these solutions to your needs, leveraging both on-premises and cloud infrastructure while leveraging the latest AI tools and methodologies to create practical applications that provide the insights needed to enhance customer experiences, accelerate product lifecycles, improve resource allocation, and increase operating efficiencies.
Automated identification and labelling of objects from images and videos. Apexon computer vision analytics services allow businesses to develop a Visual Analytics Processing capability that can enable AI and computer vision-based programs to extract meaningful information from images and videos in near and real-time
Data discovery, wrangling, model-building, model management, model consumption, visualization and workflow management in an integrated platform to accelerate the data science lifecycle.
Identify key insights from unstructured data. Use NLP algorithms to provide smart and self-learning systems that can extract information and insights contained in the NLP system as well as categorize and organize the systems themselves.
Forecast and predict opportunities, customer behavior as well as financial, economic, and market risks of future unknown events, by applying statistical algorithms to historical data.
Accelerating and managing ML model development and deployment lifecycles, using real-time and batch data processing AI/ML use cases and various cloud machine learning features like AutoML, hyperparameter optimization, cloud-based cognitive, bot services and MLOps techniques.
Anomaly detection is a way of discovering outliers in a collection; objects that do not belong there. The significance of anomaly detection derives from the concept that data anomalies translate to substantial (and frequently crucial) actionable information in a wide range of application fields. As more organizations go digital, it’s critical to put in place systems that not only allow you to examine your data after the event, but also foresee and detect abnormalities and new patterns that are necessary for turning data into useful information
As a result of more manageable data and more timely access to critical data.
Feed better data quality into business workflows and gain a more accurate understanding of actual operational performance
Free up data scientists to work on higher-value analytics activities instead of dealing with the complexities of DevOps and data engineering.
Detailed SLA analytics highlight gaps in customer service and support.
Identify and prevent potential legal issues and fines before they become a problem – especially in highly regulated industries like healthcare and financial services.
Via more automated systems, reduced storage requirements, and application/service licensing.
Predictive analytics provide insights into emerging trends, focusing future development and innovation initiatives.
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how we do it
Our partnership with Azure helps organizations move to cloud at speed, increasing application availability, technical flexibility, and security improvements.
20+ years of team experience in delivering large, multi-tenant, heterogeneous enterprise data assets, including ML/AI platforms.
We use a proven, predictable and consistent methodology to guide the data modernization process, developed from decades of data and information management experience.
We apply the foundational principles of data, or “The 4 C’s” – to every data analytics engagement: Curate, Catalog, Context, and Consume. These four principles are critical for every organization to get their data analytics initiatives right.
Our visual storyboards give deep insights into customer behaviour for a more personalized customer experience.
Advanced analytics services are end-to-end engagements offered by specialised providers to help organisations conceive, build, deploy and scale analytic models and solutions that drive real business value. They typically include services such as data discovery and engineering, model development (for predictive, prescriptive or anomaly-detection use cases), MLOps and model governance, and embedding insights into enterprise workflows. From a market perspective, the global advanced analytics market is projected to grow at a compound annual growth rate (CAGR) of ~26.4% between 2025 and 2030, with market size expected to reach USD 305 billion by 2030.
Given this scale, advanced analytics services are increasingly becoming a strategic priority—not just a nice-to-have—enabling organisations to transform data into actionable insight, reduce decision latency, improve efficiencies and ultimately gain competitive advantage.
Analytics and machine learning work together by using data analysis to identify patterns and trends, which machine learning algorithms can then learn from and improve upon. This combination allows for the automation of complex decision-making processes and the development of predictive models that can adapt and evolve with new data.
AI plays a crucial role in advanced analytics by enabling the automation of data analysis, enhancing the accuracy of predictions, and providing more nuanced insights. AI algorithms can process large volumes of data at high speeds, uncovering patterns and trends that traditional analytics methods might miss.
Industries such as healthcare and life sciences, finance, retail, and manufacturing benefit significantly from advanced analytics services. These sectors can utilize data to predict customer behavior, optimize supply chains, improve patient outcomes, and enhance risk management, driving both operational efficiency and growth.
Through our partnership with Apexon, we have been able to achieve many goals. One is to get our platform built with speed by helping our engineering teams and then we have also achieved our infrastructure goals of ISO certifications. Apexon team is helping us deploy the platform even faster from two or three times per week to five or six times a week.
Their(Apexon) attention to detail and continued focus on CD Valet has kind of proved that we made the right decision and we have expanded from one team to multiple teams. We are surveying about 31,000 CD rates on a weekly basis and Apexon plays a very important part in that process.
