The Strategic Challenge

Enterprises today face significant hurdles when deploying AI on-premises. The journey is often fraught with lengthy deployment cycles that can span months, the immense complexity of integrating diverse hardware and software components, and the constant demand for specialized skills to manage and maintain containerized environments.

Ensuring the performance, scalability, and cost-control for powerful platforms like IBM watsonx can create a major resource drain on IT departments. Organizations need a way to harness the full power of enterprise-grade AI without the associated risks and operational overhead, allowing them to focus on innovation and business value, not infrastructure management.

The Solution

The Li9 On-Premises AI Pilot, powered by IBM Fusion HCI, is a purpose-built, pre-integrated system that delivers a self-service cloud experience directly in your data center. This turnkey service is the definitive on-ramp for deploying the full IBM watsonx AI and Data platform with unparalleled simplicity and speed.

Our expert-led engagement provides a complete solution that combines high-performance compute, storage, networking, and GPUs with a pre-deployed Red Hat OpenShift environment. By eliminating integration risks and automating complex setup processes, we provide an optimized platform that allows you to accelerate your AI strategy and focus on driving business innovation from day one.

Deliverables

Upon completion of the On-Premises AI with watsonx Pilot, you will receive:

• Production-ready, enterprise-grade private cloud platform, professionally installed and configured with the complete hardware and software stack.
• Validated and healthy installation of the IBM watsonx platform, tailored to your specific use case. This includes essential components such as watsonx.data for your data lakehouse solution, running on the integrated Red Hat OpenShift cluster, with options to include watsonx.ai and watsonx.governance based on your requirements.
• Baseline data lakehouse architecture built on IBM Storage Ceph, ready for your data ingestion and analytics workloads. This specifically leverages watsonx.data for its core functionality.
• Detailed architectural diagrams, configuration guides, and operational runbooks for your new environment.
• Our team will receive hands-on knowledge transfer sessions, ensuring they are prepared to manage, use, and innovate on the new AI platform.

How It Works

Our solution is built on a validated, multi-layer architecture where each component is engineered to deliver a seamless, high-performance platform for your on-premises AI workloads.

• IBM watsonx Platform & Cloud Pak for Data: This serves as your flexible engine for enterprise AI and data. The stack is deployed based on your specific needs, with watsonx.data being a core component for the data lakehouse, and additional modules like watsonx.ai for building, training, and deploying models, and watsonx.governance for ensuring trust and transparency, available for activation as required by your use case.
• Red Hat OpenShift: The enterprise-grade Kubernetes layer provides robust, scalable, and secure container orchestration. It creates a consistent cloud-native environment that simplifies the deployment and management of the entire watsonx software stack.
• IBM Fusion HCI + Ceph Storage: This is the hyperconverged foundation that makes it all possible. The pre-engineered appliance integrates all necessary compute, GPU, storage, and networking, eliminating guesswork and configuration complexity. It is built on IBM Storage Ceph, providing a high-performance, cost-effective object storage layer that can scale as your data lakehouse grows.
• Optional AFM Data Accelerator Nodes: For data lakes residing external to Fusion HCI (e.g., in remote S3 or Azure Blob buckets), optional AFM (Active File Management) data accelerator nodes can be added. These nodes intelligently and transparently cache remote data in Fusion HCI local storage, significantly improving query performance for external data sources. Configurable policies allow for pre-fetching data or fetching on demand, and for purging stale data, ensuring optimal data currency and access speed.