# SambaNova Systems **Source:** https://geo.sig.ai/brands/sambanova-systems **Vertical:** AI Infrastructure **Subcategory:** AI Chips & Enterprise Platform **Tier:** Emerging **Website:** sambanova.ai **Last Updated:** 2026-04-14 ## Summary AI chip and platform company. $1.48B total raised ($350M Series E Feb 2026). SN50 chip: 5x faster, 3x lower cost. Intel partnership. Founded in Palo Alto. ## Company Overview SambaNova Systems was founded in 2017 by Stanford professors Kunle Olukotun and Chris Ré, along with Rodrigo Liang, to build a full-stack AI platform combining custom silicon, software, and enterprise deployment services. The company's Reconfigurable Dataflow Architecture (RDA) chip is designed specifically for AI workloads, with hardware that adapts its computational structure to match the dataflow patterns of neural network inference and training. This architectural approach contrasts with NVIDIA's CUDA-centric GPU paradigm, offering potential advantages in efficiency for specific enterprise AI deployment patterns.\n\nSambaNova offers an integrated platform—hardware, software, and model serving—targeted at large enterprises and government customers that need to run powerful AI models with strict data security, compliance, and performance requirements. Its SN50 chip delivers claimed 5x speed improvements and 3x cost reductions compared to H100 GPUs for inference workloads, making it attractive for high-volume enterprise AI deployment. The company has partnered with Intel to broaden its hardware ecosystem and offers pre-trained foundation models optimized for its silicon as part of its enterprise AI suite.\n\nSambaNova has raised $1.48B in total funding, including a $350M Series E in February 2026, demonstrating continued investor confidence in its enterprise-focused AI hardware strategy. The company targets a differentiated position from NVIDIA by going deep on the full stack for enterprise customers rather than competing head-to-head on general-purpose AI compute. Government and regulated industry deployments—where on-premises, auditable AI infrastructure is required—are a particularly strong segment for SambaNova's integrated approach. ## Frequently Asked Questions ### What is the SN50 chip? Fastest chip for agentic AI: 5x speed, 3x lower TCO, supports 10T+ params and 10M+ context. ### How much has SambaNova raised? $1.48B total. $350M Series E (Feb 2026) from Vista, Cambium, Intel Capital. ### What is the Intel partnership? Multi-year deal for cost-efficient enterprise AI inference solutions. ### What is SambaNova's DataScale system? DataScale is SambaNova's full-stack AI hardware and software system that combines SN-series reconfigurable dataflow units (RDUs) with integrated memory, networking, and the SambaFlow software stack. It is designed for enterprises that want to run large AI models on-premises rather than in the cloud, offering predictable performance, data privacy, and lower long-term TCO than cloud GPU instances for sustained workloads. ### What is SambaNova's SambaFlow software? SambaFlow is SambaNova's ML framework that optimizes model graph execution on SN-series RDU hardware. It compiles PyTorch models to run on RDUs with minimal code changes, handling the hardware-specific optimization automatically. SambaFlow supports standard deep learning frameworks and enables customers to run existing model training and inference code on SambaNova hardware without rewriting applications. ### How does SambaNova's RDU architecture differ from NVIDIA GPUs? NVIDIA GPUs use a fixed SIMD architecture designed for general-purpose parallel computation. SambaNova's Reconfigurable Dataflow Unit (RDU) architecture uses a spatial dataflow model that maps neural network computation graphs directly onto configurable processing elements — reducing data movement overhead and achieving higher throughput for specific AI workload patterns, particularly large model inference where memory bandwidth is the primary constraint. ### Who are SambaNova's enterprise customers? SambaNova has deployed its DataScale systems at national labs, government agencies, and large enterprises in financial services and healthcare that require on-premises AI compute for data sovereignty and security reasons. Government customers include US national laboratories and defense-affiliated research institutions seeking secure AI compute not dependent on commercial cloud infrastructure. ### How does SambaNova compete with NVIDIA for enterprise AI hardware? SambaNova competes on total cost of ownership for enterprises running sustained AI workloads — particularly large language model inference where the SN50 chip's 5x speed advantage and 3x lower TCO (compared to H100) makes it compelling for organizations with predictable, high-utilization AI compute needs. NVIDIA's ecosystem breadth, software maturity, and supply scale remain significant advantages, but SambaNova targets workloads where its specialized architecture delivers measurably better economics. ## Tags ai-powered, b2b, infrastructure, platform, saas --- *Data from geo.sig.ai Brand Intelligence Database. Updated 2026-04-14.*