The Future of GenAI and Insurtech: LIVE from AWS re:Invent

Summary

AWSのAry GuptaとAnorのFaruk Shayが、保険業界における生成的AIの影響について議論。Guptaは、AIが技術と人間の関係を変革し、保険業界では創造性、ドメイン探求、専門的な意思決定支援、新入社員のオンボーディングに影響を与えていると述べた。Farukは、保険会社がAIを積極的に採用し、操作効率化とデータのスケールでの活用を目指していると補足。両者は、AWSとAnorが提供するコードレスプラットフォームを活用し、保険業界のデジタル化を加速する可能性について語った。

Takeaways

• 🌟 AWSのAry Guptaが保険業界のビジネス発展をリードし、北米に焦点を当てています。
• 🔍 Ary GuptaはAWSで6年以上働いており、保険業界におけるAIと機械学習の進化に貢献しています。
• 📈 保険業界では、創造的なアウトプット、新しいドメインの探求、専門的な意思決定支援、新しいチームメンバーのオンボーディングなど、AIの活用が進んでいます。
• 🚀 保険会社は、AIを通じて運用効率を向上させるために積極的に実験を行っています。
• 🛠️ 従来のチャットボットとは異なり、AIは対話形式でQ&Aを可能にし、保険業界におけるカスタマーサービスの向上に役立ちます。
• 💡 AIは、保険業界の顧客サービスを向上させるために、リアルタイムでのサポートやカスタマイズ情報を提供することができます。
• 🌐 保険会社は、AIを活用して、データのスケールと効果を高め、遺伝子データや外部データの統合を迅速に行うことができます。
• 🔄 保険会社は、AIの力を最大化するために、AWSとNoCodeの能力を組み合わせることを積極的に検討しています。
• 🔧 従来のレガシーシステムからの移行において、AWSのBedrockを使用することで、プロセスの加速と効率化が期待できます。
• 📊 保険業界のCIOは、AIを活用して実験を行い、プロトタイピングから生産までをスケーラブルな方法で進めるべきです。

Q & A

AWS reinventでAry Guptaが参加したイベントの主題は何ですか？

Ary Guptaが参加したAWS reinventのイベントでは、保険業界におけるAWSの役割とAI（特に生成的AI）が保険業界にどのように影響を与えているかについて議論されました。

Ary Guptaの現在の役職は何ですか？

Ary Guptaは、AWSの保険業界向けのNorth America地域のMarket focused on Goto Marketをリードしています。

Ary Guptaは保険業界でどのくらいの経験がありますか？

Ary Guptaは保険業界でほぼ25年もの経験があります。

AWSが保険業界で注目している4つの主要なイノベーションの分野は何ですか？

AWSが保険業界で注目している4つの主要なイノベーションの分野は、クリエイティブなアウトプット、新しいドメインの探求、専門的な意思決定支援、そして新入社員のオンボーディングです。

生成的AIが保険業界にどのように影響を与えているか?

生成的AIは、保険業界に多くの影響を与えています。例えば、コードの作成やデザイン、検索や要約化、パーソナライズテーションの改善、Q&A形式の対話、専門的な意思決定支援、複雑なタスクの自動化、ニューハイヤーのオンボーディングなどです。

保険会社が直面している主な課題は何ですか？

保険会社は、コストの上昇、有機成長の難しさ、災害露出の増加、ビジネスコストの高コスト、データシステムの分断など、多くの課題に直面しています。

AWSとAnorが提唱するコードレスフレームワークの利点は何ですか？

AWSとAnorが提唱するコードレスフレームワークの利点は、迅速な開発、低コスト、ビジネスユーザーの早期参加、自動化されたプロセス、そしてよりスケーラブルなプロトタイピングから生産へとの移行が容易であることです。

保険会社がAIを採用する際のアドバイスは何ですか？

保険会社がAIを採用する際のアドバイスは、まず低リスクな内部運用からの実験を始め、コードレスのアプローチを検討し、プロトタイピングから生産へとの移行に向けた戦略を立てることです。

