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Custom ReportDeep AnalysisINNOVATIONINDEX2020

Research is core to our work, and in 2020 the Deep Analysis team took more than200 briefings; we talked with companies ranging from multi-billion-dollar megavendors to tiny start-ups, and we talked to enterprises to understand their needsand experiences. Every so often, in our vendor briefings, our client work, and ourdesk research, we had a “shut the front door!” moment where we saw somethinginnovative and exciting.And so, as we approach the end of this “memorable” year, we thought we wouldlook back and share some of those moments with you. This report features aneclectic bunch of companies that are not likely to be seen together in the samecontext again. Each does something different, something innovative that movesthe needle, something that has the potential to improve, educate, and stimulatethe information and process automation management industry as a whole. At thecore of their inclusion is their ability to reframe, rethink, and reinvent.Without further ado, let’s reveal who made it onto this year’s Deep AnalysisInnovation Index!Deep Analysis 2020 info@deep-analysis.netDeep Analysis Innovation Index 20202

Figure 1The 2020 Deep Analysis Innovation eRipcordWorkplaceProductivityOracleTrack wareHylandCredentials 2020 mentCaptureBlockchainDeep miDataInboxDocumentViewingGrooperDeep Analysis Innovation Index 20203

The VendorsABBYY TimelineAdobe Liquid ModeWhat it doesWhat it doesIn basic terms, Timeline extracts and readsLiquid Mode, and more broadly Adobe Sensei,the time stamps and details of any eventsstrikes a balance of maintaining a lockedthat occur throughout a business process. Itdocument’s integrity while simultaneouslythen visually models that data to reveal anyimproving the user’s experience. Via the API,irregularities. This system can be used todevelopers can move beyond concentrating onobserve, optimize, and remediate processes –traditional content services and focus insteadand process instances – in fight. Where thingson expanding and improving the experienceget particularly interesting is in Timeline’sof those working with the document itself.ability to run that information through machineTraditional capture/OCR solutions havelearning modules to predict and forecast futurenot been good at extracting complex data,outcomes. In other words, Timeline automatesand developers may use Sensei to supportthe analysis of the “as is” environment and canimproved content processing in downstreampredict an improved “to be” environment.applications such as contract lifecycleWhy we included ABBYY Timelinein the 2020 Innovation Indexmanagement (CLM) and enterprise resourceplanning (ERP).activities makes sense, as the insights,Why we included Adobe Liquid Mode in the2020 Innovation Indexpredictions, and improvements that can beTo date, the focus of document and contentgleaned from analyzing the associated datamanagement has been in securing/locking flesare invaluable. No matter how well designedand ensuring they are fled away and labeledand managed they are, business processescorrectly for later retrieval. Though the userare often unpredictable and can vary widelyinterface experience of document managementfrom the expected or planned process path.systems has improved notably, the end user’sThe use of AI in process automation is widelyexperience with the document itself has not.talked about yet rarely carried out, butSensei and Liquid Mode attempt to right thatABBYY Timeline is an early phase examplebalance. Liquid Mode is a small feature, but itthat highlights an efective use of AI in thewill have a big impact.Applying AI to complex business processautomation and process management worldtoday.You can read our ABBYY Timeline report /ABBYY-timeline-process-mining-analyst-report/Deep Analysis 2020 info@deep-analysis.netYou can read our Adobe Liquid Mode report /adobe-liquid-mode/Deep Analysis Innovation Index 20204

Alkymi Data InboxAmazon TextractWhat it doesWhat it doesAlkymi targets its Data Inbox ofering at useAmazon describes its machine learning (ML)cases within the fnancial services market,technology stack as a three-layer cake. At thespecifcally addressing the unstructured databottom is a layer for advanced practitionersburied inside the large, complex documentsto work with deep learning frameworks suchcommon within the industry. Data Inbox ofersas Tensorfow or Pytorch. The next layer is foran easy-to-use application that interceptsdevelopers to work with Amazon SageMakerdocuments arriving via email or its REST API,to build out managed ML capabilities. The topor those residing in a content repository, andlayer provides pre-built artifcial intelligenceutilizes AI powered by machine learning to(AI) services that can be used immediately viaconvert unstructured data into actionable andan API integration point. Textract is one of thesestructured business data.AI services ofered by AWS. In simple terms,Why we included Alkymi in the 2020Innovation IndexTextract provides data extraction from scanneddocuments. It does this by delivering ML-basedoptical character recognition (OCR) tools toAlkymi's approach attacks high-value complexread the document and accurately extract datadocuments. Rather than view the entireand text.document as a single entity containing aapproach, using computer vision, looksWhy we included Amazon Textract in the2020 Innovation Indexfor diferent complex structures such asTextract may be one small piece of a bigtext, tables, and charts and classifes themAmazon pie, but it is a pivotal piece and oneindividually. This allows a document to fall intothat has shaken the traditional documentmultiple classifcations, which in turn allowscapture market. Textract is a catalyst fordiferent views of the same information toinformation management buyers and vendorsbe rendered appropriately for diferent userto leverage AWS as a true platform ratherconstituencies. Alkymi has taken a measuredthan simply as a provider of cloud storage.approach by targeting a highly specialized useThough it’s labeled as OCR, even a cursory lookcase and refning Data Inbox using feedbackat Textract makes it clear that this is a fully-from customers and partners alike.fedged content extraction tool, one designedconsistent extractable structure, its uniqueto provide the data necessary for furtherYou can read our Alkymi report here: i/automation.You can read our Amazon Textract report here: on-awstextract-analyst-report/Deep Analysis 2020 info@deep-analysis.netDeep Analysis Innovation Index 20205

