Snowflake (SNOW) 22 May 242025 Q1 Earnings call transcript

Hello, everyone, thank you for attending today's Q1 fiscal year 2025 Snowflake's Earnings Call. My name is Sierra, and I will be your moderator today. [Operator Instructions] I would now like to pass the conference over to our host, Jimmy Sexton, Head of Investor Relations.

Good afternoon, and thank you for joining us on Snowflake's Q1 Fiscal 2025 Earnings Call.

Joining me on the call today is Sridhar Ramaswamy, our Chief Executive Officer; Mike Scarpelli, our Chief Financial Officer; and Christian Kleinerman, our Executive Vice President of Product; who will participate in the Q&A session.

year will fiscal financial guidance XXXX second and we first for for call, quarter of quarter and full today's review results our the the During XXXX. fiscal discuss our

our risks concerning recent we materially XX-K today by are to and most call, information our the from our to SEC to available reports. These statements as and statements, related law, available financial release, our other make During no obligation made these which update uncertainties business press earnings required Form subject assume could us. in Except today's currently based and to will any operations are differ XX-Q we All Information risks such uncertainties, of including and as actual forward-looking on statements statements. results. to and statements them performance. cause

will press presentation at non-GAAP GAAP will are Sridhar. would call today's today's discuss earnings replay to like The the to During on an to measures A measures. of earnings website that, now website. With over investors.snowflake.com. is non-GAAP also our be we included in posted accompanying investor call release A release. turn also today's the reconciliation of call, certain and press on available financial I

and afternoon, Thanks, Jimmy, good everyone.

been product the of our of responded months, I X have really pace customers, by and on Before play. as CEO: warm innovation we say teams and fueling alignment I many listening just role, execution quarter my few overall focused within past been get driving in and wanted into go-to-market our me you how you. I've and a and given team from thank by learning our our impressed has to new have and the delivery. it, key welcome to first over to priorities my

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platform philosophy One Our is product with all features simple. available.

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turn to it I'll over Mike. Now

product million. Thank to year-over-year grew XX% revenue QX $XXX you, Sridhar.

Global consumer April, large Global Smaller Our media goods outperformance. and largest outside XXXX moderated accounts the February growth important we March, retail growth entertainment of in component normal this XXXX were strong and growth as business. we an the view and variability contributors saw included a a of source Intra-quarter, a of company. and in

year, XX% leap approximately of product revenue grew year-over-year. impact the Excluding

compensation a the 'XX under top We of environment. grew XX marked first continue sales of quarter-over-quarter. Seven to FY customers plan. our see quarter signs optimization our stable QX

well gross executing down customer and slightly we of sales Our Non-GAAP consumption are margin our plan. In new acquisition year-over-year. quotas. product reps their QX, XX.X% against exceeded was

prior associated call, have invest headwinds As GPU-related initiatives. we our AI mentioned in we on as new costs with

operating Our benefited and X% outperformance. from margin non-GAAP of revenue

cash free flow non-GAAP XX%. margin adjusted Our was

flow. We $X.X X a of quarter billion used in million $XXX cash, In seasonally are $XXX.XX. we free As price long-term average shares at ended an equivalents, quarters with and reminder, adjusted non-GAAP to strong the and QX, investments. cash for short-term repurchase million cash QX QX

have $XXX We original million authorization. our $X under billion remaining

to Now outlook. let's our turn

revenue FY Cortex from only include means guidance consumption. Iceberg will This observed FY behavior. forecast later material includes guidance be product a year. does see on we such based As revenue GA Snowpark until our newer reminder, as contributions features we this not from 'XX 'XX

we Iceberg in because expect invested our it revenue future increase have to opportunity. We

of the half and year. headwinds Iceberg the of purpose out impact weighted model into the for Snowflake However, data to we the back revenue storage. movement continue of is of guidance, to associated negative The with

$X.X approximately million, $XXX now year-over-year $XXX of we expect 'XX are QX, billion, increasing guidance. year growth. XX% revenue million For our representing We we expect revenue FY and product full product between product revenue

Turning to margins.

