---
title: "Slides: Building an Agentic Platform — Ben Kus, CTO Box"
category: "slides"
video_id: "12v5S1n1eOY"
sourceLabels: ["Public YouTube video frames", "Public YouTube metadata"]
---

# Slides: Building an Agentic Platform — Ben Kus, CTO Box

## Source Video
[Building an Agentic Platform — Ben Kus, CTO Box](https://www.youtube.com/watch?v=12v5S1n1eOY)

## Relationship To World's Fair 2026
These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

## Related Scheduled Sessions
- No individual scheduled session mapping has been assigned yet; treat this as an event livestream deck.

## Extracted Slides
![[assets/slides/12v5S1n1eOY/slide-001.jpg]]

OCR text:

> INNOVATIONPARTNER
> aws
> PLATINUMSPONSORS
> Graphite
> WWindsurf
> MongoDB
> daily
> augment code
> Workos

![[assets/slides/12v5S1n1eOY/slide-002.jpg]]

OCR text:

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> fexororase REMY COINTREAU Ye neo Motus =
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![[assets/slides/12v5S1n1eOY/slide-003.jpg]]

OCR text:

> . ae é I Ph . yy 1.
> Industry-leading Ini: anagement platform
> Box as 1,500+ integrations Custom 2 geue
> Web : APIs&SDKs = ;
> 
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> B Al eta ST ov lt mAs Ne] Mode!- agnostic Perera m ole lol 1g
> . eH Files and fokders Collaboration E-signature average]
> Ce aL) I CIeTe RG) Workflow Analytcs No-code apps
> rae tecti Threat detection Ransomweare protection Classifications Pll scanning
> d. bebiaiaie sad ton Data residency Audit trails TLIO LSS Encryption
> Ure) compliance Centificaton Retention Neate
> oo A Unimited storage Data ingestion Ove RU Liat)
> and Global infrastructure High scalability High speed High availability

![[assets/slides/12v5S1n1eOY/slide-004.jpg]]

OCR text:

> Box has fully integrated generative Al starting in 2023
> Q&A across Data Al-powered
> documents extraction workflows
> 
> g How can we speed up our product roadmap? 172 Contracts Loan Approved: “eee
> 1 Above $5000 90 vein 90 Days
> Beemeiatentoris  ceutean oh tesbrdgse Neweeronvonses @
> ee sein Dy semana
> Smmrnoenn’ O

![[assets/slides/12v5S1n1eOY/slide-005.jpg]]

OCR text:

> Box has fully integrated generative AI starting in 2023
> Q&A across documents
> How can we speed up our product roadmap?
> Data extraction
> 172 Contracts
> 17 Above $5,000
> 90 Due in 90 Days
> 12 Risky clauses
> 53 Contain PII
> AI-powered workflows
> Loan Approved
> New client onboarded
> Insurance claim processed
> Compliance audit submitted
> AIE
> Microsoft
> smol ai

![[assets/slides/12v5S1n1eOY/slide-006.jpg]]

OCR text:

> Metadata is the important structured data contained in
> unstructured data
> ao
> peels ig
> Ths batual Mat-Dieciowure Agreemend (this “Agreement”! 1s made and enteeed into 3s of the date last executed by
> the Parties below ("Effective Oate’| by and betaees Bor. Inc and its athhiates (“Baw”) with oth es 2¢ 900 Jeter son
> Ave. Redwood City. CA 94063 sn QE Participant’) with oft cs at QE SERIES
> Bee any GRR erty the Partin individual a Party) Vitereas the Partaipant wishes tu explore a potential business
> opportursty to purchase or hcente services from Bar and In connection with the oppartunity each Party may
> Grctose to the othe+ cov 2: Qi rot ne ooscloung Pxty desires tne
> recorving Pacty 10 treat at contider tial Purpose’) The Parties han agreed to du 40 wtyect Lo the terns and
> CLASSIFICATION Cind tans as vet forth below
> ED ~ 5-1-0 ero ots
> by a Party Disclosing Pasty’: 10 the otter Party ( Receiving Party”) cer or after the Elective Date of Une
> Agreement that are lin Laag-bie form and Labeled “conPiential’ or the lite (61-4 div coved or ity are wunmarired
> BA CORA ened on ner tong 10 Dee CONG] a wsthen a fe atonudie bene from [he it ted Gat honure OF) Atormatica.
> that 2 reasonable person knows oF should hive known to be contdential piven the ce cumslances surroundeng
> Sixelowute The lollowiag formation shall be considered Cormidential ledor mation whether of nok muried oF
> rent fied as wich any per wonaity BentiBable informahon Wxh as the names of either Party's customers, steatoen
> mur heting plans 3nd product roadmaps, Source Code techie ab infrastructure secunty and complune
> Gocumentaton hardwsee COnfiguralion deicounte and the terms of this Agreemen! Confidertea! lntormateon shad
> at ime hate of Abt Cease Co mnt ludie at appt able inne matwin oe materials thet (a) were geareaty known to the:
> a me public on the Effective Dale (bi become generally bryan to the pubia after the EHtectoe Date other than as a
> ~a result of the act of omnson of Ihe Rece ving Panty. 1c] were reghttully known to the Recewving Party preor torts
> | ba receipt thareot from the Divckourg Party, d) are of were disc lated thy the Dru oveng Party gemerally without
> oa revtrertion on disc lovee. [0] the Recesving Party lawfully recereed trom a third party without tht {cd party's
> =
> -)

