NAMU Agentic AI for Red Hat AI Enterprise

• Enterprise-Grade Agentic AI: Provides chat bots, automated report generation, and MCP-based multi-agent collaboration on the platform, and handles large-scale inference workloads reliably through vLLM and llm-d-based distributed serving.

• Cost-Optimized SLM Strategy: Achieves enterprise-quality service levels while reducing Total Cost of Ownership (TCO) compared to closed-source APIs through inference optimization based on SLM and vLLM.

• Flexible Hybrid Deployment: Deploys and operates AI agents consistently across on-premise, private cloud, and hybrid environments, supporting compliance with domestic regulations such as PIPA.

• Rapid Time-to-Value: Shortens the time from PoC to production deployment through validated reference architecture and NAA Unified Workflow, providing consulting, implementation, and maintenance services bundled together.

• Full-Stack AI Agentic Platform: Integrated with a layered architecture, from GPU/NPU infrastructure, Red Hat OpenShift application platform, Red Hat OpenShift AI's model serving, pipeline, and Guardrails orchestration, all the way to the NAA application layer.

• NAA Unified Workflow: Six core features—Doc Chat, DB Chat, Generate Report, MCP, Agents, and Memory—are tightly integrated with Red Hat OpenShift AI to provide business automation and decision support in a single workflow.

• Context Engineering and RAG Pipeline: Processes multimodal knowledge (PDFs, images, text) through document extraction, embedding, and vector stores, combining them with short-term, long-term, and semantic memory for accurate agent responses via SLM inference.

• Verified Enterprise Infrastructure: Provides stability for safe operation in regulated industries, based on Red Hat OpenShift's Observability, Security & Governance, Storage, and Container/VM management features.

• Broad Hardware Compatibility: Supports training and inference for major GPU servers such as Dell, HP, Lenovo, and Nutanix, and AI accelerator chipsets including NVIDIA, AMD, and Rebellions.

• Built-in Regulatory Compliance: Domestic regulatory compliance, such as the Personal Information Protection Act (PIPA), is reflected in the solution's design, satisfying the requirements of strictly regulated industries like finance, healthcare, and public sector.

The bio and healthcare industries simultaneously demand personal information protection and large-scale research/clinical data analysis. NAA is being utilized as a solution that satisfies both regulatory compliance and business efficiency in this environment.

NAA provides an agent for generating clinical professional reports up to 500 pages long, Doc Chat linked to internal DBs, and security agents. This enables researchers to comply with personal information protection regulations while rapidly analyzing academic papers and clinical data and deriving insights. Notably, the automated report generation feature significantly reduces document preparation time, contributing to improved research productivity.

Furthermore, in the finance and manufacturing industries, NAA addresses key pain points through features such as generative reports, DB Chat, and GPU resource optimization. In the financial sector, real-time indicator analysis and automated report generation based on internal DBs are possible, while in the manufacturing sector, optimization of GPU resources based on Red Hat OpenShift provides operating cost reduction benefits.

• Assessment & planning (1~2 weeks): Define the industry domain and business scenarios, and establish data/security requirements and deployment architecture.

• Stack deployment (1~2 weeks): Perform Red Hat OpenShift AI installation, NAA Unified Workflow linkage, and integration of supported hardware.

• Pilot build & validation (2~4 weeks): Build priority agents such as Doc Chat and Generate Report, and complete PoC verification with actual business data.