We to view market, to are investments are light the our of increased rapidly full margin costs and year GPU-related operating guidance unlocking these initiatives as in we key we in lowering AI evolving related revenue future. additional opportunities in our a

we acquire large language certain As R&D. We TruEra GPU cost AI apps model have of and capabilities machine revenue technology reminder, an from production. learning key assets costs announced to that a and models to is employees evaluate in TruEra. and intent provides observability hire related monitor our platform both and and

in We XX employees Snowflake, is of TruEra reflected are outlook. excited to the our welcome approximately to the from transaction impact

operating For non-GAAP expect X% margin. we QX,

XX% margin, adjusted free non-GAAP expect operating we 'XX, flow margin. FY XX% margin non-GAAP product gross cash and X% For non-GAAP

with X on conjunction in we conference. our Snowflake Finally, San Data the Francisco Cloud our host June in will users Summit, Day annual Investor

interested e-mail that, the ir@snowflake.com. With you line open questions. operator, you If up can in now please attending, are for

Stanley. first Morgan with comes [Operator Instructions] Keith from question Weiss our today

Excellent. guys. Very quarter, nice

price stage, us bit now billion products Looking storage like the or on price on per that the query. pressure compute of are at is driving that acceleration? front the like is super investor per the there's pressures the what's be Or you just equation? a on other coming actually is Any data would equation. accelerating on It through indications like it your helpful. some then the It looks looks acceleration? like Can of the or drivers that there on new query relief just relations driving Is the walk the better it side X whether that the query of Any still more queries. more volume side the from center? clarity little optimization page color of acceleration. And the side, of of that again. So like equation

kinds as of Overall, growth. said, and as are categories really we credit Mike from more that is different gain core you. our all data And simple both a relationship both the customers per engineering doing credit between nicely. as they've broad one. expansion look from workloads, straightforward and very business as is is Thank and and coming all customers. growth and growth new handle, contributing we AI, quite strong well I of for existing growth example, been not for cost And across query workloads different They're well. additional And the to increasing we

question today Murphy from JPMorgan. next comes with Our Mark

Sridhar, Could to we $XX million this sounds and for that year, LLM walk in with and the of target there you architectural you little traction. Arctic is some us the spend Mike, pretty any allow run directional launch it think the just to of a GPU change the trained trending that there Snowpark like LLM Should considering higher? product difference amazing more products out other in it than the Arctic efficiently efficiency. a might through market? And Cortex

Thank you.

other amazing to orders the what models a right customers at like good how So like remarkably SQL of of on We creating to AI come small they're order that make period in lot of an actually kind went it experts impressive of of of for are figure architectures. we a remarkably absolutely, talk optimizing sure so train things training in A amount experimentation driving do the that little X the that these companies. But all leading gains things out are Arctic a for rather from queries, or data in what should GPU fed sets, our short also be they increasingly and just -- example, do care unique what for amount These data. enterprise are of had efficiency really was time, architectures these metrics, are can they pre we a models into which about, months. did the compute. over mixture the architecture. of things

are are that's modest an enterprise our context the much and the where taking we do naturally, add AI make of view value how very so most And because things. budgets we of to place we the have better in much AI in the scheme

And a so the honest, terms that gain is metrics hand then with I is a image as comfortable of expect. let's comes I'm greatest, But naturally be discipline that's to second. being models investments, like these investments the ability innovation. the ability latest, generation. something making. is scarcity, the we of of how are Mike producing in we a And Part produces the to And team kind we to creative think against I'll optimize say, of amount follow model, in over that what what and I Snowflake of develop care think about, we fast biggest on lot seeing. And to not you're that fronts number for to the in of

And focus so relatively of operate us a having that kind efficiently. on budget lets pretty modest

production. now much into released that we products have on of the And do focus very so the is take we all how

customers very XXX with platform. for the a we the fast-moving are comfortable and space, our are is effective the make This that but over making to AI AI that investments against Snowflake. Mike? pace, we have We both are choices busy developing

that And organization. be acquisition I add Those bit people we a fall may in we the will specifically more we're about spending GPUs, talked yes, all hiring, that but of AI. think it's into that, We also on TruEra. people little

impact are a world play investing as a And so for revenues. do And is have and rapidly on future in there's meaningful to I we Snowflake massive AI . it there. think evolving, of mentioned, the because will opportunity we that

Materne question next Our from Kirk today Evercore. with comes

can talk bit time Mike. to the little just start for you value can to you meaning do should Cortex, patterns? And faster start think long bit talk the about a how takes you how technology customers' can little about on using with about think consumption then Sridhar, little translate your a before it to we into Congrats them bit it just one a deferred. Mike, just quarter.

