label: Colin Heilbut - Rime

text: Ready. Start whenever you say.


text: Good morning. My name is Colin. I'm the newest account executive here at Rhyme. A little bit about me. Gosh. I started many years ago as the


text: first employee for a company called Deepgram.


text: Back then, I was carving out holes in the wall for the GPU clusters and


text: babysitting the, the founder's kids. But I I've stayed in the, the business quite a long time, and,


text: worked for intelligent voice in high security speech recognition.


text: And then more recently at a French Voice AI Lab.


text: Perhaps we could do a quick round of intros on your side, both just


text: your your roles and kind of the relevance of speech to what you do.


text: Sure. Hi. I'm Maya.


label: Voice 2

text: I run contact center operations for us. It's


text: all about call quality and handle time while keeping the experience


text: calm and clear for customers.


text: Hi, David here.


text: IT and Risk,


text: I'm focused on


text: Maya, so you're the marketing director?


text: Not marketing. I'm over contact center operations.


text: Day to day call performance, and agent workflows.


text: Cool. Continue.


text: Thanks. And, as I was saying,


text: hi, David, ITM Risk.


text: My


text: lens is reliability, data handling, and integration.


text: We like measured results before scaling anything.


text: And hi, Priya here, product for digital service.


text: I'm thinking about how voice fits into web and app drays.


text: Making that hand off smooth matters a


text: lot.


text: It was supposed to meet you all today.


text: I just perhaps can start with a a brief overview, but if there's anything you wanted me to add as


text: agenda, we certainly can.


text: As you can see, I'm working with a digital whiteboard here. Quite frankly, I just have the world's worst handwriting.


text: And so I use this to keep track of thoughts and, keep me honest, make sure that we cover all of the


text: individual, concerns you might have and can actually make a plan to see,


text: how Rime might be really applicable to some of your use cases.


text: We I'll talk very briefly about a little bit about what Nick rhymes special, but I really want to focus most of the time today just to


text: discover some of the key issues that you're concerned with and what you really


text: you in today.


text: Afterwards, I did prepare a short live demo


text: We'll see how that goes, and then we have left time throughout the conversation


text: then particularly towards the end for any


text: questions, concerns you might have. Feel free to grill me as hard as you need. I've heard it all before.


text: Lastly, of course, we can talk about next steps and potential ways to


text: really test out rhyme.


text: In a in a structured


text: way,


text: Sound good? Sounds


text: like a solid


text: sorry.


text: Yeah. That sounds like a solid plan. Happy to dig into pain points first.


text: Great. So, a little bit of context on us. We've,


text: been doing this since 2022, believe it or not. I started by two and an engineer.


text: The approach we take is is quite differentiated.


text: You know, a lot of the folks in the industry


text: have had a a good deal of success with, using actors or


text: podcasts, sort of large training sets that are often kind of shared in the industry.


text: And it it it works clearly, but


text: get really nuanced, hyperrealistic speech


text: our approach, involves setting up our own recording studio.


text: So really going from first principles and to have much more natural


text: high fidelity full duplex conversations that allow


text: our models to be quite differentiated from what's out there. And


text: don't naturally take our word for it. We are actually now powering tens of millions of calls, some that you may have even made


text: yourself this month to


text: hospitality or health care, telecom, and enterprise support.


text: We even completed a a really interesting study just recently


text: This was outbound through a third party that


text: was really gonna report


text: commissioned a study, but they're very objective, and we're gonna report whatever they found.


text: And in fact, although no one loves to receive a


text: an unsolicited outbound call, was a a government survey,


text: We found that we had the lowest hang up rate out of any TTS


text: system out there as well as the the fastest time to completion


text: out of a 100,000 calls. So I think that the takeaway here is that we do actually prove


text: produce some of the most delightful engaging voices in the industry.


text: So


text: getting to the the crux of our conversation today, it would be great just to understand a little bit more about


text: how you're generating speech today, what tools, and


text: then what's what's what you'd like to improve


text: Sure. Broadly, we're using a mix of


text: benders


text: and we're not really getting the quality we want


text: Some calls feel flat, you know, robotic,


text: and we worry about that impacting trust.


text: So flat robotic calls are a pain point.


text: Right. Yes.


text: That's a big one.


text: And from my side, we need


text: Plus, integration can't be a science project


text: need something supportable.


text: And from CX and products like


text: we want any voice experience to feel


text: connected across channels.


text: No jarring tone shifts.


text: And so the


text: the flat robotic calls, how significant a problem would you say that is?


