高盛-美洲科技：第三届年度硅谷人工智能实地考察收获-Takeaways From Our 3rd Annual Silicon Valley AI Field Trip-20260821

htEtqpi:t/wse.vaaruhelist

21August2026|1:24AMPDT

AMERICASTECHNOLOGY

TakeawaysFromOur3rdAnnualSiliconValleyAIFieldTrip

Wehostedour3rdannualSiliconValleyAIFieldTripon8/18-8/19,featuringAI

companies,VCsandresearchersfromStanfordandUCBerkeley/UCSF.Model

capabilitiesarecontinuingtoimprove,agentsareprogressingfromassistanceto

workflowexecutionandmonetizationisexpandingbeyondseatstoward

consumption,transactionsandoutcomes.Thestrongestbusinessescombine

proprietarydata,domainexpertise,customercontext,workflowownership,

distribution,verificationandpermissiontoact.Agenticadoptionshouldadvance

fastestwhereoutputsareverifiableandresponsibilityforerrorsisclear.Open

modelsshouldgaintokenvolumeacrossroutinetasks,andfrontiermodelsshouldretainvaluewherereliabilityjustifieshighercosts,supportingcontinuedtokenandcomputegrowth.AIshouldalsoexpandcybersecuritydemand,andphysicalAIwillrequiredistinctarchitecturesandcommercializationstrategies.ForBusiness&

InformationServices,AIshouldincreasethevalueofdifferentiatedinformation

assetsandhelpplatformscapturemorecustomerspendingthroughembedded

workflows.ForSoftware,selectvendorsarewellpositionedtohelpcustomers

navigateanevolvingintelligencecurvethatsegmentsworkflowsintofrontiervs.

non-frontiertokensandenrichesmodelswithbusiness-specificcontext.Our

preferredAI-leveragedideasareIRM,MCO,MSCI,SPGIandTRIinBusiness&

InformationServicesandMSFT,MDBandRBRKinSoftware.Thetripalsoreinforcedourconstructivelong-termviewsonCRWD,NET,PANWandSNOW.

TripAgendaandBackground

Wehostedour3rdannualSiliconValleyAIFieldTriponTues,8/18,andWed,8/19,focusedonmajorthemes,developmentsanddebatesinAI.Day1stopsonthefieldtripincludedprivatecompanypresentationsandproductdemoswiththe

Co-Founder&CEOofDaloopa,VPofSoftwareEngineeringfromDivergent,Founder&CEOofClioandCo-Founder&CEOofCorgi,followedbyventurecapitalvisitstoLightspeedVenturePartners,KleinerPerkinsandMenloVentures,aswellas

presentationsandagroupdinnerwithresearchersfromStanfordUniversity’s

InstituteforHuman-CenteredAI(HAI)andDepartmentofAeronautics&

Astronautics.Day2stopsonthefieldtripincludedcompanypresentationsandproductdemoswiththeCFOofHarveyAI,CEOofMoody’sAnalyticsatMoody’s

GeorgeK.Tong,CFA

+1(415)249-7421|george.tong@GoldmanSachs&Co.LLC

GabrielaBorges,CFA

+1(212)902-7839|

gabriela.borges@GoldmanSachs&Co.LLC

MatthewMartino

+1(212)902-0695|

matt.martino@

GoldmanSachs&Co.LLC

SamiNasir,CFA

+1(415)834-7967|sami.nasir@GoldmanSachs&Co.LLC

AlexLakritz

+1(415)249-7072|alex.lakritz@GoldmanSachs&Co.LLC

MaxGamperl

+1(415)249-7311|

max.gamperl@

GoldmanSachs&Co.LLC

SelinaZhang

+1(212)357-9979|

selina.zhang@

GoldmanSachs&Co.LLC

GoldmanSachsdoesandseekstodobusinesswithcompaniescoveredinitsresearchreports.Asaresult,investorsshouldbeawarethatthefirmmayhaveaconflictofinterestthatcouldaffecttheobjectivityofthisreport.

