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Appian Delivers Better Business Decisions and Outcomes with AI Plus Data Fabric Analytics

Latest version of the Appian Platform enhances end-to-end automation and data-driven decisions powered by self-service analytics (SSA) and generative Private AI

Appian announced immediate availability of the latest version of the Appian Platform for AI process automation. The new release empowers business and IT leaders to streamline processes, enhance user experiences, and drive better business outcomes through data-driven decision-making. The platform update features a preview release of Appian’s self-service analytics (SSA) capabilities, which allow any user to effortlessly gain insights from Appian’s Data Fabric.

Appian’s Data Fabric blends data from multiple sources into a secure and unified data model without moving the data. Appian customers can now explore and analyze their data through SSA, leveraging the power of Appian AI Copilot. End users can harness data in a simple builder interface with features for aggregation, filtering, sorting, and formatting. Once a report is set up, users can leverage AI Copilot to get deeper AI-generated insights from the data. AI Copilot uses the power of generative AI to help users gain new insights from their reports, even suggesting next steps to address business needs based on report data.

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Additional new capabilities in the latest release of the Appian Platform include:

  • High-accuracy document extraction. Take data extraction to a new level of precision. Appian customers will soon be able to extract unstructured data from documents with accuracy. Train custom entity extraction models on your business’s own data using Private AI, delivering superior extraction accuracy for text entities.
  • Faster language translations for apps. This release introduces an out-of-the-box way to create high-fidelity translations compatible with all of Appian’s supported languages. Users can generate, organize, secure, and deploy translation strings with the new translation set design object, ensuring the best possible user experience in their preferred language.
  • Expanded UI controls. Appian customers now have a greater set of tools for configuring complex UI navigations, additional styling controls, and improved offline experiences for mobile users.
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When Leroy Merlin, the third largest home improvement retailer in the world, needed to manage a sudden increase in e-commerce, in-store orders, and refund and return requests, they turned to Appian. Leroy Merlin accelerated their refund and return process with the Appian Platform through intelligent automation and intelligent document processing (IDP) powered by AI. With Appian’s AI and automation capabilities, Leroy Merlin was able to take the refund and return process from 15 days to 1.5–2 days.

“Anything you would love to accomplish, you can accomplish ten times faster with Appian,” said Dmitriy Anderson, CIO & Head of E-commerce and Marketplace Strategy, Leroy Merlin.

Amadori, a leader in the Italian agriculture-food sector, uses Appian to simplify and modernize work in their supply chain. Using Appian’s automation and data fabric capabilities for fleet management, Amadori reduced lead time by 466% between maintenance and order generation. Now what once took two weeks takes about three days.

“We chose Appian as a strategic platform for cloud-based digital transformation because it allows us to be agile in how business and IT respond to the changing environment,” said Sandro Salvigni, IT & Digital Transformation Manager at Amadori.”

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“Every vendor promises not to train their AI models on your data but Appian Private AI also protects you from data leaks inside your company that can happen when using GenAI with internal documents and databases,” said Michael Beckley, CTO & Founder, Appian. “On its own, GenAI doesn’t understand or respect enterprise security rules and roles but with Appian’s new Data Fabric Analytics, data security is built-in. Now everyone can confidently use GenAI to create their own reports and analysis knowing their GenAI won’t leak sensitive data across employees and teams sharing the same AI models.”

[To share your insights with us, please write to sghosh@martechseries.com]

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