![[assets/slides/12v5S1n1eOY/slide-007.jpg]]

OCR text:

> Metadata extraction enables Al to understand
> and process enterprise content effectively
> Que wee e-- —— » eS
> 8 e Contract ate
> eee einen NON DISCLOSURE AGREEMENT 108 2 ene °
> cece wee vee Je
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> ae eee
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> |
> | :
> 1 ry
> ed ]
> aws

![[assets/slides/12v5S1n1eOY/slide-008.jpg]]

OCR text:

> Before GenAl, extracting data was
> too hard for most enterprises
> Ny
> ML-based Didn’t work well for Not responsive to
> techniques too free form text data data format changes
> expensive to develop
> a : 1
> | a Microsoft = rnal)®
> al

![[assets/slides/12v5S1n1eOY/slide-009.jpg]]

OCR text:

> Building generative Al data extraction
> aaiech GNA =IecStO1|
> Performed well
> ae
> - a nnn Flexible, based on reasoning
> ™ [ Cree iit wera We. Ges
> Paroe ty LLM ee
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> NN Sg . porn s
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> yeaa) ed Sete) Required ML-based pre-
> . aa processing for OCR
> ere zals
> mu Microsoft =U
> _
> an

![[assets/slides/12v5S1n1eOY/slide-010.jpg]]

OCR text:

> Building generative Al data extraction
> Challenges
> Started getting longer /
> more complex docs
> 5
> ae ae oe Eur
> ae * aay | aa ; lose valuable info
> aa ee a deren ee ee —*
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> ad : id iahiaale Spertt rore srd more t Te ta
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> sence iain
> rs
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> a | mE corto ES UOU

![[assets/slides/12v5S1n1eOY/slide-011.jpg]]

OCR text:

> Building generative Al data extraction
> Challenges
> feed Bal as Site Le ie
> Lp feids ints groups
> Ky
> Started getting longer /
> Needes a qua:ty ind cater morse complex docs
> oe Poo Teil ar RO Eka Meet od
> a P
> - Tre OCR would sometimes
> - r
> ae a LLM a Lert E UK| sl Manto)
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> x C7 :
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> jc MIDENSA Oats MAST ee ee eer
> eed as: ae : se determine that sometimes it
> : aaa be was wrong on its first pass
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> — a Microsoft
> . a ie

![[assets/slides/12v5S1n1eOY/slide-012.jpg]]

OCR text:

> Bringing agentic technology to the Boxplatform
> AIE Foundationmodel that powersreasoning. the Al Agent follows to completeits task Structuredpmpslogc,rn summarization,and generation Instructions Almodel boxAI summarization,classification.andAl APls Specific tasks the Al Agent is designed to accomplish Functions the Al Agentuses toact-—like Objectives Capabilities andtools
> Secureaccesstoyourcontent
> Content the Al Agent draws from,thisis the foundationof secure,groundedAl
> aws

![[assets/slides/12v5S1n1eOY/slide-013.jpg]]

OCR text:

> Al Agents driven by advanced agentic reasoning framework
> kL) ;
> al / comprehend ‘\
> cn Pe) ee a ee)
> and iterate execute
> eae ast aie lee aoe ae ed
> sdentts reqused foots, Jota Passe ratroctocs, constacte. 7 , ; , - .
> Oe Rene ea) fener rang sed Bieta rra) en - ne
> ped ata Bee eat eae Rea
> eee eeeeeacnennnne
> foekt st armed ete tora ted
> nat oer Ce ed
> a
> ; mV (ai)
> ae | a Microsoft §= SUDO
> . ,~ 3

![[assets/slides/12v5S1n1eOY/slide-014.jpg]]

OCR text:

> Improving Box Q&A - Agentic RAG
> Answer Critique
> question answer
> Question —(8} EEC —> Answer
> . . :
> As aia@edecig
> [o[reselelany
> -3%-
> .
> 5 A >i)
> - | a Microsoft §=GDCU
> = ys i

![[assets/slides/12v5S1n1eOY/slide-015.jpg]]

OCR text:

> Ich-scto] am ict- 1a aT cre
> Build agentic architecture early!
> Cleaner platform Ease to evolve Improved engineering
> abstraction quickly PN Ror celae
> Separation of high-scale Easily adapt as new Helps engineers think
> infra work vs. improving techniques and Al agentically (state diagrams,
> specific agent actions models become Tools, A2A, ...) as part of
> available overall ecosystem
> == = ,
> co? | nicki ES 0000 Oh
> 7 dl

![[assets/slides/12v5S1n1eOY/slide-016.jpg]]

OCR text:

> AIE
> Thank you!
> box

![[assets/slides/12v5S1n1eOY/slide-017.jpg]]

OCR text:

> Thank you!
> box
> World's Fair

![[assets/slides/12v5S1n1eOY/slide-018.jpg]]

OCR text:

> Thank you!
> box
> World's Fair

## Slide-Derived Subjects To Review
Subject extraction uses video title, related session titles/descriptions, transcript context, and OCR text when available. OCR is best-effort and should be reviewed against the embedded slide images.