Investorsshouldconsiderthisreportasonlyasinglefactorinmakingtheirinvestmentdecision.ForRegAC

certificationandotherimportantdisclosures,seetheDisclosureAppendix,orgoto

/research/hedge.html.Analystsemployedbynon-USaffiliatesarenotregistered/qualifiedasresearch

analystswithFINRAintheU.S.

GoldmanSachsA

tetrpicsa:s/n.ology

(MCO),Founder&CEOofVercel,CFOofClickHouse,Co-FounderofSimile,aventurecapitalvisittoIndexVentures,andapresentationbyaProfessorofComputationalPrecisionHealth,Statistics&ComputerScienceatUCBerkeley.

2026GoldmanSachsSiliconValleyAIFieldTrip

Time

Participants

Type

Speakers

Title

Day1–Tuesday,August18,2026

8:30AM–9:15AM

Daloopa

Private

ThomasLi

Co-Founder&CEO

9:15AM–10:00AM

Divergent

Private

SamMiller

VPofSoftwareEngineering

10:00AM–10:45AM

Clio

Private

JackNewtonJohnForeman

Founder&CEO

ChiefProductOfficer

10:45AM–11:30AM

Corgi

Private

NicoLaqua

Co-Founder&CEO

12:30PM–1:30PM

LightspeedVenture

Partners

VentureCapital

GuruChahal

SebastianDuesterhoeft

Partner

Partner

1:45PM–2:45PM

KleinerPerkins

VentureCapital

AdityaNaganath

Partner

3:00PM–4:00PM

MenloVentures

VentureCapital

RamaSekharMattKraning

Partner

Partner

4:15PM–5:45PM

StanfordUniversity

University

KianaJafariDuncanEddy

PostdoctoralScholarinAeronautics&Astronautics

PostdoctoralScholarinAeronautics&Astronautics

6:00PM–8:30PM

StanfordUniversity

GroupDinner

KianaJafariDuncanEddy

PostdoctoralScholarinAeronautics&Astronautics

PostdoctoralScholarinAeronautics&Astronautics

Day2–Wednesday,August19,2026

8:30AM–9:15AM

Harvey

Private

AlanGhelberg

JohnLaBarre

MadeleineHyde

CFO

GeneralCounselLegalEngineer

9:15AM–10:00AM

Moody’s(MCO)

Public

ChristinaKosmowski

CihanBiyikoglu

ShivaniKak

CEOofMoody'sAnalytics

HeadofProduct&EngineeringatRMS

HeadofInvestorRelations

10:00AM–10:45AM

Vercel

Private

GuillermoRauch

MartenAbrahamsen

Founder&CEO

CFO

10:45AM–11:30AM

ClickHouse

Private

JimmySexton

CFO

11:45AM–12:45PM

Simile

Private

MichaelBernstein

MadisonFox

DannyWymer

Co-Founder

FinancialServicesVerticalLead

EnterpriseGTMLead

1:15PM–2:15PM

IndexVentures

VentureCapital

NinaAchadjianNinaGerson

Partner

Partner

3:15PM–4:15PMUCBerkeleyandUCSFUniversityAdamYalaAsstProfofComputationalPrecisionHealth,Stats&CS

Source:GoldmanSachsGlobalInvestmentResearch

Theagendaincluded:

Companypresentationsandproductdemoswithventure-backedstartupstodiscusstheirAIstrategiesandproducts.ParticipantsincludedThomasLi,

Co-Founder&CEOofDaloopa;SamMiller,VPofSoftwareEngineeringatDivergent;JackNewton,FounderandCEOofClio;andNicoLaqua,Co-Founder&CEOofCorgi.

