AlgoRisk AI
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Model Space

Your collaborative workspace for building, testing, and deploying AI models with enterprise-grade security and compliance.

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Powerful Features

Everything you need to build, validate, and deploy AI models at scale

Rapid Development
Build and iterate on models faster with our intuitive development environment
  • Code templates
  • Auto-completion
  • Real-time testing
Enterprise Security
Bank-grade security with compliance frameworks built-in
  • SOC 2 compliant
  • End-to-end encryption
  • Audit trails
High Performance
Optimized infrastructure for lightning-fast model training and inference
  • GPU acceleration
  • Auto-scaling
  • Edge deployment
Team Collaboration
Work together seamlessly with advanced collaboration tools
  • Real-time editing
  • Version control
  • Code reviews
Advanced Analytics
Deep insights into model performance and business impact
  • Performance metrics
  • A/B testing
  • Custom dashboards
Easy Integration
Connect with your existing tools and workflows effortlessly
  • REST APIs
  • Webhooks
  • SDK support

Simple Workflow

From idea to production in three simple steps

1
Build & Train
Use our intuitive interface to build and train your models with pre-built templates and datasets
Code Editor
AutoML

Drag-and-drop components, automated hyperparameter tuning, and real-time validation

2
Test & Validate
Comprehensive testing suite with regulatory compliance checks and performance benchmarks
A/B Testing
Compliance

Automated bias detection, stress testing, and regulatory documentation generation

3
Deploy & Monitor
One-click deployment with continuous monitoring and automatic scaling capabilities
Auto-Scale
Monitoring

Real-time performance tracking, drift detection, and automated retraining

Supported Models

Wide range of model types and methodologies for every use case

Credit Risk
47 models

PD, LGD, EAD models with regulatory compliance

Market Risk
32 models

VaR, Expected Shortfall, stress testing models

Operational Risk
28 models

Fraud detection, AML, operational loss models

IFRS 9
15 models

Expected Credit Loss, staging, impairment

NLP Models
23 models

Document processing, sentiment analysis

Time Series
19 models

Forecasting, anomaly detection, trends

Classification
35 models

Binary, multi-class, ensemble methods

Regression
41 models

Linear, non-linear, regularized regression

Ready to Build?

Join thousands of data scientists and risk professionals building the future of AI-powered financial models.

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Free 14-day trial
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Enterprise support