S-Core Core AI Suite
Core AI Suite combines Red Hat OpenShift AI and MCP (Model Context Protocol) to make the AI inference workflow fully transparent, reduce operational complexity, and ensure consistent performance across diverse environments.
As organizations scale AI-based knowledge management, they face limitations such as black-box responses, opaque reasoning, and inaccurate answers to complex questions.
Existing RAG systems often cannot explain why a given answer was generated, making it difficult to operate AI reliably in enterprise environments.
As organizations expand AI knowledge management, they struggle with opaque reasoning, unreliable answers, and limited explainability in existing RAG systems, making enterprise deployment challenging.
- Joint Solution Value Proposition
- Autonomous AI Agent: Beyond simple search, the AI agent canreason, plan, and iteratively gather information until it finds the best answer. This enables more accurate responses, even for complex questions.
- Complete Transparency: Track the entire process in real time through visualizationsthat show which tools the agent called and why it made those decisions. AI no longer has to remain a black box.
- Maximizing Productivity: With our own LLM served through the Red Hat AI Inference Server, fast responses can be delivered without relying on external APIs.
- Security and Regulatory Compliance: By deploying in on-premises or hybrid environments, the solution supports data sovereignty and regulatory requirements, enabling safe use in finance, healthcare, and the public sector.
- Streamlined Operations & Flexible Scalability: The Red Hat OpenShift AI pipeline automates data preprocessing, chunking, and embedding generation, allowing developers to focus on higher-value tasks. From core to edge, the solution can be deployed close to where data resides, with the flexibility to scale as needed.
- Key Features
- MCP-based Real-Time Visualization: Monitor all actions of the AI agent in real time. Use an intuitive dashboard to see which tools the agent called, what data was processed at each step, and how the final response was generated.
- Red Hat AI Inference Server: A high-performance inference engine based on vLLM thatuses GPU memory efficiently, delivers high throughput under concurrent requests, and supports a wide range of open-source LLMs.
- Red Hat OpenShift AI Pipeline: It automates the end-to-end data workflow through an ML pipeline based on Kubeflow.
- Multi-Format Support: Powered by the open-source Docling engine, the solution can process a wide range of enterprise document formats, while preserving document structure to improve search quality.
- Enterprise Deployment: Its containerized architecture, built on Red Hat OpenShift AI, enables consistent deployment across environments.
- Getting Started
Core AI Suite enables rapid deployment through proven integration with Red Hat OpenShift AI. Leverage preconfigured
pipeline templates without having to build complex infrastructure from scratch.
Deployment Phase:
- Environment Setup and Model Selection
- Platform Integration
- Validation and Rollout
