Tray.ai, the first AI-ready, multi-experience integration and automation platform, announced major advancements to its Universal Automation Cloud that equip enterprises to maximize the value of unstructured data and solve the scalability challenges found in AI projects. Native Tray.ai Vector Tables now transform unstructured data into actionable intelligence by simplifying the processing and management of the data vital for chatbots, AI assistants, agents, RAG and other AI applications. Merlin Intelligent Document Processing (IDP), quickly and cost-effectively applies AI to turn complex business documents and processes such as resumes and invoices into valuable, structured data assets. New Inline Functions provide code-free processing flexibility for complex data transformations, while GenAI-generated workflow summaries provide real-time documentation so data teams can maximize the value of their AI integrations through efficient control and collaboration, essential for integrations typical with AI projects. Together, these new features provide enterprises with one unified platform to derive value from and manage every data integration need — ranging from traditional to unstructured data synchronization and data management for agentic flows so teams can eliminate delivery tooling proliferation and accelerate time to value.
Legacy tools block enterprises from realizing AI’s full value
Enterprise data integration has hit a breaking point. Teams already face a backlog of requirements stretching from standard data extraction and app synchronization to, now, new unstructured data demands for AI projects. Legacy tools built decades ago for traditional structured data integration were never designed for these needs and are often cumbersome to work with amid a flurry of AI-related demands, forcing organizations to patch together point solutions or write custom code that further slows AI projects and adds both cost and risk.
There is an opportunity to unlock value from unstructured data like emails, audio recordings, images, web pages and intelligent document processing that extracts data from invoices and orders to address IT’s constant flow of new AI-related integration demands requiring high-velocity delivery. Over 75% of organizations state that AI-ready data remains one of their top five investment areas in the next two to three years, according to Gartner’s 2024 Evolution of Data Management as a Dedicated Function Survey.
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“Successful AI projects are often going to rely on unstructured data. Yet companies keep using outdated tools built for structured data,” said Rich Waldron, co-founder and CEO of Tray.ai. “Legacy tools and custom code slow AI innovation. Modern enterprises need a new approach to data integration that captures the full potential of unstructured content — from documents and emails to images and audio.
The future of AI depends on transforming how businesses handle the growing complexity of unstructured data.”
AI-Optimized Platform Transforms Enterprise Data Integration
Building AI agents and infusing AI into the business requires a managed, maintainable and governed data integration layer with strong controls. The Tray Universal Automation Cloud, powered by Merlin AI, is the industry’s first multi-experience iPaaS built to handle modern integration demands. Underpinned by its Enterprise Core, the platform delivers the security, governance and scalability organizations need to deploy AI with confidence and at scale. With Tray, developers and business teams can easily collaborate on data integration projects — from traditional operational data to AI embeddings and unstructured content. This unified approach, backed by low-code tools and AI assistance, accelerates AI adoption across enterprises while maintaining control over growing data complexity.
The platform delivers five new advancements to address mounting data integration challenges faced by enterprise teams:
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Unified Data Integration for both Non-AI and AI-related Workloads: New built-in Vector Tables complement traditional Lookup Tables so teams can now handle unstructured data for AI embeddings and metadata as high-dimension vectors to drive RAG pipelines, Agents or AI-infused processes. With Tray, marketing teams can use Vector Tables within Tray workflows to analyze customer feedback to refine campaigns; for HR, teams can build knowledge experiences that organize and retrieve unstructured data from training materials, FAQs and policy documents, making it easy for new hires to access relevant information quickly; and in the service desk Vector Tables can be used to enhance support by analyzing and retrieving information from unstructured data sources like past support tickets, knowledge base articles and system logs. Now teams can eliminate weeks off project timelines by using native vector tables and database storage to both speed development and reduce infrastructure complexity.
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Flexible Inline Data Transformation Control and Processing: Being AI ready for data means ensuring your team can meet the inevitable increase in data transformation complexity while maintaining strong cost control flexibility to meet processing demands. Unlike many iPaaS vendors that force users to build scripts in order to achieve control, new Inline Functions provide flexibility to create any number of multi-step data transformations to Tray workflows, all in a single efficient processing step, using business-friendly functions. It provides powerful data transformation processing efficiency and control without requiring scripts and code.
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GenAI-powered Workflow Documentation: Until now, for most enterprises, traditional data pipelines have been relatively static. AI-data demands have changed that with a proliferating data pipeline that requires integration teams to stay on top of rapidly changing requirements. New Gen-AI auto-documentation ensures teams can build at maximum velocity without sacrificing maintainability or understandability, providing clear real-time narratives on every integration. This keeps teams coordinated, enhances cross-team collaboration and assists new users to quickly grasp how an integration workflow functions.
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Intelligent Document Processing: AI opens new opportunities to automate processes, but only if unstructured data can be integrated. Built-in Intelligent Document Processing, Merlin IDP, uses advanced AI to recognize document types, locate critical fields and convert unstructured content into usable data — all through an intuitive interface. Teams can automatically extract everything from payment terms on invoices to contract delivery dates, validating the information in real-time. Organizations can quickly automate document-heavy processes and directly feed extracted data into AI and business workflows without separate processing tools.
“These advancements in the Tray Universal Automation Cloud signal a complete rethinking of data integration,” added Waldron. “By bringing a vector database and intelligent document processing into one platform, we’re giving teams everything they need to build AI-powered workflows without the complexity of managing multiple tools. This is about putting organizations in an ideal position to move faster and focus on outcomes, not infrastructure.”
SOURCE: Tray.ai