I’m in San Deigo for a quick visit to the ABBYY Technology Summit. I’m not speaking this year (I keynoted last year), but wanted to take a look at some of the advances that they’re making in intelligent capture. We had an analyst briefing today in advance of the general conference tomorrow, and some of this is a preview for those more detailed sessions.
ABBYY’s legacy is in the OCR SDK business, which allows their partners to build solutions that include intelligent data capture from scanned documents. They’re moving beyond that with mobile capture products and cloud capture solutions. They have a lot of flexibility with mobile and cloud, allowing for both hybrid solutions that use mobile for capture with recognition on a more powerful cloud platform, and for mobile-only data extraction that operates completely on the mobile platform. Since there are components for this in addition to packaged solutions, a developer can create a mobile application that makes decisions about what type of recognition to do, and where to do it. This uses a real-time recognition SDK that uses video feed to do self-correction based on several frames of video rather than just a single snap, or simpler recognition based on still photos.
Their cloud OCR service supports a community of more than 65,000 developers with 69,000 connected applications: a great use of distributed microservices from applications that need OCR but don’t want to own that technology. Assuming that privacy issues can be satisfied (since you’re sending them potentially private documents), many organizations could benefit from OCR but may not be able to afford to own a high-performance solution in-house.
They also have some packaged solutions for receipt capture and identity documents (e.g., passports). They also have a Linux version of their OCR services (their primary products are Windows and Azure-based), which is popular in certain markets.
They covered some of the market trends in capture:
- Less of a discrete technology and more of an embedded capability in business applications
- No longer production-line capture, but more intelligent capture of heterogeneous documents; there’s a great deal more diversity in document type and point of origin
- Organizations are using this to automate where possible, particularly for front-end work such as capture
This requires core capabilities of processing large volumes of documents where the content may be diverse and frequently changing, and the seamless interaction of content coming from a variety of input streams with a larger business solution. Back in the earlier days of “imaging and workflow”, we had dedicated scanning and recognition workstations for high-volume assembly line processing of documents that were all the same, or manually classified. Now, we need to have this happening on any computer, or on a mobile device, at any point in a process.
ABBYY’s products are aiming to address these changing market conditions with autonomous classification and train-by-example data extraction, including some clever processing of related documents: if you have two documents from someone with the same piece of information (e.g, a SSN), and the confidence level is low on the recognition of that information on one of the documents but high on the other, the stronger confidence level can be used to boost the confidence of the lower level. They also have improved integration capabilities including being able to embed the capture capabilities as an iframe in an html page. and an increased number of input channel types. They’re working with some of the low-code vendors since it’s now pretty straightforward to map the outputs from an ABBYY service to the inputs of a data-centric low-code application.
Their core customer base is still banking — at least in North America — but they are starting to see growth in insurance and other markets. Their number one use case is invoice processing, and they have a packaged application to address that sector. The mid market is underserved in terms of automating invoice processing; it’s a tough problem since inbound invoices can be in any sort of format, and there’s quite a bit of intelligence to ensure that all of the data is extracted correctly. Note that a lot of larger enterprises either have EDI-type processes for invoices, or force smaller vendors to login to a dedicated invoicing portal to submit an invoice in the enterprise’s format rather than the vendor’s usual format, and are more likely to have automated capture processes for the remainder. ABBYY’s goal is to complement existing accounts payable solutions by being built in as the front-end capture component, not to displace these systems.
This briefing drives home that ABBYY is the best-kept secret in intelligent capture because they work primarily through partners who bundle their capture technology into vertical solutions, but don’t have as much visibility to the end customers. Most of the enterprise customers that I talk to have never heard of ABBYY, although they may have it running in their organizations embedded within another application. Even other vendors in this space, such as BPM and low-code vendors, don’t know the name. This is a bit different from ABBYY’s competitors Kofax and Captiva, who both have had a lot of end-customer solutions that move beyond capture in addition to capture-related SDKs, or IBM’s Datacap, which does some of that but also comes in on the coattails of a suite of IBM products such as ECM and BPM. Whether ABBYY can change this market visibility themselves — or if they even want to — will be an interesting positioning going forward.
More on all of this tomorrow and Friday.