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Generative AI Use Case

Intelligent Document Processing

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Overview

What is IDP?

Are you processing large amounts of documents and need them quickly analyzed while maintaining accuracy? Intelligent document processing (IDP) works with document data using machine learning techniques, AWS Services like Textract and Comprehend, data analytics, and large language models to help with tasks which might otherwise require human readers or writers.

Am I a fit for Generative AI?

Common Verticals

Solution Fit Criteria

You should consider adopting an AI-powered IDP process if:
  • You’re working with large volumes of documents (paper or digital)
  • Handling your document data requires reading comprehension and impacts a business objective
  • Data is sensitive or subject to compliance requirements
  • Data needs subject matter expertise
  • Your current process needs a written output (i.e., summary, key text extraction, comparison with other text(s))
  • Your current process is human-driven, manual, or at low levels of automation (Excel-driven)
  • Your current process is costly
  • The throughput of your current process is too slow for your objectives
  • Your current process requires external contracting / offshoring or other factors of additional cost

Benefits of Intelligent Document Processing with Generative AI

  • No Manual Sorting

    Removes the manual labor of document processing

  • Improved Accuracy

    Tunable to exceed human readers’ accuracy / consistency

  • Scales Efficiently

    A larger throughput of documents takes more compute, not more labor

  • Greater Privacy

    Less human intervention with sensitive data / greater data privacy

Our process

Gen AI Use Case flow_IDP 2.0
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Get Your Pilot Launched

Over a 4 to 6 week period, we’ll construct an engagement to get you up and running  with IDP. By the end, you’ll have a pilot solution deployed in your environment that’s been designed to accomplish your objectives and demonstrate the potential of a fully scaled architecture.

Design Workshop
(1-2 weeks)

Pilot Deployment
(3-4 weeks)

At the end of the design phase, you get:

  • Data and infrastructure design
  • Use case prioritization and roadmap
  • Defined business use case
  • Defined success criteria
  • A proposed candidate solution for the minimum viable product
  • A high-level solution architecture using AWS services 3rd party software (foundation models)
  • A development plan for the Pilot Deployment
  • Preliminary TCO estimates

At the end of our Pilot phase, you get:

  • A pilot deployed in your AWS development environment
  • The solution architecture documentation
  • A plan to build for scale as a production-ready solution
  • A refined TCO estimate for AWS and 3rd party services
  • A summary of success criteria met and recommendations for “go/no-go”

Get Your Pilot Launched with Mission