AWS machine learning

Advancing artificial intelligence (AI) and machine learning (ML) capabilities at scale.

Capabilities

See how we’re helping our clients.

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 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 Bedrock and 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 and 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 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 and 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 natural language processing (NLP) solutions with Amazon SageMaker.

Descriptive and 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 and 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.

How We Can Help

Harnessing AI to bring business value.

As Premier partners, we have extensive experience using AWS to provide value to our clients. We have been delivering AI and ML services to global clients for many years, meaning we have a coherent MLOps approach that provides the structure needed for long-term success.

Hear from our clients on how it feels to work with us.