Sold by: ETIQ AIÂ
Deployed on AWS
AWS Free Tier
A software solution to identify opportunities and test for weaknesses in your AI
Overview
Etiq.ai is a flexible and customizable software tool for data scientists, risk, and business managers in the insurance, lending, and the finance technology industry. Etiq helps to discover new business opportunities, mitigate risk, increase productivity, data accuracy, and transparency by identifying and mitigating unintended bias in machine learning algorithms. Etiq's functionality allows data scientists & risk managers to test and store pipelines, then make parallel comparisons between pipelines when experimenting with debiasing. It allows you to identify areas of improvement, perform model monitoring and diagnosis in your algorithms. For both tech and commercial teams, an interactive dashboard that helps understand and substantiate the drivers behind machine learning models, showcase risk evaluation, accuracy, fairness, and growth potential.
Highlights
- AI monitoring
- AI governance
- Machine learning
Details
Sold by
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
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. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
t3.small Recommended | $5.34 |
t3.micro AWS Free Tier | $5.34 |
t2.micro AWS Free Tier | $5.34 |
c5n.large | $5.34 |
t2.medium | $5.34 |
c6in.large | $5.34 |
t3.medium | $5.34 |
t3a.medium | $5.34 |
c6i.large | $5.34 |
c5ad.large | $5.34 |
Vendor refund policy
Yes, email support.
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
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
- Data Fingerprinting
- Added Apple Silicon Support
Additional details
Usage instructions
Resources
Vendor resources
Support
Vendor 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.
Updated weekly
Top
100
In ML Solutions
Top
100
In Data Governance
Top
25
In Observability, Software Development
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
AI Bias Detection
Advanced algorithm for identifying and mitigating unintended bias in machine learning models
Model Pipeline Management
Capability to test, store, and perform parallel comparisons between different machine learning pipelines
Model Monitoring
Comprehensive diagnostic and monitoring functionality for tracking algorithm performance and characteristics
Interactive Visualization
Dashboard interface for visualizing model insights, risk evaluation, and performance metrics
Machine Learning Governance
Framework for evaluating and ensuring transparency, fairness, and accuracy in AI model development
Data Type Monitoring
Supports monitoring of tabular, image, and text data across machine learning applications
ML Tool Integration
Integrates with popular machine learning and data tools including Pandas, Apache Spark, AWS SageMaker, MLflow, Flask, Ray, RAPIDS, and Apache Kafka
Anomaly Detection
Out-of-the-box automated anomaly detection capabilities for identifying data quality issues, data bias, and concept drift
Privacy Preservation
No-configuration solution that operates without processing raw data, ensuring privacy and enabling massive scale monitoring
Observability Capabilities
Automated monitoring and alerting across multiple data vitals with lightweight integrations and purpose-built visualizations
Agent Observability
Comprehensive tracing and visualization of AI agent behavior including user inputs, routing logic, tool calls, memory access, and model outputs using tree-structured traces
Prompt Optimization
Interactive development environment for designing, testing, comparing, and evolving prompts with integrated evaluation results and live input/output analysis
Model Evaluation Framework
Offline and online LLM-as-a-Judge evaluations to assess accuracy, tool-calling capabilities, planning, and goal achievement of AI agents
Continuous Improvement Workflow
Closed-loop improvement mechanism combining trace analysis, evaluation feedback, and curated datasets for iterative agent performance enhancement
Monitoring and Anomaly Detection
Real-time monitoring with custom metrics tracking latency, token usage, failures, and ability to surface anomalies across traditional ML, computer vision, and generative AI models
Standard contract
No
No
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