Artificial Intelligence is developing fast, and you can easily be left behind by competitors. Companies are struggling to get started with AI, even if they think their business model requires AI-oriented thinking.
At Excelacom, we provide a complete range of consulting services required for the inception, cultivation, and implementation of your AI strategy. We offer an all-in-one AI package, which consists of strategy consulting, technology IT services for AI implementation strategy and products, along with solutions for specific areas of applying AI.
By adopting AI at the core of our operations, we have learned that the implementation of AI in business operations requires the identification of successful business models – start simple and scale-up. We assist companies in identifying problems that can be solved using AI technologies and applying the crawl-walk-run strategy that shakes out the details of your AI development and production practice.
Century data analytics platform helps perform data analytics as a complete package to gain more insights from the past.
We can leverage our data analytics platform by automating complex business processes and providing unified access to information:
The best-in-breed set of AI tools offering a highly flexible environment for analysts and users to build solutions for complex problems, leveraging a suite of integrated Machine Learning algorithms without the need for costly and time-consuming coding.
Our company offers a set of solutions built on our platform that can be integrated with your business and operations systems to:
Use process definition, process input, execution steps, timing info., and outcome to determine process success rate, execution time, and root cause analysis for failed processes.
Insights the model will learn consist of:
Provide customers the ability to reduce the number of defects by identifying components that are at risk to raise awareness regarding those areas during development and QA process.
The offering builds a predictive model by applying machine learning on:
Use customer demographics, order lifecycle, historical trouble tickets, and available assets to create an offer that best fits each customer’s needs.
Insights the model will discover consist of:
For more information on Century AI solutions and how it will benefit your company, please visit us on:www.century-ai.com
Excelacom AI platform features scalability, performance, cost-effectiveness, and ease of operation advantages over the conventional RDBMS. Users will be able to view different analyzed information, such as total sales in a given period, and be able to compare it to any other desired period. Additionally, have access to visual cues, for instance, graphs to enable executives to easily view trends and react accordingly to market shifts, by leveraging Century Analytics to construct more KPIs, charts, and graphs.
As the amount of data, analytic complexity, and number of end-users increases, analytics platforms offer a variety of options that can help reduce costs and further help in achieving a properly informed decision.
We provide various options to ingest data from various open-source tools such as Sqoop, Flume, Kafka, and NiFi or even file transfer options using Hadoop.
Provides features for effectively managing data to gain insights.
Features for advanced analytics and machine learning for predictive analytics.
Enriched with powerful security mechanisms to govern the data, make it secure from outside threats and available for the right people at the right time.
Century AI Platform is a highly automated machine learning system for creating data science applications and services.
It enables people with ML or data science expertise to build high-quality models without extensive knowledge of math, statistics, programming, and business intelligence.
Sources
use various sources of information
Datasets
use the defined sources to create the datasets
Models
make predictive models
Predictions
generate predictions based on the model
Ensembles
Create an ensemble of various models
Evaluation
verifies model against validation sets
Create data science workflows without the need for coding and build machine learning models. Choose different algorithms to build your workflows. Model each step of your analysis, control the flow of data, and ensure your work is always current. Connect to a host of databases and data warehouses to integrate data from Oracle or different file formats.
Derive statistics, including mean, quantiles, and standard deviations, or apply statistical tests to validate a hypothesis. Integrate dimension reduction, correlation analysis, and more into your workflows.
Aggregate, sort, filter, and join data either on your local machine, or in-database.
Clean data through normalization, data type conversion, and missing value management. Detect out of range values with outliers and anomaly detection algorithms.
Extract and select features (or construct new ones) to prepare your dataset for machine learning. Manipulate text, apply formulas on numerical data, and apply rules to filter out or mark samples.
Build machine learning models for classification, regression, dimension reduction, or clustering, using advanced algorithms including tree-based methods, and logistic regression.
Optimize model performance with hyperparameter optimization, boosting, bagging, stacking, or building complex ensembles.
Validate models by applying performance metrics, including Accuracy, R², AUC, and ROC. Perform cross-validation to guarantee model stability.
Make predictions using validated models directly, or with industry-leading PMML, including on Apache Spark.
Visualize data with classic (bar chart, scatter plot) as well as advanced charts (parallel coordinates, sunburst, network graph, and heat map) and tailor them to your needs.
Display summary statistics about columns in a table and filter out anything irrelevant.
Export reports for presenting results to stakeholders. Store processed data or analytics results in many common file formats or databases.
Build workflow prototypes to explore various analysis approaches. Inspect and save intermediate results to ensure fast feedback and efficient discovery of new, creative solutions.
Scale workflow performance through in-memory streaming and multi-threaded data processing.
Eliminate areas of failure
Summarized metrics provide details related to process non-compliance and enable the identification and mitigation of failures in a timely manner.
Increase productivity
Predictive and Adaptive Analytics based on KPIs, assist businesses with efficiently measuring and effectively driving improvements in productivity.
Improve customer experience
Valuable and detailed data insights enable proactive monitoring and detection of improvement opportunities, which drive actions that directly improve the overall customer experience.
Integrate data management
Consolidation of data from disparate systems eliminates the guesswork in business decision making and provides accurate, timely, and real-time data.
Create data visibility and accountability
Rich data visualization, custom dashboards, and scheduled notification alerts provide executives with access to real-time data at their fingertips without dependence on IT.
Accelerate revenue
Enhanced 360-degree view of customer data provides a greater understanding of customer behavior and drives refinement of service offerings that meet customer’s needs and demands while increasing revenue.