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Now running 300+ production models

Run every model.
AI and analytics, all in one place.

AIR is the orchestration platform that takes your analytical and AI models from notebook to production — scheduled, monitored, and fully traceable at any scale.

+100Kworkflows tracked
3M+minutes computation executed
99%+avg success rate
5+industries served
Platform Features

Everything your
models need to ship.

From scenario configuration to output visualization and comparison, AIR covers the full lifecycle of every AI and analytical run — so your team stays focused on insights, not infrastructure.

  • Workspace & App Management

    Organise your models into Workspaces and Apps. Each app encapsulates its own configuration, schedule, and run history — giving teams clear ownership and visibility.

  • Scheduled & On-Demand Runs

    Trigger models on a cron schedule, on demand, or via external events. AIR tracks every run with a unique ID, timestamp, and full execution trace — nothing falls through the cracks.

  • Kubernetes-Native Execution

    Models run in isolated containers orchestrated by Argo Workflows on Kubernetes. Scale from one to thousands of parallel runs without changing a line of model code.

  • S3 Artifact Management

    Every run's inputs and outputs are automatically stored and versioned in S3. Download raw files, compare runs side by side, or pipe artifacts into downstream systems.

  • Databricks Integration

    Connect any Databricks Job by ID and workspace path. AIR manages job submission, log collection, and output file retrieval — keeping your data pipelines in sync.

  • Live Monitoring & Notifications

    Track TTFB, average duration, success rate, and error rate across all apps. Get notified on run completion, failures, or runs exceeding expected duration — before anyone notices.

  • GitOps Ready

    CI/CD

    Use YAML definitions and standard CI/CD pipelines to version, review, and deploy your models' source code directly into AIR. Bring your Git workflow — AIR handles the rest, keeping every model update auditable, repeatable, and rollback-ready.

How it works

From config to production
in four steps.

  1. Configure your App

    Define inputs, parameters, Databricks job IDs, and output files. Set webhooks and alert preferences in the app config panel.

  2. Schedule or trigger

    Set a cron schedule or run on demand. AIR registers a new Run, validates inputs, and queues execution on the cluster.

  3. Execute & monitor

    Argo Workflows spins up your containerized model. AIR streams execution logs, tracks duration, and alerts if something goes wrong.

  4. Inspect & compare

    Download artifacts, visualize results, and compare runs side by side. Every output is timestamped, versioned, and traceable to its source.

Integrations

Plugs into your
existing stack.

AIR connects with the tools your data and engineering teams already use.

  • Amazon S3
  • Databricks
  • Kubernetes
  • Argo Workflows
  • Webhooks
  • Excel / XLSX
  • REST API
  • Docker
Run observability

Every run tells
a complete story.

Drill into any run and see the full picture: execution pipeline, input assets, output files, and logs. Compare across runs to understand model drift or performance changes over time.

  • Multi-stage pipeline tracking

    Track each phase — Input, Parameters, Data Preparation, Computation — with exact timing and status. Spot bottlenecks before they escalate.

  • Downloadable artifacts per run

    Inputs, parameters, outputs, and visualizations — every asset versioned and always one click away.

  • Side-by-side run comparison

    Compare any two runs across outputs and KPIs. Understand the delta between scenarios instantly.

Architecture

Built for scale.
Engineered for reliability.

AIR is built on a microservices stack — containerized models execute on Kubernetes via Argo Workflows, while artifacts flow through S3 and results reach you through a clean, unified API.

Trigger Layer

Scheduler

Cron / Manual

REST API

External trigger

Webhook

Event-driven

AIR Core

Run Manager & Config Engine

WorkspaceAppRun lifecycle

Orchestration

Alerts

Notifications

Metrics and Logs

Debugging

Visualization

Check results and compare runs

Argo Workflows

Kubernetes-native orchestration

Storage and Integrations

Amazon S3

Artifacts & assets

Databricks

Jobs & notebooks

Model Containerized in Pod1

Model Containerized in Pod2

Model Containerized in Pod2

Kubernetes Cluster

Security & Compliance

Enterprise-grade security,
by design.

AIR is built to meet the standards enterprises demand. ISO certified, GDPR ready, and architected for high availability — your data and processes are in safe hands.

ISO 27001 CertifiedGDPR Compliant

ISO 27001 Certified

Our security management practices are independently audited and certified to ISO 27001, ensuring your data is protected to the highest standard.

GDPR Ready

Full compliance with GDPR and EU data protection regulations. Data residency controls, right-to-erasure support, and transparent data processing agreements.

Automated Backups

Continuous automated backups of all run data, configurations, and artifacts. Point-in-time recovery ensures your operations are never at risk of permanent loss.

High Availability & Redundancy

Multi-zone deployment with automatic failover. Designed to eliminate single points of failure — your models keep running even under infrastructure stress.

Role-Based Access Control

Fine-grained RBAC across workspaces, apps, and runs. Define who can view, trigger, or configure models — with full audit logs of every action.

Encrypted at Rest & in Transit

All data — run artifacts, inputs, outputs, and configuration — is encrypted at rest with AES-256 and in transit with TLS 1.3. No exceptions.

99.9% Uptime SLA

Multi-zone deployment with automatic failover. Designed to eliminate single points of failure — your models keep running even under infrastructure stress.

Get started

Your models deserve
a better runway.

Stop babysitting notebooks. Let AIR handle scheduling, execution, monitoring, and results — so your team can focus on building better models.

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AIR | LTPlabs