just perhaps was but quarter if we've that, anything in upon that than years. prior touch great. seen I onetime down know you more there, bit in could would a sequentially This if don't nature little be there's

Thank you.

creation. And don't which easy very to is have make focus product pre without really look of our model, and AI be often the do so to write is a things, investments can many that about AI commitments what to is how AI was because context of GPUs of in AI value kinds particular make going whether SQL products to SQL, very much in renting, say, do unstructured can mentioned Cortex does. general, transcript let's customers big to anybody to how They to example, from to is Cortex that they they text for also begin earnings Cortex things consumption One that to product of get don't which there, is that value means for have example. our AI, of that are they for images now that use see structure our able the on they're comment. an information, structured cool AI, example, other to Document And at whether in this very, information being it a sort the going the it just can or interesting or like go from

that engineering with of super order There's a the AI Snowflake. use a the of other to these to to commitment and from get iterate software production, then things And in efforts there very is benefits And are commitments top. so very as not easy it to all bigger massive neither needs curve, one GPU adopt. on to customers much make we learning happen which making out that's to that take want you quickly, our ones technology value structure of in of able kinds get or

is if big on as Kirk, referring your January today, billing a very, to quarter. a billing you're big the On deferred, end of is of the to QX very year, QX question Yes. quarter. always not

have you deferred So on that the revenue. flowing through

in you deal don't and pays number have, but doesn't with see in as signed companies revenue. of do revenue, deferred that pay monthly for can a this with We've RPO, we signed RPO. us customer arrear, $XXX arrears in deals it instance, Sridhar monthly million XX% is up And in However, that a RPO, us in a show so show they're up who up year-over-year. mentioned, we big quarter deferred

today with next from UBS. Our comes Karl Keirstead question

elaborate the that pretty moderated unpack Maybe growth revenue solid. April. you explain could I usage comment usually guidance, actually your why it's it on and also And at Mike, in when fiscal could look 'XX XQ and that you then does.

that believe according moderation guidance, in to feel into So one that rolled it like doesn't lead might whatever It May. be would to there April. your

if the curious interpretation. correct Just that's

would a and is was And an gave Well, we say And saying this what Europe more model. Remember, have our impacts long March and were time they the as I consumption is and some based guidance others Day reminder, does in off consumption. impact it is April muted And strong. or a week. daily February April seeing holiday. of customers through that this as just is Easter take that you in a what really very I'm Europe, on we're Ascension upon

I a follow-up. if could Mike, ask And Okay.

P&L roll-off be side, what You efforts storage tiered revenues And Was the roll-off to at some in April I see approximate that quarter. whereby around storage maybe the could had on begin had? the previously, reps March a to mentioned on the you impact including, storage impact the in that could the that able conference would case? think, we your

all the basis, customers, roll on of out annual pricing. commitment by of whereby at storage get started, amount it depending making an of we the end way, Sure. doing on tiered last you're you year, We our did to the and

percent are and $X So always is million. say list forget somewhere the customers other in pure in That's their storage million everyone. essence, that renew our storage the pretty price just the get And continue contracts. there customers, margin $X did as your out from rolled storage is of us $XX pure quarter I change. terabyte. We an impacted. mix you associated their But That between tiered and that that of big storage per impact given we've not XX% with of size. people have as rolling That not impacted to to the revenue discounted out remained discounted to to actually of revenue where continue that, a that that's that is because storage. is, much has consistent exactly what will their started at that

growth seeing actually storage We're in Snowflake.

Raimo with question Barclays. comes from Next Lenschow

new you The how more way the -- AI comments kind AI do how is do there to you vision optivability? do for knowledge? like, want for of need play world? guys. a own evolving? don't to a your like there's demarcation kind this your where all kind many just is evolution is where you people the of you you you question thank in LLMs want there of -- around Can Where a is higher today? like line Or -- Sridhar, play the with for in thinking kind to Obviously, to versus you is acquisition need that you of where

question. an are of impact you going at acknowledge stack. think a fabulous think AI models Like as can language important of to data a of is for what is all that have multiple us and foremost, it to first I levels This

faster. But data is like for does the the be to can So going enterprise data make that that of clean. a how other going think make much but is order in sure but people system old areas sexy, one such product to investment go that the something an as like in to is Copilot We be to huge pipelines, not and a on-prem creation presence perhaps the Snowflake, data a play also already translation. migrating nevertheless translation are to cleansing, We AI going is of the way a are the in required aided example, even going have which is we grade. things of engineering from think an that AI in by both to sure system, do those role amount that make data like in big of

