Usually, the idea sounds simple: add a neural network to a mobile app. But then practical questions arise: where to place the solution? How to integrate it into the existing infrastructure?

For such scenarios, MWS Cloud Platform offers MWS GPT Model Hub — a service for working with AI in the cloud. It is aimed at developers and allows you to assemble the necessary project components in a single cloud environment.

For example, an online store team wants to launch an AI assistant for customer support. It should analyze the customer's question, find the necessary information in the knowledge base, and suggest a draft response to the operator.

Here's what such a scenario might look like:

1. Place the application and its server side in the cloud infrastructure.

2. Store the knowledge base, instructions, and other materials in cloud storage.

3. If necessary, use a database to store embeddings and RAG pipeline data.

3. Connect the AI model to the application via GPT Model Hub.

4. Configure the logic: the customer's request enters the system, the model generates a response option, and the operator reviews and sends it.

5. After testing, the solution can be gradually scaled to real load and new scenarios can be added: classification of requests, preparation of brief summaries, or search for information in internal documents.


As a result, developers do not need to assemble infrastructure from disparate components. They can focus on the product itself, test a hypothesis, and move faster from prototype to working solution.

You can test MWS Cloud Platform with a welcome grant.

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