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    IBM Consulting Agentic Application – DocuFlow-AI

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    IBM Consulting's DocuFlow-AI transforms document heavy workflows with agentic AI—enabling business users to define extraction, validation, and actions in natural language for higher accuracy, faster processing, and lower cost across industries.

    Overview

    IBM Consulting and AWS help enterprises reinvent document processing with DocuFlow-AI, an enterprise-ready agentic AI solution for end-to-end document workflows. Business SMEs can configure what to extract, how to validate it, and which actions to take, using plain language, without rigid templates or code. The result: rapid time-to-value, higher straight-through processing, and fewer manual corrections.

    DocuFlow-AI supports complex use cases (invoices, contracts, claims, statements, onboarding forms and more) and scales as an app UI or a pipeline powering other business applications. Agents can trigger simple to sophisticated actions via tool connections (MCP), and teams can “chat with data” at both the document and repository level to analyze results and drive decisions.

    Under the hood, DocuFlow-AI combines advanced orchestration, code assisted generation, and human-in-the-loop reinforcement to drive accuracy and trust. Capabilities include arithmetic, reference based, and NLP validations; improved confidence scoring; and RLHF-based tuning, designed to lift accuracy over time.

    Organizations use DocuFlow-AI to reduce manual processing, accelerate cycle times, and mitigate revenue leakage through accurate auditing, addressing the pervasive reality that most enterprise data lives in documents and current tools often require heavy template work.

    What you get: Clients engaging with DocuFlow-AI receive a focused consulting and prototyping experience designed to: Assess current document workflows and identify high value use cases for agentic automation. Rapidly calibrate extraction/validation/action flows using sample documents, with guided verification and optional tuning. Configure actions and integrations (e.g., notifications, system-of-record checks) and demonstrate “chat with data” for both document-level and repository-level insights. Define a path to MVP and scale with recommended architecture, governance, and delivery approach.

    Highlights

    • Business Highlights 1. Faster Processing, Lower Cost: Up to 70% cost savings and 4× faster processing; >40% reduction in processing cost/time. 2. Higher Accuracy & Straight-Through Processing: Up to 100% extraction accuracy & >90% straight-through processing. 3. Revenue Protection: Accurate AI-enabled auditing reduces leakage and accelerates downstream processes. 4. Empowered Users – Self-serve, no-code configuration removes template rigidity & reduces reliance on scarce technical resources.
    • Technical Highlights 1. Business users define extraction, validations in plain English; “Chat with Data” for analysis and QA 2. Simple to complex actions enabled by agents and connected tools w/ Integration & Extensibility w/ connect to downstream apps 4. Reference-based and NLP validations; key-value, table, and image extraction 5. Code-Assisted Generation for precise transformations/calculations and Enhanced confidence estimates & reinforcement learning to improve accuracy.

    Details

    Delivery method

    Deployed on AWS

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