VenturecapitalvisittoLightspeedVenturePartnerstodiscusstheoutlookfor

frontierintelligence,acceleratingmodelcapabilities,thedivisionofworkloads

betweenopenandclosedmodels,enterpriseAImonetizationandthebroadeningofvaluecreationacrosstheAIstack,featuringPartnersGuruChahalandSebastian

Duesterhoeft.

VenturecapitalvisittoKleinerPerkinstodiscusstheexpansionofagenticAI

21August20262

GoldmanSachsA

tetrpicsa:s/n.ology

21August20263

acrossknowledge-intensiveindustries,improvingapplication-layereconomics,thesourcesofdurableAIapplicationmoats,disruptionrisksforlegacysoftwareandemergingopportunitiesacrossinferenceinfrastructure,featuringPartnerAdityaNaganath.

VenturecapitalvisittoMenloVenturestodiscusstheroleofverifiableoutputs

andproprietarydatainenterpriseAIadoption,theevolutionofsoftwarefrom

systemsofrecordtosystemsofaction,cybersecurityopportunitiesandrisksandtheoutlookforcomputedemand,featuringPartnersRamaSekharandMattKraning.

PresentationsbyresearchersatStanfordUniversityonworldmodelsforphysicalAI,theuseofuncertaintytoimproveAIsafetyandtheaccountability,verification

andtrustinfrastructurerequiredtodeployenterpriseagents,ledbyKianaJafariandDuncanEddy,PostdoctoralScholarsintheDepartmentofAeronautics&

Astronautics.

Companypresentationsandproductdemoswithventure-backedstartupsto

discusstheirAIstrategiesandproducts.ParticipantsincludedAlanGhelberg,CFOofHarvey;GuillermoRauch,Founder&CEOofVercel;JimmySexton,CFOof

ClickHouse;andMichaelBernstein,Co-FounderofSimile.

CompanypresentationandproductdemowithMoody’sfocusedonagenticAI

products,connectedintelligenceacrossriskdomainsandtheuseofproprietarydataanddomainexpertisetoautomateenterpriseworkflows,featuringChristina

Kosmowski,CEOofMA,CihanBiyikoglu,HeadofProduct&EngineeringatRMS,andShivaniKak,HeadofInvestorRelations.

VenturecapitalvisittoIndexVenturestodiscussAI’simpactonsoftwareand

companycreation,thecharacteristicsofdurableAIbusinesses,enterpriseadoptionandROI,theoutlookforincumbentsandAI-nativeverticalapplicationsandevolvinginfrastructureandapplication-layereconomics,featuringPartnersNinaAchadijianandNinaGerson.

PresentationbyaprofessoratUCBerkeleyandUCSFontheuseofAItopredictpatientoutcomes,personalizescreeningandtreatmentdecisionsandaccelerateclinicalvalidation,includingtheshiftfromnarrowimagingtoolstobroadmedicalfoundationmodels,ledbyAdamYala,AssistantProfessorofComputational

PrecisionHealth,Statistics&ComputerScienceatUCBerkeleyandUCSF.

21August20264

ImplicationsforBusiness&InformationServicesandSoftware

Business&InformationServicesSectorImplications

Proprietaryinformationassetsbecomemorevaluablewhencombinedwithdomainexpertiseandworkflowcontext.AIincreasestheutilityofdifferentiateddataby

makingiteasiertoretrieve,connectandapplyinsidecustomerdecisions.Thatsaid,

durabledifferentiationdependsonmorethanowningalargedataset.Leadingplatformscombineauthoritativecontentwithvalidatedmodels,specializedtaxonomies,customercontextandexpertswhounderstandhowtheinformationshouldbeused.This

combinationcangeneratemoreaccurateandverifiableoutputsinfinancialanalysis,

legalservices,insurance,riskmanagementandhealthcare.Business&Information

Servicescompanieswithunique,continuouslyrefresheddataanddeepindustry

expertiseshouldthereforestrengthentheircompetitivepositionsasfoundation-modelcapabilitiesbecomemoreaccessible.