in flips a accidentally SQL, then that stack, detect PII user a going Copilot language can our our enterprise models analysts' from table a the can degree a hands And to interface, significantly be ability now to very API, acclaimed of goes get with data know and put have into very it. of deviations writing then, a accelerate a if to with like user, example, or product productive into begins but up within distribution wonky, high data the For course, something reliability. to data help set which for of a business patterns. And we very

automating we And talking with of have there like developing for variety document like scratch impact. think is has we a a it I a are actually done analyst model And of so like will the perfectly broad things troubleshoot majority a applications small said to did to more or be can of language midsized that do. of Having work vast I'm which that for that problems, models, AI do, Arctic, about. things what an example, is my capable problems for from we the the model suffices for point some that,

you're and how on are And benchmark, throwing models. can get MMLU, are training those size we one talking of -- under a needing billions be there. are like at play there's investment dollars team small without to model and need where it's spending about very modest benchmarks there a depends people companies done level much dollars. to notoriously with I so amount talking a many don't that think academic at called huge difficult We

the to that focused think we company, a us we one are will for so The is is we're going customers going need is Mistral, of I there's have to that AI very Even long partnerships that people. partnerships take with finally, that of today, to model being we don't every AI other investments I about to ton a large we person add way that of landing deal with with amazing a making. And I use. with collaborating what on and that ton how doing with wrote will be every think our I make deliver Reika but amount have going company of with companies.

We we and in core they models the of models. are go at market together. other collaborate in XX,XXX able customers being players to value that a actively for to the need have developing set and And of obviously, we large good we very see our with kinds

And so I this terms continue we what is to do. indefinite future think to likely the need of for in

Our with from next question today Brent Thill Jefferies. comes

Mike, else was XX%. was But this that up that you starting you're or reacceleration? I on to you other of trends there haven't the acceleration $XXX deal. to the Any mentioned million helped RPO in anything maybe that seen know in see surprising you the quarter notable now?

Yes. year-over-year. Remember that XX% is up

million to deal that So There was there. $XXX signed subsequent the that, that year ago QX went comparison was in didn't have the $XXX another signed million deal into too. we

-- in and we deal will potentially as another is QX, million with as and our are but say do we what pleased did we I -- this and the $XX $XXX in So QX, number mentioned, in -- of CAP bookings I a quarter are million Xs mentioned, deal I will very too. there

business more of very and we're that making term. in with are pleased the So Snowflake commitment our our customers long

mentioned And for guess, where perspective, but the I of are are top quickly your from for new know your are Sridhar, the same, I rest the you the 'XX? priorities CEO, you priorities

to at support is with stress you see touched And incredible in the up related coming coming of potential our platform, like Snowflake. on that data. what Hybrid The AI in see in out, exciting able today across to the have I fast yesterday way We bear again one AI want applications I sitting then data faster we actually and we data them, definitely came like of is general this data theme an Arctic. all innovation But announcement that fruition we top list. product Snowflake things the our Services, run is more is can things to Build and Conference. But beyond layers the Cortex of Container massively for of players we that cloud. an there AI on chapter Iceberg which had are did to for new to how Tables with kind part, are kind AI but expand on that, is that the driving bring or market

So one innovation product is focus.

XX-odd time of also amount customers XXX meet road on I'm a enablement game importantly, say, the our I'm customers, in, on other efficiency. go-to-market that's on to the customers, rough for execution to go-to-market just zone the traveling folks that average, deliver on enablement suite just substantial others that to as on in like take our the That week. I the job days. within is of I product over front not would would That's to we teams having market, most with every Just what, focus also say broad how and applications these partners Snowflake my field, But products on get sure the the of in many priorities, kind helping able and priority inside. I market, be products upping talking in that a and my spent customers. of equally specialization make you a work to value also of great with. breakdown taking of with doing to

comes today Hedberg RBC. question next Our with from Matt

sales from does guess, expanding scientists, about need your forecast on your Sridhar, I to, And instance? you've focused to what your and reach. talking we R&D evolve in noted spend when a you lot and learned specifically, or change data time GPUs. But there of time say, your motion marketing making especially maybe investments when I'm and sales you're wondering for the

question. this previous a is and to Absolutely. touched on the great answer question, my This I in