AWSのBedrockサービスとは何ですか？

AWSのBedrockサービスは、事前訓練されたファウンデーションモデルへのアクセスを提供し、APIフレームワークを通じて複数のモデルにアクセスできるフルマネージドサービスです。

保険会社がAI技術を採用する際のセキュリティや規制上の考慮事項はどのように対処されていますか？

保険会社はAI技術を採用する際に、セキュリティや規制上の考慮事項を重視しています。特に、データプライバシーや顧客情報の保護は重要であり、AIの実装にはこれらの要素が適切に取り入れられています。

Ary Guptaが保険業界で見ている最も興味深いトレンドは何ですか？

Ary Guptaは、保険業界で最も興味深いトレンドとして、生成的AIの認知的自動化機能の到來を指摘しています。これはスケールで実施可能であり、技術の進化が非常に迅速であると感じていると述べています。

Outlines

00:00

🌟 導入とゲスト紹介

この段落では、イベントのライブ配信が開始され、ゲストであるAry GuptaがAWSから加入したことが歓迎されています。Faruk Shayが保険ビジネスをリードしているAnorで、Ary GuptaがAWSの保険業界の市場に焦点を当てた北アメリカ地域をリードしていることが紹介されています。Ary GuptaはAWSに6年以上勤務しており、保険会社や再保険会社、大型ブローカー、ISV、システムインテグレーターと協力してAWSの保険顧客へのビジネス変革を促進しています。Aryは保険業界で約25年働いており、AWS re:Invent会議に出席していることを楽しみにしています。

05:01

🤖 ジェネラティブAIが保険業界に与える影響

この段落では、AIと特にジェネラティブAIが保険業界にどのように影響を与えているかについて議論されています。Ary Guptaは、ジェネラティブAIが強力なツールであり、そのような強力なツールがユーザーの手中にあることを指摘しています。保険業界においては、これまでに不可能だった様々なアプリケーションが可能となりました。また、AIがもたらした技術革新の歴史を振り返り、ジェネラティブAIがAIと機械学習の進歩の節目をもたらしたと感じていると述べています。Aryは、AWSの保険顧客が見ているイノベーションの主要な分野について4つのカテゴリに分け、それぞれについて説明しています。

10:02

🚀 保険業界の課題とジェネラティブAIの機会

この段落では、保険業界が日々直面する課題と、ジェネラティブAIがどのように役立つかについて説明されています。Ary Guptaは、COVID-19の流行以来、保険業界に起きた変化や課題について話し、マクロ経済の立場からのコストの上昇や保険会社の有机的な成長の難しさについて触れています。また、AIがデータをより効果的に利用できるようにし、保険業界の複雑なデータシステムやレガシー環境から解放される方法についても議論しています。

15:04

🛠️ 保険会社のデジタル化とAWSの役割

この段落では、保険会社がAWSの機能をどのように活用してデジタル化を進めているかについて説明されています。Ary Guptaは、AWSの顧客が特に審査機能と請求機能で活発に実験をしていることを指摘しています。AIによる支援機能や詐欺検知、カスタマーサービスの改善など、保険業界におけるAIの活用方法について詳細に説明しています。また、AWSとAnorが協力してBedrockを通じて保険会社がどのように支援されているかについても触れています。

20:04

🤝 保険CIOへのアドバイスと未来の展望

最後の段落では、保険会社のCIOや業界の他の関係者にとって、ジェネラティブAIの今後の進展に向けてどのようなアプローチを取っていくべきかについてのアドバイスが提供されています。Ary Guptaは、組織内で実験を始めることを勧め、特にAWSのBedrockを使用して事前訓練された基盤モデルにアクセスする方法について説明しています。また、AnorとAWSが協力してBedrockを活用し、保険会社がレガシーシステムの移行を加速する方法についても言及しています。保険業界の技術採用の速度と、AIの可能性を最大限に活用するための期待が表現されています。