AttestivBurstIQWhat it doesWhat it doesIn principle, what Attestiv provides is anBurstIQ is a data exchange network thatapplication and platform to capture andleverages blockchain technology to buildvalidate images and videos in insurancesecure data solutions, creating identity proflesworkfows. It does this by recording fles at theby using big data. The profles are then usedpoint of capture on a blockchain; for example,in applications, which for BurstIQ primarilyphotographs of an asset (such as a vehicle) atfocus on the healthcare sector, though thethe time it is insured or at the time of damagetechnology is still generally applicable to otherand a related claim. Though simple in concept,data and industries. BurstIQ’s goal is to build athe provision of a mobile app for adjustersglobal network for specifc and true ownershipto capture and lock digital media is new inof data, exchange the data at scale, and fndthe industry.deep connections within the data. Its secretWhy we included Attestiv in the 2020Innovation Indexsauce is to store virtually all data (except forimages) on-chain rather than on- and of-chaincombined and to use proprietary machineBlockchain has the potential to underpin manylearning algorithms and techniques to createbusiness applications in the future, but asindividual identity profles from among theof today there are few practical applicationsdisparate blockchain data.on the market, even though the underlyingand ofers many variations and options. AttestivWhy we included BurstIQ in the 2020Innovation Indexin this regard is ahead of the curve, but moreMachine learning and big data analytics areimportantly the company has focused in onnot typically thought of in conjunction witha specifc industry vertical rather than takingsecure enterprise blockchains. In fact, at frstthe path of many start-ups that try to “boil theblush these appear somewhat in confict asocean.” Attestiv is a small and focused product,machine learning mines sensitive data at scalebut it has the potential to make a big impact inwhile healthcare blockchains provide securitythe insurance sector.and decentralization. It is worth noting that weblockchain global infrastructure is immensedon’t see the big boys as having capabilitiesYou can read our Attestiv report here: stiv-insuranceblockchain-analyst-report/like BurstIQ’s at this time. The bottom line hereis that there should be no shortage of earlyadopters and frms with relevant innovativebusiness models able to build on a BurstIQPaaS to extend standard enterprise blockchainsecurity and data analytics capabilities.You can read our BurstIQ report here: tiq/Deep Analysis 2020 info@deep-analysis.netDeep Analysis Innovation Index 20206

CollabwareGrooperWhat it doesWhat it doesMost record management (RM) productsGrooper describes itself as a data science andon the market only concern themselves withdata integration platform that comes withcategorizing and applying retention schedulespre-installed machine learning capabilities. Atto content. But Collabware’s Collabspace goesfrst glance that would seem to put Groopermuch further by applying a data lake approachin competition with the likes of Boomi,to provide full content management and searchInformatica, and MuleSoft. But a second lookfunctionality wherever the content resides. Inat the Grooper ofering reveals something quitesimpler terms, all of the data (information) indiferent. For where traditional data integrationthe data lake is analyzed and processed via theplatforms focus on structured data, Grooper’smachine learning capabilities. New values areapproach is to recognize, capture, and analyzeextracted from that content and, once added,both structured and unstructured data inare also stored in the data lake. This provides adocuments and forms. That is ambitious forrich body of active and automatically updateda small company, and positions it, in theorycontent to mine. Overall, Collabspace providesat least, into some of the most complexa holistic RM system with the added value of adata collection and integration challengesbuilt-in archive, backup, and recovery system.imaginable.Why we included Collabwarein the 2020 Innovation IndexWhy we included Grooperin the 2020 Innovation IndexInnovation comes in many diferent forms.Grooper represents one of the moreWhat Collabware brings to the table is aremarkable corporate and technology pivotssensible and practical method for managingwe have seen. A company that was well knowncontent both in place and by leveraging aand long established in the capture/scanningdata lake approach. However, the companymarket reinvents itself as a data integrationtoday has little visibility in the market, andplatform vendor. What it has done so far – andits ambitious plan to rethink governance andit has taken seven years of development workRM fies beneath the radar. Without a doubt,– it has done well. The vision and recognitionthough, this novel approach to enterpriseof the need for a system such as Groopercontent management has broad applicabilitythat embraces rather than tries to ignore thebeyond the current target markets thattricky topic of unstructured information is wellCollabware has focused on.founded.You can read our Collabware report here: abware-analystreport/Deep Analysis 2020 info@deep-analysis.netYou can read our Grooper report here: per-aiclassifcation-analyst-report/Deep Analysis Innovation Index 20207