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December 23, 2025
5 minute read

Reinventing Retail Forecasting with Autonomous MLOps on AWS

Background

Altimetrik Builds an Autonomous ML Ecosystem Driving Accuracy, Speed & Governance.

A global retailer partnered with Altimetrik to modernize its forecasting engine through a fully automated Champion/Challenger Machine Learning Framework powered by Amazon Sage Maker. The new MLOps ecosystem enables rapid experimentation, faster deployments, and zero downtime, reducing validation cycles from months to days while enhancing governance, observability, and cost efficiency.

The retailer’s legacy forecasting process relied on manual validation and limited transparency, slowing decisions across inventory, supply chain, and seasonal planning. As business complexity grew, the existing setup couldn’t support experimentation, enterprise governance, or real-time oversight, triggering the need for a modern, scalable MLOps foundation.

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Key Business Challenges

Slow & Manual Model Validation
Model evaluation required months of manual checks, limiting forecasting agility.
High Deployment Risk & Limited Experimentation
Introducing new algorithms was risky and lacked automated benchmarking against production models.
Insufficient Governance & Observability at Scale
Global operations needed stronger security, auditability, real-time monitoring, and cost visibility.

Solution Overview

Champion/Challenger ML Framework

• SageMaker manages training, tuning, drift detection, and production orchestration.

• Challenger models are benchmarked against Champion using identical data.

• Only outperforming models progress to production, ensuring continuous improvement without downtime.

Operational Excellence & MLOps Automation

• GitLab CI/CD pipelines for automated testing, security scans, and deployments.

• Datadog, Splunk, and PagerDuty for performance monitoring, logging, and incident response.

• Terraform provisioning ensures consistent, repeatable, cloud-native infrastructure.

Governance, Security & Compliance

• IAM, KMS encryption, MFA, VPC isolation, and Azure SSO integration.

• Full auditability via CloudTrail and compliant enterprise-grade architecture.

• Cost governance through AWS CUR insights and Cloudability.

Business Outcomes

Accelerated Innovation

Validation cycles reduced from months to days, enabling rapid experimentation.

Reliable, Continuous Forecasting

SageMaker ensures zero-downtime model

transitions with always-live Champion

models.

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Enterprise-Wide Efficiency & Governance

Improved accuracy, reduced operational overhead, enhanced security, and stronger cost optimization discipline.

Self-improving intelligence ecosystem

Altimetrik transformed the retailer’s forecasting into a self-improving intelligence ecosystem. The automated Champion/Challenger MLOps framework delivers continuous innovation, stronger governance, and business-ready reliability, creating a scalable blueprint for AI-driven decision-making in modern retail.

Client Success Stories

Real results in action

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Amit singh

“Amit Singh is the Chief Strategy Officer and Chief of Staff to the CEO at Altimetrik, where he drives corporate strategy, growth acceleration, and value creation through transformation initiatives. In this dual role, he partners closely with leadership teams, investors, and the board to align business strategy with sustained, technology-driven growth.

With over two decades of experience at the intersection of technology, business, and transformation, Amit brings a unique perspective on how organizations can innovate and adapt in a rapidly evolving digital landscape. His career has been defined by building high-performing teams, scaling innovative platforms, and driving organizational change to deliver lasting impact.

Before joining Altimetrik, Amit held senior leadership roles at Visa, where he led technology strategy, engineering, and product development for Real-Time Payments and the Visa Developer Platform. Earlier, he served as Chief Product Officer at a startup and spent more than a decade at Oracle, leading product and engineering teams across a wide range of enterprise software applications.”

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