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Codeless and low-code compositions

The aforementioned means of connecting sources for content services are integral for composing applications with what’s now the classic low-code or no-code methodology. Contemporary content services platforms utilize this approach to allow end users to hasten the process of building workflows or applications. Some of these techniques involve templates for frequently occurring use cases. “Solutions templates could be for anything from HR to IT help desks,” Ding said. “But, in addition to those horizontal solutions, there are vertical solutions for certain industries, too.” Other such “solution suites” are predicated on specific data sources routinely incorporated into content services. “A very common use pattern is to connect SAP , Salesforce, and the Microsoft suite, particularly Teams,” Bates said.

In addition to incorporating information from these sources to compose processes or workflows, users get the added benefit of creating applications such as 360-degree views across data sources. Such perceptivity is critical for monetizing content services while enabling horizontal visibility across departments. “If the legal department's negotiating with a customer and is trying to be too hard on them because they think it’s a small deal and actually there’s a massive deal in the pipeline, that might be important,” Bates said. “There’ s tremendous untapped revenue in what you might consider to be dark data.”

The ease of integration that’s foundational to composability supports low-code or no-code application building by automating measures that redress differences in data models and semantics. Certain methods for mapping this information between sources include what Rapelje termed “tokens,” which are used with workflow engines to orchestrate resources. “All the data that’s coming in can be harmonized into a token that can be plugged in for outgoing data, or applied to a form for showing as metadata on a document,” Rapelje said.

Composable AI

Because of its immense utility in enabling organizations to create structure from unstructured content, various AI modules are frequently incorporated into composable content services. Often, they categorize, extract, and input information into downstream workflows. “Advancements in natural language processing, used to unlock meaning in unstructured documents, and computer vision, used to unlock value in images and videos, have drastically increased the level of accuracy,” Adams observed. These capabilities produce two additional benefits for workflows. They increase the speed of these processes (such as IDP, for example), which also increases their scale. “If you rely on a human to read the documents and input the metadata manually, you’re very limited in the throughput of the number of documents you can process,” Donze said.

However, with composable AI, organizations can use any AI application they want—instead of those of a specific vendor. “No one can compete with the likes of Google, Amazon, and Microsoft on AI,” Bates acknowledged. With composable AI, content services providers don’t have to. End users can readily switch offerings from any providers. AI services become just another pluggable module that can be used to compose tailored applications, workflows, and processes. These might pertain to decoding emails and extracting requisite PDFs for paying invoices or going over contracts. “That’ s the ideal scenario for AI and that’s why it’s complementary for content services,” Donze said. “Content services takes care of all of the processes, the different steps, the routing between the human and the automated worlds, and the AI makes it possible for the system to process the documents automatically without humans having to read them page by page.”

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