Keywords

💡AWS

AWSはAmazon Web Servicesの略で、クラウドコンピューティングサービスを提供するAmazonの部門です。本動画では、AWSが保険業界にどのように影響を与えているかについて説明されています。AWSは、データ分析、機械学習、アプリケーションのホスティングなど、幅広いサービスを提供しており、保険会社がビジネス変革を遂行するのに役立ちます。

💡保険業界

保険業界は、保険サービスを提供する企業の集まりを指します。この業界は、COVID-19の流行以来、顧客の行動の変化や経済的な圧力など、多くの課題に直面しています。本動画では、AWSが保険業界の課題をどのように解決するかについて議論されています。

💡生成的AI（Generative AI）

生成的AIは、新しいデータを作成できるように設計されたAIの分野です。これは、画像、音声、テキストの生成や自然言語処理などに適用され、保険業界では新しい製品の開発やカスタマーサービスの改善などに活用されています。

💡ビジネス変革

ビジネス変革は、企業のビジネスモデルやプロセスを根本的に変えることを指します。本動画では、AWSが保険業界のビジネス変革を支援する方法について説明されています。テクノロジーの進歩により、保険会社はより効率的なサービスを提供し、顧客のニーズに応えることができます。

💡カスタマーサービス

カスタマーサービスは、企業が顧客に提供するサービスやサポートを指します。保険業界では、カスタマーサービスの向上が重要であり、生成的AIなどの技術を活用することで、カスタマーサービスの質を向上させることができます。

💡意思決定のサポート

意思決定のサポートは、意思決定プロセスを支援するために提供される情報やツールを指します。保険業界では、専門的な意思決定のサポートが重要であり、生成的AIを利用することで、専門的な意思決定プロセスを効率化することができます。

💡データ分析

データ分析は、データから意味のあるパターンやトレンドを見つけることを指します。保険業界では、データ分析が顧客のニーズやリスクを理解し、保険商品の設計や価格設定に役立ちます。AWSのサービスを利用することで、保険会社は大規模のデータを効率的に分析することができ、ビジネスの最適化につながります。

💡デジタル化

デジタル化は、紙ベースのプロセスや手動プロセスをデジタル技術に置き換えることを指します。保険業界におけるデジタル化は、手続きの効率化や顧客サービスの向上、コスト削減につながります。本動画では、AWSの技術を利用することで、保険会社のプロセスのデジタル化が進められ、ビジネスの改善が期待されています。

💡NoCode

NoCodeは、プログラミングの知識がなくてもアプリケーションを開発できるプラットフォームを指します。保険業界では、NoCodeプラットフォームを利用することで、ビジネスユーザーが自分でアプリケーションを開発でき、開発コストを削減し、スピードを向上させることができます。

💡レガシーシステム

レガシーシステムは、古いまたは過时なシステムを指します。保険業界には、多くのレガシーシステムが存在し、これらのシステムの移行や更新は大きな課題となっています。AWSのBedrockサービスを利用することで、レガシーシステムの移行を加速し、効率的なビジネスプロセスを実現することができます。

Highlights

Ary Gupta, who leads AWS's insurance industry go-to-market focused on North America, discusses the impact of generative AI on the insurance industry.

Generative AI has brought an inflection point in AI and machine learning, making significant advancements in a short period.

Generative AI empowers users to create images, videos, and write code, offering new possibilities for the insurance industry.

The potential for foundation models within generative AI is incredibly exciting, though it's still early days.

In the insurance space, generative AI is being used for creative output, domain exploration, expert decision-making support, and onboarding new team members.

The importance of choice in generative AI models and the platforms provided by AWS is highlighted, allowing for tailored solutions.

AWS's launch of Amazon Q demonstrates the game-changing potential of generative AI in technology and DevOps.

The rapid pace of generative AI development means that insurers should maintain a flexible mindset and not be tied to one model.

Insurers face challenges such as increased cost of doing business and the need for innovation to stay relevant.