kind with bit in leaders in is is the needed puts a for line that them applications we are actually of so that a product products product a specialized of from, similarly, share business can part their that a to example, their the from applications the needed collaborations I've team bring benefit offerings tell you using with partner exciting, conversation need effectively different who we additional with much do for actively yes, organization, these that with for for revenue I conversations these. And there world data opportunity is to we on managed of applications on where our be data example, of now to our Snowflake I data of in then able Snowflake, to focused call people more from that data think things say, companies that's the then on different going are is warehouses. customers. That something are had on us directly science team motions like revenue. language have a today that top we and how is become and write written little created with What helping many different them. And actually to top and customers providers because customers models. conversation that can running generate comfortable are people top feel drive AI, different We and explicitly

they that's it gradual are big they is Our change. a there to how is also booth make know, into you But go-to-market going Absolutely, analysts. get that motion. magic from is a AI going to that change all our Snowflake. use as And available we

And our We are a take looking organizations organized constantly what's for problem. how specific particular field way customer to and or a best reflected in that market how to solve the managed. you to see are product

one I color on said question on a just on consumption seen bit great. then a just super May. quick Mike. sounds back appreciate based slow versus you've your a you you maybe seasonally week. like traditionally? this trends. That's That's the That's know a bounce guidance guess what I what May April you seen maybe for helpful. great. I Have And

consumption As inside the that's upon and quarter, there. seeing based we're in reflected said, patterns is guidance I our

comes Our Piper Bracelin with Brent Sandler. from next question

you in unlock can to environment Iceberg? Sridhar, Maybe flagged go as opening growth. spending why But Iceberg view. you an that moves remarks, your how that's longer-term up where for a could Snowflake actually walk the potential through just accelerate could in customer

there storage to sum But or cloud is it a capability to right is will a fact to into XXXx And on that of an an able the some matter Snowflake. in in they So the because XXX data. have of capability. to Iceberg first Iceberg a from of customers move be portion Snowflake that want all, lakes structured will is their for read run And data interoperable top format. a data is format of be yes, file and or most of they is the data data sitting that often has that application that general inside customers

pipe we Snowflake with this to able have long on of information wait insight engineering use data. a or is for a the at that's about. that Iceberg lot top under a you Christian order data And future these whether don't already I'll becomes sudden, has to all workloads have cases, seamless for on. and of also word, it's a for this unlock in directly time support and that our have, of I'm say pitch been very to of Now format Iceberg all win he's it existing can some into be whether as a time with customers talking a and it, run this

would Sridhar just said. I to what Yes. add

use existing have of existing customers, they want think petabytes into makes We have be sense of be don't cases to with -- to have but ingested data. tens our in of where [indiscernible]. of copied many to ready have they Snowflake, that data, They lots that combine they that it They analyzed. Snowflake data or for data,

through is that. and [indiscernible] announcement what Microsoft So available data take about make real. last the Snowflake. in is Sridhar do X it we with very opportunity the is the alluded Iceberg, days made to, that we And available also in the How [indiscernible] to

that So a framed not long-term for. is the lot wait not have something we'll that's It's to a one. opportunity

sounds in here. It Mike another tough. macro like down another I clarification in one $XXX Quick that? million big driving for Is is What's knocking Last checked, some QX. QX. AI helping? deals, pretty the map deal road the

the customers, around of that's these quarter doing And driving all with in customers -- is and are data one they're both warehousing, these AI. one and business many their big we make these it is to their core a interested QX, the are But core do in the to and have These business. but going they us. what's really want to that commitments and current how still run we're what Q in existing to discussion all long-term core customers to now, large we are

help very several large a AI not of in access very Snowflake. one and And And very its as mentioned, are customers these data actually into of and absolutely, these on but these, data are the folks be deals, having bet that on monetize having applications the AI which the these that other should powerful a investments data all this large as customers the catalyst. is these snowflake But in creating see of at AI their several by their large leaning you then serves a Mike by platform. Snowflake top conduit as ones, collaborations are core,

Our next question today from comes Colville. Patrick

on This ago, Snowflake for Joe but CEO know been X about year a you is Colville. Sridhar, [indiscernible] I about joined now you've Patrick for months.

