Sold by: Mphasis
Deployed on AWS
A deep learning based solution that extracts insights in response to the factoid questions with respect to the context passage.
Overview
Text Comprehend is a Natural Language Understanding solution that help users comprehend a passage of text. This is a state-of-the-art context aware, factoid model with bi-directional attention for comprehension. A deep contextualized embedding is used for distributed word representation. The output of the model will be a sub-string of words of variable length from the context passage.
Highlights
- A deep learning based model with attention which extracts insights to factoid inputs with respect to the context passage. Contextual embeddings are used for the distributed representation of the passage. The input context passage can have a maximum length of 1024 words.
- Text Comprehend can be used in document search engines to improve search, in factoid text based systems, and in building chatbots etc.
- 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
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Delivery method
Latest version
Deployed on AWS
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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.c5.large Inference (Real-Time) Recommended | Model inference on the ml.c5.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
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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
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
• The input has to be a '.zip' file named as “Input.zip” which contains two text files : 1. passage.txt – contains passage whose length should be between 100 and 1024 words. 2. question.txt – contains question whose length should be of minmum 3 words • The text files should follow ‘utf-8’ encoding.
- Input MIME type
- application/zip, text/csv
https://github.com/Mphasis-ML-Marketplace/DeepInsights-Text-Comprehend/tree/main/input
https://github.com/Mphasis-ML-Marketplace/DeepInsights-Text-Comprehend/tree/main/input
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
passage.txt | This data contains passage whose length should be between 100 and 1024 words. | Type: FreeText | Yes |
question.txt | This data contains question whose length should be of minmum 3 words | Type: FreeText | Yes |
Resources
Vendor resources
Support
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Customer reviews
0 ratings
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1 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Computer Software
An AI-Powered Tool : Analyzer, Enhanced and Decisive details from unstructured text
Reviewed on Apr 16, 2025
Review provided by G2
What do you like best about the product?
The best thing about DeepInsights Text Comprehend is its ability to quickly extract meaningfull information accurately.
Upsides of using it are:
Time Efficiency,
Actionable Insights,
Scalability,
Multilingual Support,
Improved Accuracy,
Integration Friendly
Upsides of using it are:
Time Efficiency,
Actionable Insights,
Scalability,
Multilingual Support,
Improved Accuracy,
Integration Friendly
What do you dislike about the product?
I have experience the least helpful aspect of DeepInsights Text Comprehend is that it may sometimes misinterpret nuanced languages, sarcasm, sentiments, industry-specific terminology, leading to less accurate results in complex or highly specialized content.
The downsides of using it are:
Customization Limits,
Costs are not as effecient as it should be becuase I found it bit expensive for processing large volumes of text,
Privacy are concerns for sensitive data
The downsides of using it are:
Customization Limits,
Costs are not as effecient as it should be becuase I found it bit expensive for processing large volumes of text,
Privacy are concerns for sensitive data
What problems is the product solving and how is that benefiting you?
DeepInsights Text Comprehend helped me to solve quite a lot of problems especially by extracting key entities, sentiments, and topics from extensive text data, it streamlines information processing, aiding in quicker decision-making. It also enhanced the search capabilities and chatbot development that facilitates the creation of more intelligent chatbots by enabling them to understand and process user inputs more efficiently.
These functions are particularly beneficial for customer service, legal and healthcare industries, as I have quite a good experience in working in all these industries.
These functions are particularly beneficial for customer service, legal and healthcare industries, as I have quite a good experience in working in all these industries.