Sold by: MphasisÂ
Deployed on AWS
The solution extracts the metadata and formatting related information from digital documents.
Overview
Digital content in different file formats like pdfs, docs, ppts, emails have a lot of metadata as well as formatting data associated with them. This solution parses documents, extracts metadata and formatting information from documents and standardizes them. It provides information about the document whether it is password protected, encrypted etc. along with the formatting information like Highlights, List, Section and Sub-Section etc. at sentence level. These details help in augmenting NLP algorithms with added information for decision making.
Highlights
- Automated Metadata extraction from documents reduces manual effort and improves the data extractions modules by filtering and processing data on the basis of metadata.
- This solution helps in parsing the documents, analyzing the documents at sentence and paragraph level, captures vital information at document and sentence level. This solution standardizes input file content so that ingestion in subsequent pipelines/algorithms is uniform across different file formats.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need Customized Deep learning and Machine Learning Solutions? Get in Touch!
Details
Sold by
Delivery method
Latest version
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $20.00 |
ml.t2.large Inference (Real-Time) Recommended | Model inference on the ml.t2.large instance type, real-time mode | $10.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $20.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $20.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $20.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $20.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $20.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $20.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $20.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $20.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
This is the second version of this application.
Additional details
Inputs
- Summary
Usage Methodology for the algorithm:
- The input must be pdf file.
- The input file should be a digital pdf. This model does not work on scanned pdf.
- Check the instructions and sample endpoint in the sample jupyter file provided.
- Limitations for input type
- The size of the input file should not be greater than 10mb
- Input MIME type
- application/pdf
https://github.com/Mphasis-ML-Marketplace/Metadata-Extraction-from-Documents/blob/main/Input/sample.pdf
https://github.com/Mphasis-ML-Marketplace/Metadata-Extraction-from-Documents/blob/main/Input/sample.pdf
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out at:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
Aktus AI Platform is a comprehensive, enterprise-grade multimodal Retrieval-Augmented Generation (RAG) system that transforms how organizations process, understand, and extract value from their document repositories. Our platform handles text, images, and other data formats through a unified intelligence layer, enabling seamless document ingestion, intelligent search, and contextual insights extraction.
QDox is Quantiphi’s document processing platform - powered by AWS.
With QDox, enterprises can create custom document processing workflows to extract key information from a variety of documents and utilize the data as required.
The QDox Developer Tool Suite, human-in-the-loop architecture, and pre-built components reduce development time by 70% without compromising accuracy.
Turn documents into actionable insights — effortlessly. Cloudtech’s AI-driven document processing turns unstructured data into searchable, structured insights — fast.
OpenText™ Knowledge Discovery for AWS brings the expansive ingestion, data enrichment and analytics capabilities of IDOL to AWS. Allowing users to ingest more than 1900 document types and 160 different repositories while extracting all the data within, powering Enterprise Search and File Analysis.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.