curious And into if So of few CEO other role? worth surprised the out unit or just streamed your you've a there's store. also wondering that you stepping products, then and on calling that's view anything since learned that

there. talk bit seeing engagement could you you're If about a customer

also as here lot is had respect our customer how which feedback conversations. have hard make of close to important write efficient releasing for to ownership. I AI to our truly how that things do of some to to lowering been that The the we dramatically easy and able core to that. is new tech about is thing maintenance-free, amount customers products. anybody how pretty obviously I've pleasantly said, get for because is we have And and year. and trouble And reviewers misty total we uniformly, I've surprise tough do me, preserve a cost pretty at quality the take the us from the can Snowflake AI. an while I that now is continues layer, are that is it use, It easy a lot product, of it is SQL, that, yes, the with we Cortex, a love Yes.

surprise those -- like combination quality prototyping know, to rapid without an of surprise, every Snowflake. for application bring hosted a pleasant write think on an use knew it, it think able a be time and up. And terms while Streamlit, that a don't And it of incredibly powerful a customers and for that simplicity It's Streamlit do any being have having to Snowflake is still little is work. bit ease is I environment? other of then is it I in I

up have cluster. to a You don't Kubernetes bring

that none You of don't have a to binary, stuff. deploy

little application, and a just runs. write You it

in perspective, hugely, that's Streamlit our highlighting, forward. on is on hugely as have example, snowflake efficiency functionality, information, our There or super operational an users. And incredible these notebooks be important for for Snowflake the in to of it to it it showcasing but are our run personally making chatbots finance run we has priority There of broadly. as a it's the been been going of compensation distribute And it's been are because easy application. Snowflake working a they customer applications think positive have And even inside very example, that the ton whether whether deployment. to or instance things is already created, all this folks just information with I forecast Snowflake, really that going which one, team adopted just part these also that is very, like running that

of kind side. on in It later public that positive is that them meant in this address GA workload analytics Snowflake. Unistore these that lots on things of be is in So often preview. And call top then really It than as year. Hybrid more Tables, will of the runs different on workload we a to transactional are or nature

need applications opens the new same up Snowflake. on can magic, it to don't Snowflake that I up stand think servers. top run of sort classes you of is effectively It's very several which of

on customers of can work with X? You lot. Christian, them see, it's think, hybrid expect or don't tables. top need on a go lot of I any to And are whole deal these go that we up We XXX actively other to thoughts do close to by a using absolutely that number clusters. Kubernetes

And [indiscernible]. customers lot and of year. X end on the is the many general likely That actually generally all has of at [indiscernible] they clouds. No. for a this valuation have Streamlit the driven are waiting not of our availability available

from question with Our Stifel. today next comes Brad Reback

on Brad. This is for Rob

yesterday, the few maybe strategy Sridhar, or Christian companies investing opportunity wondering ventures and trying months, that is big underlying you're that and investments, there is observability a Snowflake to including the what few I'm visibility in For the over type of address? some with logging is past some

happening Snowpark context our go an quality [indiscernible]. and One for to be and I container for service But observability what observability more we well host code. is data here. have also able like doing? for into know evolved is as How we'll my to observaility and business ecosystem variations understand customers big continue and code. data is will application Or Christian us, important very troubleshoot help data is us the do both there's on platform, to be for rich is logic [indiscernible], and a partner and Snowpark. as how do is an priority and Observability things That the Snowflake with monitor important I itself. all understand be data able data what's on that also

on on make partnerships on one that Snowflake applications And top is is to that vibrant general end will close example, want top collaborating, give sort a be of that of just sometimes ecosystem in of. comment on I platform companies develop have with because applications data keeps that investing we up we several list great to and going platforms, But to another lot interesting the of a on is And build top Snowflake. Snowflake area. observability and there customer a of

Tyler question next Citi. from Our comes with Radke today

rest talk more from do maybe the this some small talked of of was start-ups, customers, year? quarter. strength this the smaller upside this throughout about you Or you you about those during of And just the the to GenAI a nature customers Could one-off? companies? Mike, persist expect

broad-based, the board. these all across much and companies of it's there, too, very very I'm a and non-GXK and was it's some of industries in is companies, It about, private lot across are talking the large

And it. and side. sales Got quick on a marketing the follow-up then

that Is and expenses quota-carrying Just that us primarily quite sequentially. hires? higher a a what's bit investment? both folks? count marketing give So on the head exactly sense it driving increased Is

