वीडियो पर वापस

Giga AI

Multi Party Coordination: How Giga’s AI Resolves Real Time Delivery Conflicts

प्लैटफ़ॉर्म
YouTube
अवधि
2:13
बोली जाने वाली भाषा
अंग्रेज़ी
व्यूज़
1.2 हज़ार
औसत कट
4.16s
स्क्रीन पर चेहरा
100%
गहरे फ़्रेम
83%
Giga AI Multi Party Coordination: How Giga’s AI Resolves Real Time Delivery Conflicts at 0:00medium presenter
Giga AIMulti Party Coordination: How Giga’s AI Resolves Real Time Delivery Conflicts
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Multi Party Coordination: How Giga’s AI Resolves Real Time Delivery Conflicts की ट्रांसक्रिप्ट

फ़िल्म के अपने ऑडियो से एक स्पीच मॉडल द्वारा लिखा गया, ब्रांड द्वारा नहीं। उस पल पर जाने के लिए किसी भी पंक्ति पर क्लिक करें।

  1. 0:00I ordered DoorDash here, and for some reason I have to go back to my office.
  2. 0:05And I go back to my office, I call the Dasher and tell them that,
  3. 0:09hey, my office is on the way, why don't you just drop the food there?
  4. 0:13And generally, like, you know, Dasher's are nice people.
  5. 0:16And then since it's also on the way, they would most definitely do it.
  6. 0:20So they would drop it off there, and I take my order, I go back into my office,
  7. 0:25and they are stuck outside my building.
  8. 0:27They're trying to mark the order as delivered on the app,
  9. 0:29and they cannot because they are far from the original delivery address which is like the studio
  10. 0:34what do they do like they reach out to support they're like hey i am stuck in this delivery i'm
  11. 0:39i cannot move forward to my next delivery and then our ai right now answers this so our ai is going
  12. 0:45to understand like what is the issue what error messages are you seeing and everything and then
  13. 0:49it finally comes to the conclusion that oh this is actually because the customer requested an
  14. 0:54a test change, which is not present.
  15. 0:58So what we do right now in production is we check the chat history between me, the customer
  16. 1:04and the Dasher and see whether I request an test change.
  17. 1:06Since I called the Dasher, there's nothing you can find.
  18. 1:10So this is a use case, which is in production right now.
  19. 1:13We make an outbound call to the customer who is me.
  20. 1:17So an AI agent, which is on a call with one person already, which is on a call with the
  21. 1:21Dasher is going to make another call to customer and it's going to synchronize two different
  22. 1:26conversations at the same time. It's going to call me. It's going to say, hey, did you order your,
  23. 1:31did you request your burrito to be delivered to a different address? Because that's what the
  24. 1:35Dasher is claiming. And then I being the customer, I can like, you know, I'll say, yes, yeah, I
  25. 1:39actually got it delivered to a different address. Now this other AI agent, which is still on a call
  26. 1:43with the Dasher, the Dasher can still talk to it about anything they want while this other
  27. 1:47conversation is happening. So that part was not possible with humans before. Previously,
  28. 1:52like, you know, what did humans used to do? So they would call the customer, put the Dasher on hold,
  29. 1:57and the Dasher is stuck waiting on hold for like two to three minutes. And even if they have other
  30. 2:02issues, they just cannot do anything. While that is happening, the Dasher will talk to the AI and
  31. 2:07the customer confirms the receipt of the order. And eventually, like, you know, the AI is going
  32. 2:11to resolve the ticket.
32 पंक्तियाँ · 483 शब्द

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