Rackspace Technology's AI proof of concept accelerates the value you get out of your data by leveraging AWS and open source AI and ML frameworks and services combined with Rackspace's highly skilled and experienced team of data scientists, architects, and engineers. With our AI accelerator, customers are able to

Prove business value with a fail-fast approach

Yield demonstration capability in a few weeks

Build familiarity with cloud and AI/ML solutions

Bring new insight to business challenge

Make the case for further investment

Throughout the project, Rackspace data scientists and engineers will perform:

Discovery - review data set, attributes, use case and existing heuristics and patterns

Planning & Design - determine appropriate algorithms and data; design architecture for model training and architecture for test and evaluation

Model Development - prepare the data, develop the model, run model training, iterate on design and tune the model

Testing & Validation - test and validate the model, conduct hyperparameter tuning, and evaluate model performance and quality

Reporting & Analytics - package mode code, provide inference endpoint, and conduct knowledge transfer to customer team

At the end of the project, Rackspace Technology will provide:

Prototype model

Architectural diagrams

Implementation guides and documentation

Templates, scripts and code

Empower your data to make automated recommendations, take preemptive action, and streamline decision-making.

Rackspace Technology has deep expertise in data science and engineering to help customers turn data into intelligence. Our deep technical and business expertise combined with leading cloud native AI/ML frameworks, data preparation and MLOps Foundations accelerates AI projects to completion.

Rackspace provides dedicated planning, data science and AI/ML engineering expertise, and automated operations that help customers define the right AI strategy, prepare their data, incorporate AI/ML frameworks into application and data platform development, and maintain and optimize their environment.

Delivery

Typical projects are anticipated to last for four to eight weeks (to be confirmed in the Scoping Document).

Talk to us to about qualifying for AWS funding programs to help startups take advantage of this offer.