Partnership
Credera and Amazon Web Services Machine Learning
Advancing artificial intelligence and machine learning capabilities at scale.
Overview
Why our partnerships are different.
As an AWS Premier Consulting Partner, we advise clients and deliver end-to-end AWS solutions that unlock innovation and increase flexibility, scalability, and security to accelerate business goals and growth.
Amazon Web Services Machine Learning Capabilities
AWS Machine Learning Offerings
Artificial intelligence (AI) is a strategic priority for more than 80% of companies’ corporate roadmaps, yet over 80% of all AI projects will never make it past the proof-of-concept stage. Most organizations will fail to scale their AI and machine learning (ML) models. Other organizations with outsourced AI and ML capabilities will be stuck with a black box solution with no control and no understanding of how it predicts and recommends.Using the scalability of managed services like Amazon SageMaker on AWS, we equip our clients with advanced capabilities within data science, ML, and AI at enterprise scale to better target customers, improve customer experiences, optimize inefficiencies, and lead the market.
Data Monetization Strategy & Platform
Discover the three basic ways to create enterprise value through data monetization: improve internal efficiency, enrich current offerings, or monetize directly. Then, architect a platform using the latest technology from AWS to build a product factory that can take these monetization plays from idea to product quickly.
Data Product Delivery
Deliver products that realize the value of your data assets with a modern data product delivery lifecycle that fuses business planning, experience design for the product front-end, data science built on the Amazon Sagemaker platform, and data engineering using AWS tooling like EMR and Glue.
Machine Learning Model Operations (MLOps)
Bring your models to Production with an integrated enterprise architecture, operating model, and data product ecosystem. Our teams can address common ML challenges with a unified AWS architecture, automate operations tasks, and improve the value of machine learning investments.
Unstructured Data Extraction & Processing
Extract previously inaccessible data from unstructured documents, classify it, generate knowledge graphs, and enable the development of new data products for your organization. Leverage services like Amazon Textract and Amazon Rekognition to generate training data and build computer vision and NLP solutions with Amazon SageMaker.
Descriptive & Predictive Analytics
Leverage AWS technology to build descriptive and predictive analytics solutions that unlock the value of your data and deliver predictive analytics to guide business decisions. In addition to delivering well-architected machine learning and analytics solutions, Credera upskills client organizations in modern data patterns, introducing teammates to advanced techniques and working with them to learn and grow their model-building capability.
Anomaly Detection & Insights
Leverage machine learning to detect anomalies and alert users with a call to action. Then, analyze the alerts and detect trends that unlock insight from the patterns, reducing alert fatigue with actionable intelligence. Credera’s anomaly detection and trendspotting approach matches a deployment technology (e.g., Kinesis Analytics, Spark ML, or SageMaker) with the real-time needs of each data stream and applies advanced algorithms (e.g., Random Cut Forrest, Prophet, etc.) that account for multiple forms of seasonality / periodicity. This delivers a sustainable trendspotting process with timely insights to guide business decisions.
Case Studies
See how we solved these challenges for our clients.
Related Insights
Client Success Stories
Here are a few clients we’ve partnered with Amazon Web Services Machine Learning.
Here are a few clients we’ve recently worked with to identify valuable solutions through a similar discovery conversation.
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