Generative AI can help insurers with operational efficiencies, especially in underwriting and claims functions.

Fraud detection in claims is an area where generative AI shows promise, with the ability to flag patterns of fraud more effectively.

Improving customer experience through real-time assisted functionality is another application of generative AI in insurance.

Insurers are embracing generative AI more actively than other industries, with a thoughtful and secure approach.

Legacy migration and the use of AWS Bedrock are central to the conversation for streamlining business processes in insurance.

Ary Gupta advises insurers to start experimenting with generative AI and consider no-code solutions to accelerate the innovation process.

The combination of AWS's technology, no-code capabilities, and industry collaboration is seen as a powerful approach for insurers.

Ary Gupta and Faruk Shay encourage insurers to reach out and engage in conversations about adopting and leveraging generative AI.

Transcripts

we're live uh

Daniel hello and welcome everyone from

AWS

reinvent uh Anor is proud to have Ary

Gupta from AWS joining us today my name

is Faruk Shay I lead the insurance

business at Anor welcome everyone Ary

would love to start with a quick intro

from your side uh tell the viewers about

your background what you do at AWS and

it's a pleasure to have you here yeah

thank you Faruk uh and thank you to the

uncork team for having me so my name is

arti Gupta and I lead aws's insurance

industry goto Market focused on North

America region and I've been with um

with AWS for over six years now what I

do in my current role is I really uh

lead the business development and go to

market working with both BNC and life

insurance companies re reinsurance

companies large Brokers so really

anything in the insurance space along

with our isvs and system integrators and

really just helping them effectively

position the benefits of AWS to

Insurance customers to really drive that

business transformation um with the line

of various lines of business so I've

been working in the insurance industry

for almost 25 years um and really happy

and excited to be

here it's a pleasure having you I'm

super excited about the conversation I

was saying this to somebody earlier the

AWS 3 invent conference like always it's

such a magnificent event and this year

yeah with all the kind of activity

around gener like generative AI it's

been exceptional to be here I guess to

kick off the discussion maybe we can

start there right it's a Hot Topic AWS

is doing a lot of work in gen would love

to get your perspective on how gen is

influencing the insurance

industry yeah absolutely you know I was

actually it's funny you say that I was

thinking about the last year's reinvent

and the reinvent this year right I think

geni was not as you know probably not

even mentioned at last year's reinvent

so how so much has changed in a way like

so much advancement has been made when

it comes to AI more broadly but

specifically gen and I feel like you

know gen has really brought an

inflection point in our kind of Journey

of overall Ai and machine learning and

if you really look at the history it has

really always been about change and lot

of that change has been driven by

technology um I feel what's really

different with Gen and I think the hype

is real and obviously a lot of our

customers are super excited about it we

are very excited about it but there are

a couple things um in my opinion that I

feel are very different right so first

thing is I think if you just like purely

look at gen I think it's a very very

powerful tool but the beauty is that

something so powerful is now directly in

the hands of users so users can go

around and play around with it and do

things like creating images videos

writing code and all that stuff right so

even in terms of insurance there's lot

of different applications that you know

traditionally were not quite possible um

but now with geni that um business users

can just jump in and start playing with

it and then the second thing I think

with Gen more broadly speaking is

historically has just been about you

know writing technology writing software

and then humans had to kind of learn how

to really um derive value from that

software and Technology gen again has

really just reversed that it has just

made the whole process so much easier by

giving those tools in the hands of the

users and I think the potential for

foundation models within you know gen in

particular is incredibly exciting um and

having said that that I would say it's

still very early days because as you

kind of think about the the key areas of

innovation that at least we see from an

AWS standpoint with our insurance

customers I would say more broadly

they're kind of falling in the four key

buckets number one would be creative

output whether that's just you know U

writing code or designing or modeling

really being used behind the scene and

improving that search and summarization

and personalization so I think that

really gaining a lot of traction um in

in the insurance space second thing I

would say would also be new domain

exploration where it's very much in a

Q&A very conversational type of format

that historically we have not seen um

