Intelligent MLOps
Services
From Notebook to Production. Seamlessly.
Industry Applications
Fintech & Banking
- •Real-time model governance for regulatory-compliant AI in fraud and credit scoring.
- •CI/CD pipelines for faster deployment of risk analytics and personalization engines.
Retail & Consumer Tech
- •Automated model refresh for demand, pricing, and inventory optimization.
- •Performance tracking of recommendation models across channels and customer segments.
EdTech & Online Learning
- •Scalable pipelines for continuous learning model updates based on user interaction data.
- •Centralized registry and monitoring for models powering adaptive assessments.
Healthcare & Life Sciences
- •ML observability for clinical decision models to ensure safety and accuracy.
- •End-to-end audit trails for AI models used in diagnostics and treatment forecasting.
Our Core Services
Pipelines
Models
Drift Detection
Detect Model Drift
Versioning
Version Control
Scheduling
Live Data
Code For ML
Templates
Pipelines
Models
Drift Detection
Detect Model Drift
Versioning
Version Control
Scheduling
Live Data
Code For ML
Templates
Model Reliability
Always-on, production-grade ML
Fast Deployment
Move from training to live in days
Repeatable, Scalable ML Infra
Templates and pipelines that grow with your models
Trusted & Traceable
Built for compliance
Cost Efficient
Eliminate shadow tech and idle compute
WHY IT
MATTERS
WHY IT
MATTERS
Model Reliability
Always-on, production-grade ML
Fast Deployment
Move from training to live in days
Repeatable, Scalable ML Infra
Templates and pipelines that grow with your models
Trusted & Traceable
Built for compliance
Cost Efficient
Eliminate shadow tech and idle compute
REAL RESULTS
Reduced false positives in credit card fraud detection by 76% using AI models with explainability, retraining, and rule integration
Segmented customers using clustering to tailor marketing strategies and increase sales across income groups and purchase behaviors
Built a promotional mix modeling engine to quantify ROI by channel and optimize marketing spend using historical sales data
Reduced false positives in credit card fraud detection by 76% using AI models with explainability, retraining, and rule integration
Segmented customers using clustering to tailor marketing strategies and increase sales across income groups and purchase behaviors
Built a promotional mix modeling engine to quantify ROI by channel and optimize marketing spend using historical sales data
Platform Advantage
Automind for no-code MLOps:
- Drift monitoring
- SHAP dashboards
- Auto retraining workflows
TECH STACK
WHY INTELSTACK?
30+ cross-platform MLOps engineers
Pre-built Accelerators that cut dev time
Seamless collaboration with data science teams
30+ cross-platform MLOps engineers
Pre-built Accelerators that cut dev time
Seamless collaboration with data science teams
Case Studies & Resources
Ready to Scale Your AI?
Let's move your models from lab to live.
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