AIR: Scaling Analytics with Automation and Integration

At LTPlabs, we design solutions that empower clients to extract value from data at scale. Our AIR platform plays a key role in this mission, acting as the bridge between analytical models, business applications, and production environments.

Seamless Orchestration with AIR
AIR exposes an API that allows external systems — whether internal tools or client applications — to communicate with Argo Workflows and run code on demand. This ensures that advanced analytics can be embedded directly into business processes, transforming data-driven insights into operational impact.

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Enabling Scalable and Responsive Analytics
To make AIR accessible for real-world business scenarios, we developed AIRPY, a lightweight Python package that simplifies integration by handling login, token refresh, and file transfers while supporting asynchronous execution. This allows clients to delegate heavy tasks from dashboards (e.g., Plotly visualizations) to AIR, ensuring applications remain fast, scalable, and responsive. With AIRPY, analytical models can interact directly with workflows, turning complex computations into smooth user experiences.

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Built on Modern CI/CD Practices
Reliability is at the core of AIR. By adopting Continuous Integration, every code change is automatically tested and validated, ensuring consistent quality. Through Continuous Deployment, successful builds seamlessly move from development to staging and production environments, accelerating delivery without compromising stability.

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Safe and Robust with GitOps
All AIR deployments follow LTPlabs’ GitOps approach. Infrastructure configurations live in Git as the single source of truth. Automated pipelines ensure that reality always matches what is defined in code, while observability tools detect and fix drift. For clients, this means solutions deployed on AIR are not only scalable but also secure, traceable, and robust by design.

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By combining orchestration, integration, and automation, AIR enables LTPlabs to deliver analytics that scale beyond prototypes, helping clients operationalize data science with confidence.

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