kind of play out with the traditional

chat Bots and then um the expert

decision making support um I think for

Rook you probably see a lot more use

cases on that front too where it's the

human in the loop almost as an assistive

functionality where um whether it's in

underwriting or claims you can have an

assistant so to speak powered by gen to

really kind of automate the complex task

that really save that human cognitive

power for those things that require

human intelligence but reducing the

consideration set of things that they

may need to consider and then of course

we also see that in onboarding new team

members into potentially complex subject

area so I think the use case is a really

really uh powerful and very diverse set

of use cases that we are seeing in the

insurance space curious about your

thoughts as well it's been

fascinating looking at the uh keynote

yesterday uh at aw3 invent and they were

talking about the importance of choice

right the ability for you as these

models get developed in generational AI

to or generative AI to be able to

leverage the right model for the right

capabilities and the kind of platform

and choice that AWS provides through

bedrock that was fascinating to see it

was also very interesting with the

launch of um AWS or Amazon Q right which

all so we were we were spending some

time with a number of our clients who

have uh technology and devops

capabilities uh and and folks who spend

all their time looking to automate those

functionality but the ization of gen in

that context really is a game changer

right like it's you need to SP

environments and ec2 instances and so

forth and you can you can actually just

have a conversation with some like a

technology capability that helps you do

that right so the learning curve the

adoption the speed and automation that

you would expect like it's like

fantastic to see and in fact like the

one of the biggest observations uh

client made today was it's moving so

fast we just just don't know what it in

six months right like it's only been to

your point less than a year since we all

like become familiar with the technology

and the word of geni but it's moved so

fast and across so many kind of areas

right like

marketing engagement customer engagement

servicing

technology Amazon whisper automation

productivity there there's so many

fronts here right so the confusing a

little bit to say what it might be six

months from

now oh yeah I mean new models I feel

like are just coming out every day and

new features and functionalities so

right so and I I always tell our

customers as we are working with Gen um

use cases or proof of concept to really

maintain like a mindset a flexible

mindset and not not necessarily being

tied to just one model because the

models just are you know coming out

every day more and better and faster um

and that's the beauty of Technology

there it's fascinating the the the way I

think about gen is that this is there's

been many Technologies like cloud and

rpas and like you know uh blockchain and

but this is the first time you're seeing

really the cognitive automation

capability oh absolutely right at scale

which is very very exciting I I wanted

to check with you right like in that

context how do you see there's this

world of cognitive automation gen

capabilities models and and services

coming out but at the same time as you

look at insurers and the industry

broadly what are some of the challenges

that you see on a day-to-day

basis yeah you know um it's funny you

ask so I think few things I would say

within the last two years because it's

interesting right so in the spectrum of

um Insurance in particular but even more

broadly I I think covid brought in some

Behavior changes and um you know just

different challenges that came with

covid but now coming out of covid right

so this postco

era so it kind of put these pressures

more kind of an economic standpoint and

you know we all hear about inflation we

all hear about just you know the higher

cost of doing business so I I think both

in the personal General Insurance space

as well as life Insurance base what we

are first of all seeing is just in terms

of an overall macroeconomic standpoint

is just the cost of doing business is

higher plus I think that organic growth

for insurance companies is has been

challenging right like the PNC insurance

companies are really struggling more I

would say from a profitability

standpoint the catastrophic exposures

are at kind of at an all-time high and

like I said the cost of doing business

is you know higher so

and insurance as you know there's always

like a lag in terms of being able to

catch up to the right rate for the right

risk so I think that's going on on the

life insurance side what I'm seeing

talking to our customers is I think

they're just looking for that Innovation

um in terms of making those um you know

whether it's the term life an nudies

those you know typical products in the

Life Insurance space making them really

more relevant um for their and customers

being able to appeal to the younger

Generations being able to make that ease

of doing business direct to Consumer

channels uh elevating the customer

experience right like so all those

challenges are really even more

highlighted I feel in today's world and

