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Generative AI in 30 days implementation: A DPi30 offer
The Generative AI in 30 days offer is designed to help organizations analyze generative AI use cases and rapidly prepare for deployment of generative AIs.
Generative AI, such as OpenAI’s ChatGPT, is unlocking numerous new use cases for AI in organizations. As with any new technology, however, there is a lot of hype and uncertainty about what it can do, making working with a leader in AI, like Fractal Analytics, essential to help cut through the noise.
The Generative AI in 30 days offer is designed to help organizations analyze generative AI use cases and rapidly prepare for deployment of generative AIs. The offer achieves this by leveraging predefined resource deployment procedures and templates from Microsoft and Fractal Analytics.
As a part of this offer, AI experts at Fractal Analytics will work with client stakeholders to understand the client's business challenges and identify generative AI use cases in a discovery workshop. From the workshop findings, Fractal consultants and engineers will advise the client on the best approach for implementing their use case and create an initial architecture.
Once the architecture is agreed upon, Fractal will then implement generative AI capabilities and establish a landing zone on Azure for any data the customer needs to use with their models. Once data has been populated in the landing zone, Fractal will then work with the client to build out the generative AI proof of concept and provide the client with a go-forward plan aligned with resourcing and architectural requirements for bringing the POC to production.
By taking part in this offer, organizations will a proof of concept for one generative AI use case defined by the customer, plus gain a data landing zone built on Microsoft Azure. The landing zone will feature built-in geo-redundancy and high availability architectures, globally available data storage and analytics tools, auto-scaling, and cost-effective, pay-as-you-go resources.
Please note: Final cost varies based on project size & funding availability.