text: Noticeable. We see it pop in longer calls.


text: And some customers get impatient. It's not


text: catastrophic, but


text: it's enough that it


text: hits


text: our metrics.


text: And gets flagged in QA.


text: So when when that when that sort of your metrics are impacted


text: how what's the the kind of


text: the bottom line there? What is the the the true impact? And then what would sort of success look like there?


text: Let me just think through that.


text: So for Maya, it's about trust and time.


text: When calls feel robotic, people talk over prompts or ask for re keeps.


text: That's seconds added per call and softer


text: For David,


text: success means better CX without adding risk.


text: Plus a clean integration.


text: And for Pria, it's a consistent journey of cost


text: channels. No jarring handoffs. If the voice feels


text: natural and on brand, that's progress.


text: Put that together, success could look like reduced handle time,


text: steadier CSAT or QA scores, and positive agent feedback


label: Voice 3

text: on


text: conversations feeling smoother.


text: And what are


text: these are all sort of


text: KPIs. How what's the true measure


text: of


text: success? What is the bottom line business impact here?


text: One second.


text: Great. So bottom line, it's cost to serve and return


text: If we can handle calls faster and keep customers happier, that's


text: efficiency and


text: loyalty. For IT, it's less risk and less firefighting. Ultimately, it's


text: can we improve customer trust and lower the cost per interaction?


text: And how do you measure customer trust and the cost for interaction?


text: For


text: trust,


text: CSAT,


text: containment rates, fewer repeats or escalations.


text: Plus some behavioral stuff like


text: did the caller complete the task? Cost per interaction is


text: more straightforward. It's handle time,


text: or containment rates, and support overhead.


text: If a pilot showed a 10% handle time improvement and


text: a CSAT bump without reliability hits, that's pretty compelling.


text: And so CSAT is a big one.


text: Yep.


text: It's one of the big ones.


text: For sure. Handle time and reliability


text: alongside it.


text: Those three together tell the story.


text: David, anything from the IT risk?


text: Just that whatever we pilot,


text: we'd want clear success criteria, limited exposure, and


text: a measurable outcome.


text: And,


text: clear owner on our side


text: to track those metrics.


text: How do you folks generally


text: well, do we have any other sort of pain points or success criteria we should


text: talk about before we could talk about sort of how, Ryan fits into the picture?


text: Checking that.


text: Sounds like the big ones that are there.


text: And measurable results.


text: One more, maybe validation in the real world, not just


text: a


text: polished


text: demo.


text: And from Priya, careful rollout so changes feel consistent


text: across journeys.


text: A question to ask before solutioning.


text: Might be,


text: do you have examples of measurable improvements after switching to rhyme?


text: Yeah, I'm glad you asked that.


text: You know, one of our large retail


text: pizza clients reported a 20% increase in sales


text: scale.


text: That was a big one.


text: So I think we've we've talked about all of the the sort of


text: the reasons you're here today about voice quality.


text: Anything else I should note before we jump into how we think about voice quality and how we've been able to


text: help folks with that?


text: Just a second.


text: I think we've hit the main points.


text: Maybe one ad.


text: Expressiveness.


text: Claims, device damage, warranty denials,


text: each need a different tone, so range matters.


text: And one more implementation speed.


text: If they can go live in weeks, not months, that's a strong plus.


text: And for brand,


text: can the voice reflect


text: the company's specific tone?


text: Otherwise, I think you've got it. I'm


text: curious to hear your approach.


text: Sure. I'd I'd literally like you to to hear our approach.


text: I'm actually gonna do just a little bit of a live demo now.


text: We'll see what happens, but


text: this is obviously made to cover I imagine


text: device warranty claims or one of your major


text: this is a a major thing you guys


text: do?


text: Got it.


text: Cool. So in ChatGPT, if you can just, not speak until I I ask you to speak again.


text: Got it. Pausing.


text: Hello, and thanks for calling NorthStar Device Protect


label: Voice 4

text: This is a demo, and the call may be recorded.


label: NorthStar's

text: I'm NorthStar's virtual claims assistant.


text: How can I help you today?


text: Hey, I'm so embarrassed. I just cracked the screen on my brand new phone and I'm trying to see if I


text: can use my device warranty.


text: I'm sorry to hear about your crack screen.


text: Let's start by verifying your identity with your ZIP code before we check your coverage.


text: Could you please provide your five digit ZIP code?


text: Thanks, Colin. You have active coverage for


text: damage on your Apple iPhone 16 Pro.