I'm I'm really hoping as as we you and I

are kind of just discussing about the um

promise of Genna I think these all these

areas really can you know be good

candidates for that experimentation and

really bringing first of all those

operational efficiencies to kind of take

take out the cost uh but also being able

to leverage data um at scale and more

effectively because again you know I

think insurance has been kind of really

notorious for having this disparate Data

Systems and Legacy environment um and

being able to really kind of break free

from that and get into use cases where

you can really liberate not just your

internal data but uh you know attack on

your external third party data and being

able to do it with really um speed

velocity and at scale so I think those

those are kind of my things like I think

they the customers are facing but I

think there's definitely a lot of

potential in addressing those risks this

is such an exciting time I always think

about it when we when we talk about the

challenges that the industry has faced

right but if I if I put together all the

Innovation and capabilities that

AWS has provided over over the years

right all the way from like just the

cloud capabilities and the serverless

capabilities and and kind of how we had

uncor think about codess and then you

add then to the mix right I would love

to get your perspective on how are you

seeing opportunity for insurers to

leverage some of these capabilities

together to exrate their

Journey yeah I think the key areas that

I'm kind of seeing a lot of um interest

and experimentation number one you know

that operational efficiency that I was

talking about so I think the two key

business units that pop up over and over

again is in underwriting uh functions

and claims functions right because again

there are um I mean if you think about

from a traditional standpoint I would

say for example our AWS customers are

using what we call intelligent document

processing but I think what happens

traditionally with those models is you

still have to train a lot of your

documents um and the data to to be able

to you know get the outputs that you're

Desiring um but the hope with now gen

and the experimentation that we are

seeing is that these models are

generalized and trained upfront so

they're much more immediately Deployable

and being able to kind of get the

results and also with better accuracy so

I think that assisted functionality

again I'm not saying that there are

going to be decisions kind of you know

automated decision making happening in

underwriting in claims but definitely

being able to enhance those processes

and really kind of cut down on those

manual tasks um are some of the areas we

are seeing same thing with on the claim

side you can have all your adjuster

notes and stuff like that being able to

um automate and summarize so you know

you can extract the relevant information

much more timely and really speed up the

claims resolution process and then also

I'm seeing um on the fraud detection

standpoint uh from a claims again claims

functionality where I think gen is

showing a lot of Promise being able to

kind of look at the data holistically

and being able to flag those patterns of

fraud again you know fraud is a big area

of interest uh within the insurance

industry and then last but not the least

overall from a customer experience

standpoint U I think that's again that

real time assisted functionality for

your call center Representatives being

able to guide them and when you have an

angry customer on the line or being able

to kind of Coach them through it in real

time with Gen being able to summarize

and present that personaliz information

the next best action I think those um

all areas I think show a lot of promise

and this is this is such an interesting

space right like uh as I think about

today all of our customers are very

actively experimenting with Gen right

and what we have seen generally and I'm

I'm sure like as we work together on so

many clients we're seeing the same thing

that the insurers are actually embracing

Genai much more actively than they've

ever embraced any technology yes faster

than most Industries have right like so

it's very fascinating for insurers just

kind of engage with technology this

quickly but they're also very thoughtful

about it right like there's always the

security conversation and I think people

beyond that already there's also a lot

more of the experimentation for on

internal use cases like underwriting

claims marketing devops and so forth and

then there is also to your point they're

very thoughtful about not trying to

automate the decision making but rather

digitize the process of decision making

right human in the loop whether it's

underwriting whether it's claims

adjudication fraud and so forth but

getting the you know the the difficult

manual pieces of the process out of the

way in a more digitized process manner

right like so that that's very exciting

I did I I also wanted to you know the

more we work together there's a lot of

work that we are seeing from a legacy

migration perspective right like and

Bedrock is the central theme in this

conversation right so whether it's goal

migrations and there's very early