AIexpandsthesectorfrominformationdeliverytowardworkflowexecution.

Business&InformationServicescompanieshavehistoricallymonetizeddata,analyticsandprofessionalexpertisethroughsubscriptions,reportsandlabor-intensiveservices.Agentscannowstructureunorganizedinformation,performanalysis,monitorchangingconditionsandinitiatedownstreamactionswithinacommonworkflow.Daloopacan

updatefinancialmodelsandcompleterepeatableresearchtasks,ClioandHarveycanexecutelegalworkflowsandMoody’scanconvertinsurancesubmissionsinto

decision-readydatawithinseconds.Thesecapabilitiesallowproviderstoaddressalargershareofcustomerspendinginsteadofremainingoneinputintoabroader

process.Thestrongestplatformscouldevolvefromsystemsofinformationintooperatingsystemsforknowledge-intensiveindustries.

AIcanexpandaddressablemarketsbyconvertingprofessionalworkinto

repeatablesoftware.Financialanalysis,legalresearch,insuranceunderwritingand

marketresearchcontainexpensiveworkflowsthathistoricallyrequiredsubstantial

professionallabor.AIcanencodeportionsofthatexpertiseintoreusableagents,

makingexistingworkfasterandpreviouslyuneconomictaskscommerciallyviable.Lowerdeliverycostscanincreaseserviceaccessibility,usagefrequencyandthenumberof

questionscustomerscanaffordtoanswer.Thiscreatesanopportunitytocapture

professional-servicesspendinginsteadofonlycompetingforexistingsoftwarebudgets.Businessmodelsshouldbenefitmostwhereproviderscanautomatestructuredportionsofaworkflowbutpreserveexpertjudgmentforforecasts,consequentialdecisionsandexceptionhandling.

Monetizationshouldbroadenbeyondseatstowardusage,transactionsand

outcomes.Seat-basedpricingbecomeslessalignedwithcustomervaluewhenagents

completemoreworkindependentlyandeachprofessionalcansupervisegreateractivity.Business&InformationServicesplatformscanmonetizeincrementaldataconsumption,completedanalyses,processeddocuments,transactionsandagentusage.Daloopacitedroughly100xgrowthindataconsumptionacrosscertainintegratedagentworkflows,

andCliocombinessubscriptionswithpaymentsandothertransaction-basedrevenue.

Moody’sisalsobeginningtochargeincrementalsubscriptionfeesforMCPaccessand

separatefeesforagentusage.Thesemodelscanallowrevenuetogrowindependentlyofcustomerheadcountandgiveprovidersadirectwaytoparticipateintheproductivity

21August20265

gainstheirproductscreate.

Incumbentsretainmeaningfuladvantages,butAI-nativeentrantscanwinthroughdeeperworkflowcontrol.Establishedplatformsbenefitfromtrustedbrands,

embeddeddistribution,accumulatedcustomercontextandaccesstotheapplicationswheredecisionsareexecuted.Theseadvantagesgiveincumbentspermissiontocreaterecords,posttransactions,processpaymentsandtriggeractionswithoutrequiring

customerstotransferinformationbetweensystems.AI-nativeentrantscanstillgain

sharethroughmateriallybetterproducts,specializedworkflowsordifficult-to-replicateinfrastructure.CorgicombinesAIwithinsurancelicenses,regulatorycapitalanddirectcontrolofunderwritingandclaims,andHarveycombineslegalexpertisewith

workflow-specificagentsandevaluations.Themostexposedprovidersarethosewithcommoditizeddata,shallowworkflowintegrationorbusinessmodelstiedprimarilytolaboranduserheadcount.