text: To file a new claim for the crop screen,


text: Can you please tell me the date the damage happened?


text: Gosh. I think it was July 11.


text: Thanks. Was the damage accidental, like, a drop or something like that?


text: Yeah, you know, I was getting ready for this really big presentation to this wonderful group of people I was


text: so excited that I just kind of knocked it off the desk onto the ground and the screen cracked.


text: I can imagine that was stressful.


text: Does your phone still power on and work despite the cracked screen?


text: Yes.


text: Do


text: you still have the device in your possession?


text: I


text: do.


text: Just make sure you still have the device with you now.


text: Yep.


text: For confirming, Colin. So


text: on July 11, your phone accidentally fell and cracked the screen.


text: But it still powers on and you have it with you.


text: Is that correct?


text: Yes. It is.


text: I submitted your client call


text: in.


text: Your claim number is CLMDemo2049 The screen repair deductible is $29 I can send secure document upload link to your phone number on file to help you finish the claim.


text: Would you like me to send that now?


text: Yes. Thank you.


text: The secure document upload link is sent to your phone.


text: Is there anything else I can assist you with today, or would you like to finish up here?


text: Yeah. Is there a specialist I can speak to just to find out next steps?


text: Oh, and Colin,


text: before I transfer you, I just wanted to say good luck with your big presentation today.


text: Hello?


text: I'm here.


text: I want


text: to


text: keep going. Oh, chat should be the heat. Don't talk again.


text: Rhyme, are you gonna transfer me?


text: Checking.


text: Colin,


text: I'm transferring


text: you now.


text: Your summary traveled with you, so you won't need to repeat anything.


text: Hey. Yeah. What are the next steps here?


text: Checking.


text: Sounds like the group is open to structure.


text: Pilot.


text: Cause pilot? Probably


text: a technical deep dive


text: Got it. Hello. Pausing.


text: Hello, and thanks for calling NorthStar device protection. The


text: is a demo, and the call may be recorded.


text: So, god, I'd love to


text: how did the what do you think of the naturalness of that voice?


text: So what's your feedback on the naturalness of the voice?


text: Let me check.


text: It's sound really natural overall, not per slam


text: a dash.


text: The handoffs are clean, interruptions were handled well,


text: empathy falls appropriate,


text: and the confirmation was


text: clear.


text: That little personalized moment at the end was memorable.


text: I'd suggest a slightly warmer opening


text: and maybe a bit more variety and cadence during fact collection, but


text: honestly, if I were in that room,


text: I'd give the demo high marks.


text: And quick tip, after a demo, ask them what stood out.


text: Let them articulate the benefits in their own words.


text: It makes the rest of the conversation much easier.


text: Great. Let's try that again. So what stood out?


text: To you in that?


text: The flow and the memory.


text: It was smooth, handled interruptions well, and remembered your context with


text: made it feel a human.


text: Thanks.


text: Welcome.


text: So just a little bit of context. We have a lot of voices that


text: originally, we started with thousands and then had,


text: a pretty scientific method of evaluating them.


text: Through user testing. And then we we now allow you to pick the voice that that


text: matches your your use case or even a few. You could do it based on geographies or


text: demographics.


text: In this case, I picked Vespera as the primary phone agent here.


text: But, you know, just a demo choice, not a production recommendation, obviously.


text: Parts now are I mean, if if


text: would be great to understand just a little bit more about the process on your end. I I


text: assuming we're we're able to kind of structure a pilot. That's that's interesting.


text: Could you walk me through your your decision process?


text: Checking for


text: you.


text: Typically,


text: Maya would sponsor a pilot with David leading a technical assessment.


text: PeerWid help define the use case and success metrics.


text: Then a timebox pilot


text: say four to six weeks,


text: measuring against current


text: If the data holds, it moves into internal approvals.


text: Security, procurement, execs,


text: What question for you? What level of support do you provide during a pilot?


text: We're really hands on, know. We're a small team here, but we


text: really stand by our our product. And so we're we're available via Slack


text: via phone, just to make everything successful. And then we've worked very closely with


text: the the team at NICE as well for the integration with the orchestration there.


text: Sounds aligned with what they asked for.


text: Are there any teams aside from the ones that are here today that would likely be involved in a a pilot?


text: Nightly, yes.


