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    DocAIQ – Intelligent Document Processing Powered by Agentic AI

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    Sold by: Apexon 
    DocAIQ is an AWS-powered Intelligent Document Processing solution that ingests, interprets, and structures complex documents using Amazon Textract, Amazon Bedrock, and Amazon Comprehend. It combines hybrid extraction (template-based + LLM-based), human-in-the-loop validation, and a low-code configuration layer to automate document workflows at scale with high accuracy and control. Built on AWS services including Amazon S3, AWS ECS, AWS SNS, and Amazon Aurora, DocAIQ delivers secure storage, near real-time processing, and enterprise-grade monitoring, helping BFSI, healthcare, legal, and manufacturing teams reduce manual effort and accelerate end-to-end digitization.

    Overview

    DocAIQ is Apexon’s next-generation Intelligent Document Processing (IDP) platform, purpose-built on AWS with a microservices architecture. It combines Amazon Textract for OCR and structured extraction, Amazon Bedrock for LLM-driven reasoning, and Amazon Comprehend for entity detection and classification to process both structured and unstructured documents. With agentic AI, DocAIQ adapts to new document types, formats, and business rules with minimal rework.

    Documents are ingested via Amazon S3, orchestrated through AWS ECS, and stored and indexed in Amazon Aurora to enable fast retrieval and RAG-based semantic search. A low-code UI lets business users configure prompts, rules, and extraction templates without heavy engineering effort, accelerating rollout across teams.

    With human-in-the-loop validation, CI/CD using AWS DevOps tooling, and API-first integration via Amazon API Gateway, SNS/SQS, and downstream data lakes, DocAIQ delivers end-to-end traceability, governance, and compliance. The result is faster time-to-value, higher extraction accuracy, and scalable automation for BFSI, healthcare, legal, and manufacturing workflows.

    Highlights

    • Agentic AI on AWS adapts to new document types and workflows, using Amazon Textract, Amazon Bedrock, and Amazon Comprehend for extraction, classification, validation, and correction. Built-in human-in-the-loop feedback continuously improves accuracy and control.
    • Agentic RAG with short- and long-term memory on AWS enables fast, context-aware retrieval using Amazon Aurora and Amazon Bedrock. Enterprise-ready by design with RBAC and governance enforced through AWS-native security controls.
    • Comprehensive agent workflow debugging with server event captures, delivering end-to-end traceability and observability of agent actions and behaviors to strengthen governance and compliance.

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