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AWS Details Multimodal WhatsApp Ordering Assistant Built on Amazon Bedrock AgentCore

AWS demonstrates how to deploy a multimodal WhatsApp assistant using Amazon Bedrock AgentCore and Amazon Nova 2 to handle orders across text, voice notes, and calls on a single number.

This article was AI-generated and published automatically. Context, labelling and all sources at the end of the article.

(KI-generiertes Symbolbild: Gemini / AI Connect)

AWS has outlined how to deploy a multimodal WhatsApp ordering assistant designed to handle transactions across several communication formats. The system is built on Amazon Bedrock AgentCore with Amazon Nova 2. Through this architecture, the assistant takes customer orders through text, voice notes, and real-time voice calls on a single business number.

The underlying design maintains a strict structural division, ensuring the channel and ordering layers stay separate. To maintain continuity across interactions, the system relies on one shared memory that recognizes each customer across all three channels. This arrangement allows the assistant to support diverse input types on one number while managing customer recognition through unified memory.

What this means for you

By keeping the channel and ordering layers separate, businesses can decouple communication endpoints from order-processing logic. Furthermore, operating a single business number backed by shared memory allows organizations to maintain consistent customer context across text, voice notes, and voice calls.

Evidence

Solidly sourced
46/100

  • The ordering assistant runs on Amazon Bedrock AgentCore paired with Amazon Nova 2.

    single source
    Quote

    „built on Amazon Bedrock AgentCore with Amazon Nova 2“

    AWS, Machine Learning

  • The assistant processes customer orders via text, voice notes, and real-time voice calls on one business number.

    single source
    Quote

    „takes customer orders through text, voice notes, and real-time voice calls on a single business number“

    AWS, Machine Learning

  • The implementation keeps the channel layer separate from the ordering layer.

    single source
    Quote

    „The channel and ordering layers stay separate“

    AWS, Machine Learning

  • A single shared memory recognizes each customer across all three channels.

    single source
    Quote

    „one shared memory recognizes each customer across all three channels“

    AWS, Machine Learning

Sources

The evidence score is computed, not hand-set: from confidence, the number of sources and the share of verified statements.

Source & transparency

As of: September 04, 2026

AI-generatedAI-generated: produced automatically from vetted sources with technical quality checks (source, quote and figure verification); no human sign-off of each item before publication

Sources
1
Verified statements
0 / 4
Evidence score
46Solidly sourced
AI AgentsUse CasesGenerative AI

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