VerificationandaccountabilitywilldeterminehowquicklyAIreachesproduction.Business&InformationServicesworkflowsfrequentlyinvolvefinancial,legal,regulatoryoroperationalconsequencesthatmakeunverifiedoutputsdifficulttodeploy.Adoptionshouldprogressfastestwheredecisionsarebounded,resultscanbechecked,incorrectactionscanbereversedandresponsibilityforerrorsisclear.Source-linkeddata,audittrails,confidencethresholds,independentevaluationsandtargetedhumanreviewcanreducetheoversightburdenwithouteliminatingaccountability.Providerswithtrustedcontent,validateddomainmodelsandestablishedregulatoryrelationshipsshouldhaveanadvantageovergeneral-purposeapplicationsinthesemarkets.Newopportunitiesmayalsoemergeincertification,monitoring,benchmarking,incidentreportingand

insuranceasenterprisesrequireinfrastructurethatallowsagentstoactsafely.

SoftwareImplications

Opensourcevs.frontiermodels:theoutcomeislikelymorenuancedthaneithercampsuggestsonthepathtomoregranularworkflowsegmentation.

Thefrontiercamparguesthatmodelprogressissignificantlyunderestimated

becauseenterprisebenchmarksarepoorproxiesforrealcapabilitygains.This

makesstep-functionimprovementsinintelligencedifficulttoobserve.Ifintelligenceisthelargestaddressablemarketinhistory,theremaybenoshortageofproblemsforincreasinglycapablefrontiermodelstosolve.Interestingly,several

early-to-marketAI-nativeapplicationcompanieswilltalkaboutmodel

diversification,butstillremaininglargelydependentonfrontierprovidersin

productionenvironments,becauseoftotalcostofownershipconsiderations(anytrade-offinaccuracyisnotworththemodelsavings)andproductpriority

considerations(focusonplatformfunctionsnow,andcostlater).

Atthesametime,industryexpertssuggestedthatmostenterpriseworkflowsdonotrequirefrontier-levelintelligence,andcustomersarebecomingmorewillingtotrademarginalperformanceformateriallylowercosts.OneVCsuggested90%oftokenswillgotoopensourcein~12-18months.Earlysignsofpricingpressure,risingusagelimits,andexamplesofcustomersreducingfrontiermodelconsumptionsuggest

modelprovidersarealreadycompetingoneconomicsratherthancapabilityalone.Themorenuancedviewisthatfrontiermodelsretainthehighestvalueworkloads,

21August20266

whileopensourcecapturesthemajorityofvolume.

AsthePareto-optimalcurveofintelligenceebbsandflows,weareincreasingly

confidentthatindependentsoftwarevendorslikeMicrosoft,Cloudflare,DatabricksandVercelwillbeabletocapturevaluebygivingenterprisestoolstoorchestrate

modelswhilekeepingtheirowncontentproprietary.

RiseofworldmodelssuggeststhatthenextAIplatformshiftmaylookbiggerthanLLMs.AgrowingnumberofresearchersareshiftingfocusbeyondLLMsoverthelast18months,arguingthatnext-tokenpredictionaloneisunlikelytocapturehowthereal

worldbehaves.Instead,thenextgenerationofAIwillneedtomodelenvironments,

causality,physics,andreal-worldinteractions.Thecompetitivemoatcouldalsolook

differentfromtheLLMera.Ratherthantrainingonlargelysharedinternet-scale

datasets,manyworldmodelapplicationsdependonhighlyspecializeddatatiedto

physicalsystems,industries,andoperatingenvironments.Thatcreatesafundamental

debatearoundwhethervalueaccruestobroadfoundationalmodelsorvertically

specializedsystemsbuiltonproprietarydatasets.Theeconomicopportunitycould

ultimatelyexceedthatoflanguagemodels.Physical,industrial,scientific,androbotic

systemsrepresentamuchlargeraddressableproblemsetthantextgenerationalone,

withmanyworkloadsrequiringsubstantiallygreatercomputeintensity.TokendemandfromworldmodelscreatesanScurvethatwilllayerontopofourenterprise

forecastforcomputetosupport24xmoretokensinthenext5years.Thislikely

drivestightersupply/demanddynamicsforlonger,benefitingMicrosoft,OracleandCoreWeave.

