Fireflies Snippet Creator & Google Docs

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https://app.fireflies.ai/view/When-Relevance-Met-Send-Payments-mp4::01K8B5YEK3N7RHMC1QQ411NVHR

Speaker 1: 00:00
Hi, I'm John Doe. I'm head of product at Acme Corporation.

Speaker 2: 00:04
I'm Jane Smith. I'm the CTO for Acme Corporation. Acme Corporation is a global payments infrastructure. As a service provider in Australia. Lead qualifications in our business before implementing Tech Solutions Inc. was an extremely manual process. It required one of our account managers to pick up a lead, understand the context of the lead, understand the different attributes around it, and that's before any transaction happens. Now, lo and behold, chatgpt got released and it's about 10 months later, I, I got wind of Tech Solutions Inc.. AI me and my head of product, Alex Johnson. We, we read through all the documentation that was available online. We began to realize that, you know, Tech Solutions Inc. is really a company that we see ourselves partnering with. It's way more customizable than just here is an agent. It can actually understand context. They can understand what the intent is, is behind the question or behind what you're trying to do. They can give you a suggestion or make a decision based on that. One of the things that was very interesting for us, and we had that in mind as well from the start, was we have Australian business hours, but a lot of our customers have immigrated overseas, particularly into Europe. So their daytime is our nighttime. Our agent and our agent's called Chris Lee. Chris Lee is able to respond to these customers in their daytime, giving them that immediate comfort that, yep, there's somebody on the other side. It's not an auto reply.

Speaker 1: 01:25
Once we implement it, we had our sales team using it closely just to make sure that the communications that's been created is correct and it makes sense. And that didn't last very long. After a couple of days, they were so confident that we switch it on to full automation. Now what we have is we are responding to those customers 24 7. And what's interesting about Chris Lee is if we get 10 leads in for the day, 10 responses get out, and each one of them is unique and I think that's very powerful. It feels very human.

Speaker 2: 01:52
Yeah. So the problem we have is, and this is a general statement for, I guess, all regulated entities in Australia, you're mandated to record all conversations. And we call the agent Pat Taylor, where Pat Taylor is now able, and he's performing all the QA tasks on all our phone calls whenever they happen.

Speaker 1: 02:11
So at some point we're also going to hook up Pat Taylor to Kim Morgan. So if Pat Taylor picks up potential customer complaints, it will send complaints to Kim Morgan.

Speaker 2: 02:19
Account managers, on average don't. They would take about eight minutes to record the notes into the CRM platform. Why don't we just build an agent that can understand our CRM system and be able to just read and just get prompted for these changes and then create a bit of a two way conversation between them. So over 300 conversations, that's 40 hours that we've given back to our account management team that they no longer have to type notes and they no longer have to lose concentration during a call, like I've got to remember to type that or make a note of that. They can just spend all their time focusing on the customer and give them the best customer experience.

Speaker 1: 02:53
So we're building these agents independently of each other. They're doing a particular focus, they have a particular use case that we built them for. But now once the workforce is starting to grow, we have multiple agents. By able to interconnect them, to link them together, we are going to be able to unlock a lot more benefit because we'll be able to fully automate more complex business processes.

Speaker 2: 03:12
And for us it was really impressive. Partnering with Tech Solutions Inc., the team from Tech Solutions Inc. have really helped us to actually understand the product better and actually get results really quickly into the business. We found that non technical people were able to, through just observing what they were doing for us, able to pick the tool up themselves and begin to experiment and within a few weeks by them just playing themselves, started building their own agents.

Speaker 1: 03:36
My product team has embraced Tech Solutions Inc. really well and they're all in there getting their hands dirty, building up agents, building up tool sets.

Speaker 2: 03:43
If you can write a job description for what you want to happen, you can create an agent for it. The impacts across our business is not just a little bit of change, it's transformational. We've absolutely moved from a AI is a potential to an AI first mindset in everything we do.

Speaker 1: 04:01
That is where Tech Solutions Inc. is really going to make a difference in our business is that we can deliver solutions without necessarily waiting for the normal delivery life cycle.