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Giga AI

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

Platform
YouTube
Length
2:13
Spoken language
English
Views
1.2K
Median cut
4.16s
Face on screen
100%
Dark frames
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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Transcript of Multi Party Coordination: How Giga’s AI Resolves Real Time Delivery Conflicts

Transcribed by a speech model from the film's own audio, not written by the brand. Click any line to jump the film to that moment.

  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 lines · 483 words

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