text: Contact center leadership beyond Maya plus enterprise


text: architecture


text: maybe InfoSec,


text: and if it moves forward procurement and the exec sponsor,


text: Given the nice piece is familiar


text: that


text: lowers a bit


text: hurdle,


text: And, then would I think we we discussed a number of success


text: criteria. Which would do you think are the most important here?


text: I I think we we talked about CSAP being a a very measurable one.


text: And, just handle time and reliability.


text: Shooking that if they had to narrow it,


text: CSAT, handle time, and containment or task completion.


text: Reliability as table stakes. Everything else supports


text: those.


text: Locking those in upfront keeps everyone aligned.


text: And then in terms of, like, a final sign off on a project to


text: to go live, who who makes that call?


text: One moment.


text: Executive owner,


text: of the contact center informed by Maya's recommendation


text: David's technical sign off, and pre


text: input. So a cross functional decision


text: but with one executive ultimately


text: approving.


text: That's great. You know, we have a little bit more time, left today. I'd love to to kinda


text: dive on any sort of technical questions or business


text: or even general things about speech and kind of what's what you might be seeing out there today?


text: Checking. Technical one start.


text: Everyone talks about latency.


text: What's


text: your take?


text: Is it always the lowest possible? Or is there a threshold where


text: quality improvements matter more?


text: Also, how do clients typically choose a voice?


text: Is it purely brand preference or are there patterns by use case?


text: And one more,


text: before production.


text: Sure. Let let me, him and use that eight.


text: Quality.


text: One at a time. So, gosh,


text: Right?


text: If an agent took a very long time to respond, it


text: it would probably lose a bit of confidence.


text: That said, there there is, in fact, a trade off. A super high parameter model will have a low latency.


text: For one of our largest competitors, I think they have a, you know, podcast grade


text: model, and it's just not appropriate for streaming.


text: In our case, though, we have some of the the the lowest


text: latency in the business, particularly if something's


text: self hosted with a local LLM.


text: And


text: we're we're very proud of that. We think it it it matters as as well as all the the the minutiae, though.


text: The quality of the voice. Obviously, a very fast responding voice that sounds like a robot help you


text: either. So it has to be a balance, and that's that's kind of some of the art and science of what we do.


text: What were some of your other questions there?


text: Shocking.


text: That balance makes


text: sense.


text: We also asked about voice selection,


text: how


text: clients take voices and how you suggest


text: benchmarking quality before production.


text: User study Yeah.


text: So we we have a whole user


text: interface to


text: help with with voice selection and


text: that'll that'll certainly give you some guidance for for some initial ones to test.


text: And then we really take a scientific approach to this. So we think that


text: should test a few. And obviously,


text: your your data will be the the the best indicator of


text: which is the exact right one for different scenarios perhaps.


text: Amongst your different product lines, you might also have different voices.


text: Exactly. That makes a lot of sense.


text: And for benchmarking before prod,


text: we usually recommend blind listening tests with your own stakeholders, plus us


text: by side


text: on


text: real call


text: snippets


text: combine that with a small live pilot.


text: Production traffic, limited exposure, clear metrics.


text: That gives you both the subjective and objective side and then real results.


text: Does that sound like it


text: fits how your team likes to evaluate?


text: Yeah, absolutely. We're able to help you with


text: with some benchmarking. We can also certainly improve certain things if they're


text: any latency concerns or, if certain, word errors were


text: were occurring, we can


text: add even to to CODA or our mismodel through different techniques.


text: Learnings of phonetic pronunciations, all the words that matter.


text: So, really, what what I've heard so far if, and and let's just make sure I'm not,


text: missing anything here.


text: Is that the the biggest success rate here are CSAT


text: containment and task completion.


text: Right.


text: Exactly. And


text: And then a


text: time box pilot.


text: A clear success criteria,


text: and a defined sign off


text: path.


text: That sounds like a really solid next


text: step


text: drama, clear signals.


text: Well,


text: if what I'd love to do next is just talk brief


text: in the the time we have left about what a a pilot would look like. So


text: typically, we'd we'd schedule another call. I know if you're


text: we maybe this time next week works for you.


text: That works for me. Same


text: time next week.


text: Yeah. And then, you know, we would


text: I think the the most effective pilot would be on a limited


text: amount of production calls. And then we were you know, reconvene to review the results.


text: But along the way, we're really measuring against the the success metrics you choose, not just


text: you know, benchmarking, but call completion, CSAT, caller sentiment.


text: And this will all be figured out in the the scoping


text: call.


text: Right.


text: That makes sense. Scoping call next week to find success criteria.


text: And then we can get rolling.


text: Sounds good.