The generative AI revolution has arrived, but enterprise adoption remains fragmented.  Latency, cost, security, and data ownership concerns hinder broad-scale deployment of  large language models (LLMs). SambaNova Systems answers this call with a reimagined, full-stack AI platform built for enterprise performance, privacy, and scale. This white paper  explores how SambaNova’s Composition of Experts (CoE) architecture, powered by its  SN40L chip and DataScale platform, is enabling enterprises to securely deploy generative  AI models across functions, on their terms. 

1. Introduction 

Generative AI promises to transform enterprise operations—from customer support and  document summarization to risk analysis and product development. However, relying on  cloud-based APIs or generic monolithic models introduces challenges: 

• Unpredictable latency 
• High inference costs 
• Limited control and customization 
• Data governance and privacy risks 

SambaNova Systems has built a new paradigm that resolves these constraints,  empowering organizations to take AI in-house with the world’s fastest and most secure  enterprise-grade platform. 

2. Market Challenges 

Today’s enterprises face: 

• GPU Bottlenecks: Legacy GPU-based inference introduces latency and  infrastructure sprawl. 
• Closed AI Models: Cloud APIs offer limited customization and explainability.
• Cost Overruns: Token-based billing and scaling complexity inflate TCO. 
• Data Governance Risks: Sending proprietary or regulated data to public models  threatens compliance. 

Enterprises require a solution that balances performance, control, and cost-effectiveness  without compromise. 

3. SambaNova’s Breakthrough: Composition of Experts (CoE) 

SambaNova’s answer is the Samba-1 model—a 1.3 trillion parameter foundation model  based on Composition of Experts architecture. 

Key capabilities: 

• Multiple domain-specific expert models working together 
• Smart routing of prompts via a controller model 
• Role-based access control and model partitioning 
• 10x lower inference costs via selective model loading 
• On-prem or hosted deployment for security and governance 

The CoE approach allows SambaNova to outperform monolithic models in speed,  accuracy, and scalability across use cases. 

4. Powered by the SN40L Chip and DataScale Platform 

At the core is the SN40L Reconfigurable Dataflow Unit (RDU): 

• 638 TFLOPS AI compute 
• 1.5 TB memory, 5nm process 
• 10x lower latency vs. GPU stacks 

The DataScale platform provides: 

• Full-stack orchestration (training + inference) 
• Integration with open-source LLMs and enterprise data 
• Modular deployment via the SambaNova Suite and SambaStudio

This creates a complete AI fabric for both model builders and business teams. 

5. Real-World Impact 

SambaNova’s solutions are already transforming sectors: 

• Public Sector: LLNL, TACC use SambaNova for scientific inference at scale • BFSI: Signal-oriented banking and fraud detection 
• Enterprise SaaS: Sales coaching, job matching, knowledge agents • Retail & Energy: RAG pipelines, customer support, field ops automation These clients report: 
• Up to 300% faster application response 
• Up to 80% lower energy use vs. GPUs 
• Full model/data ownership and compliance alignment 

6. Conclusion: A New Standard for Enterprise AI 

SambaNova delivers the performance of trillion-parameter models with the flexibility and  security enterprises need. Its CoE architecture redefines TCO and unlocks multi-domain  generative AI that works within the enterprise’s control boundaries. 

As AI moves from hype to enterprise-wide execution, SambaNova is setting the new  standard for speed, trust, and scale in the age of private AI. 

To Learn More: 

Contact: Consult@aimach.net