AI 기반 조달 솔루션: 비즈니스 프로세스 혁신

### 조달의 혁신: 비즈니스 효율성을 위한 AI 솔루션
* 💼 "에어비앤비에서 엔지니어링 및 제품 책임자였던 공동 창업자 루와 저는 **구매 프로세스를 간소화할 필요**가 있다고 생각했습니다."
* 🔍 직원들이 구매를 요청할 수 있는 단일 액세스 지점을 만들어 **예산, 법무, IT 등 다양한 부서에서 승인 프로세스를 간소화**했습니다.
* 🤖 Workday 솔루션은 **생성형 AI를 활용하여 계약서, 송장 등 방대한 양의 비정형 데이터를 처리**함으로써 기업 고객의 조달 효율성을 향상시킵니다.
* 💰 상당한 자금을 확보하여 조달 데이터의 실용적인 애플리케이션을 개발하고 서비스를 개선하기 위해 **AI 연구소에 투자**하고 있습니다.
* 🏢 저희 플랫폼을 통해 **3,000건 이상의 불필요한 업무 승인을 없애는 등 상당한 비용 절감 효과**를 거둔 Discover Financial 및 Snowflake와 같은 주요 기업들과 협업하게 되어 자랑스럽습니다.
* 📊 조달은 **전 세계 기업의 지출 중 두 번째로 큰 분야**로, 수조 달러에 달하며 최적화를 위한 막대한 기회를 제공합니다.
* 🌟 시스템을 통해 송장 처리를 자동화하여 수천 시간을 절약한 코인베이스의 경험에서 알 수 있듯이 **OpenAI와의 파트너십은 결실**을 맺었습니다.

Zip의 공동 창립자들은 승인 프로세스를 간소화하여 조달을 혁신하여 주요 기업에 큰 혜택을 제공했습니다.

Used to work at Airbnb, and you had a specific job, and you were basically like, This isn't working. So you went with some friends and colleagues and designed something better and were like, You know what, let's just start a company that does this. That's pretty fair, right? No, that's absolutely fair. So my co-founder, Lou, and I were both engineering and product leaders at Airbnb, and we had to go through this confusing procurement process of if we need to buy something in the business, what are all the approvals that are required, right, between budget and legal and I.T. and security and all the different teams? And that's what we solved. We started to solve for it by providing one front door for any employee in the business to request to purchase. I'm really interested that your AI powered. What form is this generative AI? ML Broad AI because you're serving open AI, for example.

So you built upon that large language model. How does that all go? What are you building that they can't internally for their own process? Procurement? Yeah, that's a great question. It's absolutely generative A.I. And if you think about the procurement process as a whole, right, we have access to so much relatively unstructured data, right? When employees at organizations are buying things, there are millions of contracts, invoices, order forms, so much data that's available, and we can take A.I. and actually apply it in a really, really practical way, which is what we do for our enterprise customers today, to do everything from helping pass invoices to reading messages and contracts for risks and the like. You're with the money hiring, engineering, talent, R&D talent, you're setting up an AI lab and I go back to really what is underlying all of this. Are you building your own large language models to be able to do this?

Are you looking to develop that more with these tools that you want to build in the lab? That's a great question. So we absolutely are using these funds to invest and create in the iLab and really double-click on if, you know, like I sort of said, like the data that we have access to as part of procurement and really thinking about how do we best apply it in a practical way. And so there's more that we'll have to share there in the coming months and so which I'll allow me using. So we today largely use the OpenAI models. I broke my own rule, which is I always start on what's newest and fresh, but I wanted the backstory because it was 52 years ago that you and I first met. So in that time you've raised a lot of money. You have a decent valuation, more than 2 billion. But have you built a business in that

time? Have you managed to take this product and technology and actually sell it to other businesses and enterprises who in turn are using it themselves? Yeah, of course. We've been really privileged to work with some of the largest enterprises in the world, companies like Discover, Financial, Snowflake, Prudential, Coinbase, and many others. And even as an example, Discover Financial has saved over 3000 different business approvals that they've realized they don't need anymore, or Snowflake has over $305 million of zip-supported savings logged. What we find is that procurement is actually the second largest area of spend for any business in the world after payroll, right? It's trillions of dollars in the world that, you know, employees of companies are buying, you know, for office supplies, software, and the like. And so there's so much opportunity. And so you yourselves building on top of open AI. What's that been like? You know, in the news cycle, it's pretty

chaotic when it comes open. I bet as a customer or a partner, what was it like for you? I'd have to say it's been great. And the feedback that we've received from customers has been really positive. As an example, Coinbase has saved thousands and thousands of hours with zip processing, you know, hundreds of thousands of invoices in a much more automated way.

Zip Funding Round Boosts Valuation Path to $2.2 Billion

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전 에어비앤비 리더였던 공동 창업자들은 직원들의 구매 요청을 위한 단일 플랫폼을 제공해 기업의 복잡한 구매 프로세스를 간소화하는 것을 목표로 삼았습니다.

이들은 계약서, 송장, 주문서 등의 비정형 데이터를 분석하는 생성형 AI를 사용하여 기업 고객을 위한 실용적인 솔루션을 제공하고 있습니다.

또한 인재를 채용하고 AI 연구소를 설립하여 자체적으로 대규모 언어 모델을 구축하여 서비스를 향상시키고 있습니다.

iLab 및 비즈니스 성장에 대한 투자

이 회사는 조달 데이터를 실질적으로 적용하는 데 초점을 맞춰 iLab에 자금을 투자하고 있습니다.

Discover Financial, Snowflake와 같은 주요 기업들과 협력하여 상당한 비용 절감을 달성하는 데 도움을 주었습니다.

조달은 기업에서 두 번째로 큰 지출 영역으로, 성장의 기회가 무궁무진한 분야입니다.

고객과 파트너는 우편물 처리에 대해 좋은 경험을 하고 긍정적인 피드백을 받았습니다.

일례로 Coinbase는 수십만 건의 송장 처리를 자동화하여 수천 시간을 절약했습니다.

이러한 자동화는 비즈니스의 효율성을 크게 향상시켰습니다.