Sold by: Dynamic AIÂ
Deployed on AWS
Free Trial
Detection of similarity of texts using mixed AI and statistical models
Overview
This model is designed for automation of business communication. Technical walk-through video describing how to use the model: https://youtu.be/rDdC0ekIBd4Â
It can serve as basis for classification, automatic responses and other uses. For example see the demo implementation for CRM in Customer Care: https://youtu.be/8f5-SpRfEcc Other demos are available on our website https://dynamic-ai.comÂ
We used our own dataset as the test set to evaluate the accuracy of the proposed method. Test report and confusion matrix: https://docs.google.com/spreadsheets/d/1sBrIUqytH3kMD1eJgmJKIE2Nu50gVRTN1MvZ0_80XxI/edit#gid=399507084Â Our system achieved an average accuracy of 95% on corpus of 232 messages.
Highlights
- Model is learning in real-time from every piece of input data and provides simple and easy to use interface for text categorization and similarity assessment. Number of messages it can consume is unlimited but message size is limited to 1000 characters.
- Powered by our Patented Genetic Coding engine with Evolutionary Core which is capable of assessing similarity between text data with argumentation of accuracy minimizing false positives.
- For ml.m5.4xlarge instance importing of 100-message categorized corpus takes 1hr. Prediction for a single message takes 3 to 30 seconds.
Details
Sold by
Categories
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
Free trial
Try this product free for 60 days according to the free trial terms set by the vendor.
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.m5.4xlarge Inference (Batch) Recommended | Model inference on the ml.m5.4xlarge instance type, batch mode | $1.00 |
ml.m5.4xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.4xlarge instance type, real-time mode | $1.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $1.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $1.00 |
ml.c5.4xlarge Inference (Batch) | Model inference on the ml.c5.4xlarge instance type, batch mode | $1.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $1.00 |
ml.m4.4xlarge Inference (Real-Time) | Model inference on the ml.m4.4xlarge instance type, real-time mode | $1.00 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $1.00 |
ml.c5.4xlarge Inference (Real-Time) | Model inference on the ml.c5.4xlarge instance type, real-time mode | $1.00 |
ml.m4.2xlarge Inference (Real-Time) | Model inference on the ml.m4.2xlarge instance type, real-time mode | $1.00 |
Vendor refund policy
Not available.
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 bleeding-edge technology release and is highly experimental. It contains alpha-grade Genetic Core so accuracy and performance may differ from the Production version. There is no possibility to import or export the current state of the model.
Additional details
Inputs
- Summary
This model is expected to be run as real-time inference only and does not support batch transform. Unlike classical ML model, this product supports both making inference and training on the same deployed endpoint.
For detailed usage information please consult:
- Limitations for input type
- To achieve optimal performance the following limits should be met: - Each message should be up to 100 words and 1000 characters long. - Total number of messages in the system should not exceed 10 000.
- Input MIME type
- application/json
This is not a conventional ML model and uses custom interaction protocol built on top of JSON messages.
Please use a Python helper library provided to feed data in and get results.
https://github.com/Dynamic-AI/aws-sagemaker-examples/blob/master/src/v1/rent-a-car-corpus-small.txt
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
type | Input command for the model.
Available actions are implemented as functions of the Python helper library. | Type: Categorical
Allowed values: addMessage, addFeedback, getSimilarity, isReady, reset, restoreCheckpoint, saveCheckpoint | Yes |
Support
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
An AI-powered solution that automates regulatory compliance by analysing new mandates and their impact on existing contractual documents, enabling organizations to maintain compliance efficiently while reducing manual effort by 60% and improving accuracy by 80%.
XTDB is a SQL database designed to simplify development, reporting and compliance for immutable systems. Featuring: comprehensive auditability with SQL:2011, a modern SQL dialect with PostgreSQL wire-compatibility, support for schema-free document handling, and a cloud native architecture. XTDB offers read-scalable ACID transactions on top of Apache Arrow and S3.
Address your browser automation needs with this Docker-based Grid Server for remote Selenium tests. It queues incoming requests and distributes them to containers automatically. Automate Chrome, Firefox, and Edge concurrently.
Easily connect to Dynamics 365 from AWS Glue
Easily connect to Dynamics CRM from AWS Glue
StrongDM is a protocol aware proxy that manages and audits access to databases, servers, clusters, and web apps. StrongDM customers enjoy easy and secure infrastructure access regardless of tech stack or environment.
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.