Durabledifferentiationwillcomefromownershipofworkflowcontext,notjust

data.Theverticalvs.horizontaldebateincreasinglymissestherealsourceof

differentiation.SimpleAIwrappersappearmostvulnerableasmodelcapabilities

improve,whilehorizontalplatformsbenefitfromscalebutremainexposedtofeature

competition.Thestrongestpositionsmaybelongtoworkflow-nativesoftware

companiesthatcombinedomainexpertise,embeddedprocesses,andproprietary

context.InanAIworld,owningtheworkflowmaymattermorethanowningthe

application.Thesameprincipleappliestodata.Accesstocustomerdataisoften

mistakenforamoat,butmanyformsofenterprisedataaccessareeffectively

commoditized.Anyvendorintegratedintothesamesystemscanoftenseethesame

underlyinginformation.Themoredurableadvantagecomesfrombeingembeddedin

theworkflowthatcontinuouslycreates,structures,andenrichesthatdataovertime.Assoftwarecreationbecomescheaperandfaster,uniqueworkflowcontextmaybecomeoneofthefewremainingformsofdefensibledifferentiation.Shopifyinourviewisa

goodexampleofleveragingincumbencyintoableeding-edgeproductroadmapinavertical-specificcustomerbase.Samsara(IOT)illustratesthesamedynamic,withitsconnectedassetfootprintcontinuouslygeneratingtheoperationalcontext

requiredtodeliverdifferentiatedAIproducts.

Agentsarebecominganewtopofthefunnel.Historically,developersandenduserschosetoolsdirectly.Inanagenticworld,softwareincreasinglyneedstobediscoverable,callable,andusablebyagentsactingonbehalfofusers.Vercel’scommentarysuggeststhatthefundamentalbuildingblocksoftheinternetareshiftingfromusersand

applicationstowardagentsandtokens,creatingaworldwhereinfrastructureisno

longeroptimizedforhumaninteractionalone.Ifagentsbecomeameaningfulsourceoftrafficcreationandworkfloworchestration,thebiggestbeneficiariescouldbethe

21August20267

infrastructurevendorsthatsitclosesttowherethoseagentsoperate.

Theinfrastructurestackisbeingoptimizedforagent-nativeworkloads.VercelandClickHousebothnotedthatAIworkloadsplacefundamentallydifferentdemandson

infrastructure.Agentsgeneratemorerequests,executemoreactions,makemore

decisions,andinteractwithmoresystemsthantraditionalsoftware.Thatshiftsthe

bottleneckawayfromapplicationdevelopmentandtowardtheinfrastructurerequiredtosupportautonomousexecution.Real-timedatabases,low-latencycompute,scalabledatapipelines,andgloballydistributedsystemsbecomeincreasinglyimportantbecauseinfrastructureisnowservingmachinesoperatingatmachinespeedratherthanhumansoperatingathumanspeed.

OurindustryconversationsechoedtheconsensusviewthatSecurityshouldbenefitfromAI,andincumbentscouldbenefitdisproportionately,withafocusonSOC.AIislikelytoexpandtheattacksurface,similartopriorplatformshiftslikeinternetand

cloud(seeourlagbetweenAIandAIsecurityspendnote).Itshouldalsomakeattacks

morefrequentandmoresophisticated,especiallyasopen-sourcemodelsimproveandputstrongercapabilitiesinthehandsofattackers.Thiswilllikelydriveanear-termpushtowardpeopleandprocess(e.g.forpatchingandhygiene)andproduct

experimentation.ThereisascenariowhereAIinthehandsofthedefendersshiftsthe

oddsofsuccesspermanentlyinfavorofenterprises,astheymaygainperfectvisibility

intotheirenvironmentssuchthatattackersonlyneedtomakeoneanomalousmovetobecaught.Atthesametime,AIalsocreatesanopportunitytohelpenterpriseswithtwocorecyberproblems:talentshortagesandtoomanypoorlyintegratedvendors.ThisisparticularlytrueinSecOps,wherethereisanopportunitytorebuildwithbetter