emerging successes in this area right we

we're seeing this where insurers are

actively looking to address the biggest

problem that we have had in the industry

right for a long time which is all about

Legacy migrations desperate systems like

the whole plora of of systems and

infrastructure that you can you can

think about and I'm I'm very excited

about the potential for using llms using

jna for legacy migration bedrock and the

functionality it provides to

accelerating the journey for the

industry to streamline their business

right like uh from your perspective like

what would your advice be to insurers as

they're thinking about ni as you're

thinking about the amount of innovation

aw is bringing how would you think about

what an insurance CIO should be looking

to do over the next few months over the

next year what what does success look

like for

insurers yeah no great question I think

number one I would say that you know

experimentation is the key I think as

the you know as in your organization

you're kind of finding like these use

cases that again could be internal could

be low risk more from a regulatory

standpoint so not really automating the

decision- making but more from an

operational standpoint I would say start

um you know kind of experimenting there

um but you know even even I I do want to

kind of bring to a point um you know

about the partnership that we have Faruk

you know AWS and uncor as we have worked

together through several different um

customers I think what your organization

is able to bring in is that code L

aspect and that kind of becomes the glue

in this conversation too what I really

like about that is as you're

experimenting and you're working with

Partners such as your organization I

think not only you are gaining the

agility so three times faster but also

that reduced cost in terms of 70 almost

70% you know reduced maintenance cost

and again as the name suggests no code

generated no code needed and being able

to bring your business users into the

process early on on I think that's

really huge because historically the way

things have worked and I've grown up in

the insurance spaces you know business

rules you know are defined and then

they're kind of thrown over to the

developer side and then they kind of

build something and then you go back to

the user

testing I think with with a partner like

yours I think what we are seeing jointly

and I would love to hear your thoughts

too where you know you can just go in

with a codeless framework and being able

to kind of Build That Joint Le with the

business users being part of the process

faster and better at a reduced cost so

first of all yeah I mean so I think as

the cios or any Persona in the

organization is thinking about and you

know bedrocks in particular you know

that's really the easiest way um from an

AWS standpoint to access pre-trained

Foundation models with a single API

framework that can really provide access

to multiple models because it's a fully

managed service with API access is um

and by default it's not trained on

customer data and prompts but it really

kind of achieve that domain adaptation

mainly by providing custom data through

through the prompt and really new

features are coming out so we have now

agents for Bedrock which really gives

you the enable generative AI apps to

complete the task in just a few clicks I

mean that's really nice and also being

able to connect your own data to bedrock

um and I know some of the work uh a s

and uncor is doing jointly leveraging

Bedrock um in that in that framework is

something we can also talk about

especially you know around Cobalt

migration and whatnot but I think those

are all the uh you know tips I would

give that just start experimenting and

consider codess as part of the process

this is this is great right and this is

what we are seeing across the industry

right like there's a method of bringing

the power power of three right like the

the right AWS as the biggest kind of

Provider of technology and innovation in

this space and the codeless capability

to accelerate the journey I know

everyone's thinking actively about

prototyping but very quickly you to

consider how do we go from prototyping

to production in a scalable manner

similar to how you know everything

everything in technology and Innovation

needs to have that mindset of how do you

go from prototyping to production and

how do you Leverage The Power of of AWS

Oncor and the

kind of industry together to streamline

so it's as I said again very exciting

times um I'll close with the like please

reach out AWS onor reach out to either

Ary or myself would love to engage in

this conversation with the industry

there's a lot of work underway and I'm

very impressed by the amount of

excitement within the insurance industry

on adopting technology faster than I've

ever seen before and would love to be

part of the journey and and build this

together together so thank you Ary for

joining us today and really appreciate

your always a pleasure uh to be at ews

reinvent and super exciting times for

the industry ahead yeah thank you for

having me great conversation and yeah

anybody looking to jump into this and

start experimenting please reach out to

Faruk reach out to me we' love to help

you take care thank you