LigaData AI Fabric is an enterprise AI platform designed to help organizations operationalize their AI models at scale. Covering the complete machine learning lifecycle—build, deploy, and monitor—the platform accelerates the journey from development to production from weeks to hours.
LigaData AI FABRIC
Enterprise ML Platform
Platform Overview
AI Fabric brings together development, operations, and governance to support scalable and repeatable ML outcomes.
Collaborative Development Workbench
A ready-to-use, shared environment for data scientists and ML engineers, enabling rapid experimentation with familiar tools and libraries.
Native Data Platform Integration
Tight integration with LigaData Data Platform (LDP) provides direct access to governed, production-ready data and features.
Distributed & Scalable ML Runtime
Run ML workloads on Kubernetes with support for distributed processing and mixed CPU/GPU clusters.
Multi-Version Model Management
Track experiments, manage model versions, and control promotions across development and production environments.
Hybrid Deployment Ready
Deploy consistently across cloud, on-premise, or hybrid environments.
Simplified MLOps — Platform Highlights
- Collaborative Development in shared workspaces
- Central model tracking & registry for version control and reuse
- Continuous Training & Continuous Deployment (CT/CD) for faster releases
- Model serving lifecycle management (deploy, scale, upgrade, rollback) via APIs or batch scoring
- Performance monitoring & drift detection to maintain accuracy over time
Key Capabilities
Designed for production ML, not just experimentation
- Library-agnostic model support
- Containerized training and deployment
- CI/CD-integrated ML pipelines
- Workflow orchestration and scheduling
- Drift monitoring and continuous retraining
What’s New in AI Fabric 2.0
Enhanced usability, automation, and control
UX-Driven Model Deployment & Management
Deploy trained MLflow models and manage endpoints directly from the user interface.
Template-Based Workflow Orchestration
Copy, customize, and run LigaData-provided Argo templates to accelerate ML pipelines.
Unified User Experience
A single interface across model development, deployment, orchestration, and monitoring.
Pre-Integrated CI/CD Pipelines
Automate the build, packaging, and deployment of ML code using Argo-driven CI/CD workflows.
Customer Value
Measurable impact for AI and IT teams
Shorter Go-Live Cycles
Reduce production release timelines from weeks to days.
Cost Efficiency
Achieve 20–40% average improvements in infrastructure and resource utilization.
Higher AI Success Rates
Increase successful model experiments by up to 30%.
Ready to Operationalize AI?
Turn AI projects into enterprise intelligence—at scale.