automation,continuousremediation,andsystemsthatareconfiguredcorrectlyfromthestartratherthanstitchedtogether.OneVCnotedthatmostorganizationsdon’teven

havethebasicsofdataaggregationandorganization,suchthattheycouldintroducemoresophisticatedreasoningontopofdatastores.Thislikelycreatesapushtoward

modernizationbuiltontopofaSIEMdatastore,whileanewlayerofagent-nativetoolsemergestoreasonoverthatdata,enforcecontrols,andtakeactioninformatsbuiltforagentsratherthanhumandashboards.

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TakeawaysfromPrivateCompanies

Daloopa

CompanyIntroduction

DaloopaisanAI-poweredfinancialdataandresearchplatformthatautomatesthe

extraction,standardizationandvalidationoffinancialstatementlineitems,KPIsand

companyguidancefromregulatoryfilings,earningsmaterialsandothercorporate

disclosures.Theplatformisdesignedforequityanalysts,investorsandfinancial

institutions,providingsource-linkedandaudit-readyfinancialdatathatcanbe

integrateddirectlyintoresearchworkflowsandvaluationmodels.Itsupportsmodel

maintenance,earningsanalysis,financialforecastingandinvestmentresearch

workflows.Theplatformisusedbyhedgefunds,assetmanagersandinvestmentbanksseekingtoimproveproductivity,dataqualityandworkflowefficiency.

ProductDemo

Daloopa’sproductdemoshowcaseditsAI-poweredfinancialdataplatform,which

collectseveryhistoricalfinancialstatementlineitem,KPI,companyguidancemetricandnon-GAAPadjustmentfromprimarysourcedocumentsandlinkseachdatapointtotheunderlyingdisclosureforverification.Thecompanydemonstratedhowitsreal-timedatainfrastructurecanautomaticallymapnewlyreportedfinancialinformationinto

customer-specificExcelmodelsregardlessoftheirstructure,reducingthemanualworkrequiredtoupdatemodelsduringearnings.DaloopaalsoshowedalibraryofAIskills

thatusesitsstructureddatatoperformworkflowssuchasearningsreviews,researchnotegeneration,guidanceanalysis,supplychainmappingandindustryanalysis.Thedemoillustratedaknowledgegraphthatorganizescompaniesbysectorandconnectseachcompanywithpreviouslycompletedanalyses,creatingacontinuouslyupdatedresearchmemorythatcansupportadditionalquerieswithoutregeneratingthe

underlyingwork.Daloopaalsopresentedanautomaticallygeneratedcompanymodelthatincorporatedhistoricalfinancials,consensusestimates,segmentforecastsand

supportinganalyses,withoutputslinkedtotheiroriginalsources.

MeetingTakeaways

Financialdatainfrastructureisthecoredifferentiator.Daloopaextracts,structuresandsourcesdisclosedfinancialdata,KPIsandcompany-specificadjustmentswhile

preservingtheterminologyusedbyeachcompany.Eachdatapointlinkstoitsoriginalsource,allowingcustomersandAIsystemstoverifytheinformationbehindanoutput.Proprietarydatapipelines,structuredoperatingprocessesandaroughly400-personvalidationteamhelpaddressAI’sinherentvariabilitywhilemeetingstringentaccuracyandlatencyrequirements.Thiscombinationoffinancialexpertise,technologyand

humanvalidationismoredifficulttoreplicatethantheLLMoragentlayer.

AIexpandsDaloopafromdatacollectionintofinancialanalysis.Daloopacan

automatemodelupdatesacrosslargecompanyuniverses,reducingmanualdataentryandallowinganalyststomaintainbroadercoverage.Becausethecompanycapturesacomprehensivefinancialhistory,individualcustomerm