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PKSHA ChatAgent powers NTT Docomo's follow-up-asking support AI

PKSHA ChatAgent powers NTT Docomo's follow-up-asking support AI

3 Key Points

  1. What happened

    PKSHA Technology provided the conversational AI agent feature of its AI SaaS "PKSHA ChatAgent" to NTT Docomo's "Online Procedure Support" desk for contract and billing procedures.

  2. Why it matters

    The generative AI confirms a customer's intent by interacting with them, then narrows down the needed information while referring to procedure data and FAQs, so customers are not required to phrase their questions correctly.

  3. What to watch

    The design targets short inputs like "rate change" or "plan change," which are hard to pin down by intent, so whether the AI narrows intent accurately is the test.

WHO IT HITSThis lands on customer support and contact-center teams at telecom carriers, who handle complex contracts, rate plans and eligibility conditions. It may also affect teams building self-service online procedures, since the AI is meant to guide customers from vague input to the right step.

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Context & Analysis

NTT Docomo customers do not always send fully formed questions. Short phrases like "rate change" or "plan change" make it hard to tell what the customer actually wants, and trying to be accurate often produces long explanations instead. In telecom services in particular, contract details, rate plans and eligibility conditions have grown complex, and online procedure options have multiplied, so a system that can guide customers to the right information even when they leave out the premises has become necessary.

Against that backdrop, PKSHA Technology provided the conversational AI agent feature of its AI SaaS "PKSHA ChatAgent" to NTT Docomo's "Online Procedure Support." The approach deliberately abandons the premise of making customers ask correctly. The generative AI talks with the customer, confirms the intent of the question, and narrows down the information while referring to procedure information and FAQs.

The test is likely to be whether the follow-up questions actually converge on the right intent when the input is only a few words. For support teams at carriers, the payoff hinges on whether this reduces the effort customers spend hunting for the right FAQ or procedure, rather than simply adding another layer of conversation.

FAQ
Which desk at NTT Docomo uses this AI?
It is used at NTT Docomo's contract and billing procedure desk, called "Online Procedure Support." The conversational AI agent feature comes from PKSHA ChatAgent.
How is this different from a conventional chat?
With conventional chat, a short message is hard to interpret, and accurate answers tend to run long. Here the generative AI confirms intent through back-and-forth and narrows down the needed information.
What kinds of customer questions are targeted?
Short inputs such as "rate change" or "plan change." Because these omit the customer's background, the intent is hard to identify from the words alone.

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