Well, expensed mentioned being expense deferred the first of at you end immediately going were expense see in our on and we comp of versus plan, amortized. of change the last commission quarter because side, more all, to

the organization, organization principally this sales As our and throughout see I ramp think you including in that we in the on SDR number invest the our doesn't people but we team to the we're add said, within the can But it them. a good a did continue lot really side as to change the cash And will year, headcount, I feel are we as pretty adding well will the of in looking development, quarter, we about the as SEs flow we first acquisition see it We've numbers business us. business. reps, And hit and the sales expense. constantly we the as at are space adding commercial company. well, in too,

Our final today Wolfe Alex Zukin Research. comes from question with

bit just Cortex share Congrats a cases maybe on Maybe a interesting quarter. prepared on vision deploying in you of how and for more, start are of it from use some Can Sridhar, some in your mentioned impact deploying maybe [indiscernible] [indiscernible]? when it can the and they thinking customers how And more the first great you dig some remarks. really [indiscernible] of production larger Cortex Arctic.

and is your figure questions. information embedding a by vector for repository, customer your like little of on what history. sentiment a things gist the is question can text feedback able you like And to categories unstructured over, using question, I'll central answered bit forum, example, like analyze, is got easy out, things I for say, definitely language magic there like it. makes to new ability process. think are answer automate the or say, What new even address able of where the Snowflake be based I that already a a be then out new a the they comes the that to to today as forum [indiscernible]. Increasingly, figure say, in, been index, imperfectly cases, I what this came this stack, of question most and problem The related to generate well, for are answered? think you let's question -- will soon do companies where this able an Cortex models are simply do as of let a the generator auto in support Snowflake a bunch let's This they for is you has previously for let's of search AI

chatbot, model which from to not answer to And in me, basically where get and is a Snowflake, dispatched just from getting what it. But can is there service repository decides questions does rep the new he company sitting truly that is obviously, pure scratch a that that's requests with logic prototype, can is language a just customer the about to central because a So interact. know a like there's this. in outside do something control that routed to

questions have is from, applications is like is data like our say, a We is consumption. lot things extracting commit of solved. sentiment get this no they trivial. But at I of transformation. basically or IT somebody for let's about driven information conversation generates have If also example, automate more model about quick one all usage, problem all that to interesting that these detection, language We this internally get deployed images. what by extracting there's on is stuff of talked the Cortex make pre other complicated, a things. And consumption. JSON, summarization about those from There of perhaps all are like beauty of our deployed. already you but Snowflake, so is is a just We can like really

great And software And and Snowflake engineering the of usage. that acting means That's before hours. drive tasks runs so Snowflake coming that a every it's complex required almost X [indiscernible] in into on this out in it also every simple come pipeline applications anyway. hour, how is that making all like little become that just obviously, data

one say So language things are just models. I'm accelerated talking that cases would of that are the you about by that I like Snowflake use with presence could -- is This these category. massively do the

much access is that data it structured do is easier make Snowflake. models to data how The is language that really second in one in

idea data refer as it's The like currently to is it me heard API. hard. quite a that You've basically

public You is a go people be What of by it have preview, you conversation perhaps it new we in this is will semantic have yet essentially to analyst, tool, information make about any to get are through schema, to snowflake pieces an information. it. BI which working possible on, a soon, with product giving a by for not a

coming like quite yet, I'd Scarpelli but aren't unlock that Mike out business user here that there that knows to actually big the he's trust give about to to now and We to of And much access it's larger information any [indiscernible] the course, that where within information and able directly base. query is authorized that's is has user is data access it. Obviously, but that user Snowflake. but there complement a the interact much to direct base a can of data larger finance Snowflake, a governed, with

on I keep going can about. super hopefully, But There's feel on. application. get and of lots passionate a is more. that This for I'm the you a topic kinds

class first class data. data, second structured is the The unstructured is

any Our together box to these is it. all vision question you to an and to be answer able ask get where enterprise for of can the bring a like single into

It give maybe exceeding or did wasn't any Makes then, talked sense. about expectations, maybe just specific any dig strength? But Is to Snowpark to to anything geos specifically more that into quotas. -- you broad-based customer contribute And momentum I any there there talked is size. I like you wanted Mike, consumption strong us driver. about verticals around there? you or a exceeding anything that can were guess

good strength business, continues said, in the it Financial some though, we that company, the core and Their the was health but in the really care our be did uptick a verticals. biggest. of It's across broad-based. see outperformed services No. groups to number technology our all With space. and it's other pretty growth in

today's will you conclude Thank conference all That your for participation. call.

now may lines. disconnect You your