Solution leverages AI and ML to provide accurate, real-time insights for underwriting, marketing and claims. Solution extracts property attributes from high-resolution aerial imagery and combines with additional property-level features that influence risk. With these insights, insurers can better evaluate develop risk models, and combine individual peril scores into an overall risk score. For underwriters, the solution offers risk scores for fire, weather and flood. For claims processing, it provides a severity score, helps with triaging and reserve setting, and supports assessment of replacement value. The solution can also help carriers increase marketing ROI.Pricing Information: Pricing is indicative.
Highlights
End-to-End Solution: Support a variety of use cases across your enterprise with a single solution that brings together an ever-growing pool of third-party and partner data to optimize decision making.
Flexible Contracting and Deployment Options: Choose the right combination of image and data features, as well as technical integration models, to meet your specific needs.
Speed to Market: Get to market quickly with minimal development effort and an on-demand consumption model.
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.
You pay based on usage of this property image analytics solution. Twenty-six billing dimensions apply. Twenty-five charge per host hour of batch model inference, one for each machine learning instance type. These span the m5, m4, c5, c4, p2, and p3 families, from smaller sizes up to the largest configurations. Larger instances offer more compute for heavier batch workloads, so you select the size that fits your processing needs. A separate dimension charges per inference request, letting you pay by the volume of predictions you run.
Top-of-mind questions for buyers
What counts as one host hour for the batch inference dimensions?
A host hour is one hour that a chosen machine learning instance runs a batch inference job. You pick an instance type, such as ml.m5.large or ml.p3.16xlarge. Billing accrues for each hour that instance is active processing your batch workload. Larger instances cost per host hour at their own rate.
How do the per-host-hour charges combine with the per-request inference charge?
The two metrics bill independently on the same invoice. Host-hour dimensions meter running time of your selected instance during batch jobs. The request dimension meters the number of inference predictions you run. Which one dominates depends on your workload. Continuous batch processing favors host hours; high prediction volume favors request charges.
Am I charged for a batch inference instance when it is not running?
Charges apply per host hour while the instance is active on a batch job. Once the job finishes and the instance stops, software charges stop accruing. You only pay for the running time of the instance size you select. Underlying AWS resource fees may apply separately.
www.exlservice.com
Helpful?
Vendor refund policy
No Refund for this version
How can we make this page better?
Tell us how we can improve this page, or report an issue with this product.
Give us feedbackReport a problem with this product or seller
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).
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.
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:
Real-time inference
Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference .
Batch transform
Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI .
Version release notes
First Version
Additional details
Inputs
Outputs
Usage instructions
Sample notebooks
Inputs
Summary
Currently this version requires to enter required property attributes in the csv format
United Kingdom and Europe
St Clare House, 30-33 Minories, London, EC3N 1DD T +44 (0) 207.767.3500
United States (Global Headquarters)
320, Park Avenue, 29th Floor, New York, New York 10022 T +1 212.277.7100 F +1 212.277.7111
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.
EXL™ Transaction Insights offers a one-stop solution for mining deep insights from bank data. Built on EXL domain experience, analytic prowess and engineering expertise, the solution extracts deep customer insights such as strength & stability of their income, obligations, financial ecosystem and preferences. This helps financial institutions with a holistic 360-degree view of a customer assets and liabilities that can be leveraged across risk, marketing, and product design use cases to improve customer experience and strategies across the complete life cycle.
EXL Insurance LLM is a domain-specific large language model (LLM) built for the insurance industry. Unlike generic AI models, it is fine-tuned with private insurance data, using deep domain knowledge of industry-specific workflows and processes, enabling high-precision claims adjudication. The EXL Insurance LLM offers seamless integration with the NVIDIA AI Enterprise software platform, and is available as an NVIDIA NIM microservice.
EXL Code Harbor is a Generative AI-powered service leveraging multi-agent conversion framework that accelerates the migration of legacy codebases to novel and open-source languages, as well as enhances data and code governance. It leverages the modular capability of code conversion and optimization, code governance and documentation; and automated testing to convert the client's codebase. It addresses the manual effort involved in writing and optimizing code to transform the process, resulting in accelerated delivery, reduced costs, and higher accuracy.
EXL Paymentor℠ is an intelligent AI-driven collections and receivables management SaaS solution that engages customers in a two-way digital communication, provides collection analytics, and can be utilized throughout the collection lifecycle.
Paymentor℠ improves debt collections by increasing the liquidation rate, reducing the cost to collect, all while improving customer experience and retention. This cutting-edge solution provides intelligent digital debt collection services that work with your current CRM and payment processor. This allows lenders to automate, simplify, and manage collections effortlessly across multiple touchpoints throughout the entire collection process.
EXL SmartAudit.ai is a patented audit solution which re-imagines the audit transformation journey through a Gen-AI driven unified capability allowing automated monitoring of audit processes, maximizing the scope to ~100% coverage enabling higher and quicker detection of audit & compliance gaps.
The solution’s configurable audit engine and real-time dashboards empower teams with actionable insights, helping reduce audit handling time and increasing efficiency. With built-in capabilities for sentiment analysis, quality monitoring, and automated scoring, SmartAudit.AI ensures regulatory alignment and enhances service quality. Its intuitive interface and seamless data ingestion from diverse sources make it a powerful tool for improving audit reliability, optimizing training strategies, and elevating customer experience.
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.