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Extreme Scale Solutions

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Extreme Scale Solutions is a United States-based AI/ML engineering firm that builds and deploys advanced AI/ML systems under real-world constraints such as latency, cost, security, privacy, auditability, and operational robustness.

Last updated September 28, 2026

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Overview

Extreme Scale Solutions is a United States-based AI/ML engineering company headquartered in Newark. According to its official website, the firm builds and deploys advanced AI/ML systems where real constraints dominate: latency, cost, security, privacy, auditability, and operational robustness. Its stated mission is to solve extreme challenges with precision and speed, spanning from FPGA inference at the edge to exabyte-scale graph optimization in supercomputers. The company organizes its work around five core disciplines. High-Throughput Inference covers FPGA and embedded NPU deployments where determinism and efficiency matter, including quantization, memory planning, and throughput tuning for real-time constraints. Multimodal Retrieval focuses on RAG and Graph-RAG systems that convert long-tail enterprise knowledge into cited answers, using vision transformers, chunking strategies, and provenance tracking. Perception & Audio Intelligence delivers real-time sensing and interaction, from YOLO object detection on edge devices to target-speaker extraction, beamforming, and acoustic anomaly detection. Security & Privacy addresses Homomorphic Encryption, Post-Quantum Cryptography, and device trust primitives, with custom hardware acceleration for encrypted ML inference with zero data exposure. Scientific ML & HPC Performance Engineering applies Fourier Neural Operators, physics-informed neural networks, and distributed training at DOE supercomputer scale, with rigorous profiling, reproducible benchmarking, and measurable acceleration across chemistry, seismic, and related domains. As of the official website, Extreme Scale Solutions reports 19 active projects, 5 core disciplines, and 9 industry domains. The company positions itself at the intersection of edge computing and high-performance computing (HPC), serving organizations that need AI/ML systems to operate under demanding technical and regulatory constraints. Its public-facing materials emphasize proven deployments rather than research prototypes, and its capabilities span the full stack of applied AI/ML from hardware-level inference optimization to enterprise knowledge systems. Extreme Scale Solutions is a private company; no parent company, owner, or listed status is disclosed in the available evidence. Its headquarters is in Newark, United States, and its primary operating market is the United States. The company maintains a public website at extreme-scale.com.

History

Extreme Scale Solutions is a United States-based AI/ML engineering company headquartered in Newark. The available evidence does not disclose a founding year, founder, ownership structure, or detailed corporate history. What is known comes primarily from the company's official website, which describes its mission and capabilities. The company positions itself as an engineering firm that builds and deploys advanced AI/ML systems where real constraints dominate: latency, cost, security, privacy, auditability, and operational robustness. Its stated scope runs from FPGA inference at the edge to exabyte-scale graph optimization in supercomputers. This places the firm in the applied AI/ML engineering space, serving organizations that need production-grade systems rather than research prototypes. Extreme Scale Solutions organizes its work around five core disciplines. High-Throughput Inference addresses FPGA and embedded NPU deployments where determinism and efficiency matter, including quantization, memory planning, and throughput tuning for real-time constraints. Multimodal Retrieval covers RAG and Graph-RAG systems that convert long-tail enterprise knowledge into cited answers, using vision transformers, chunking strategies, and provenance tracking. Perception & Audio Intelligence delivers real-time sensing and interaction, from YOLO object detection on edge devices to target-speaker extraction, beamforming, and acoustic anomaly detection. Security & Privacy focuses on Homomorphic Encryption, Post-Quantum Cryptography, and device trust primitives, with custom hardware acceleration for encrypted ML inference with zero data exposure. Scientific ML & HPC Performance Engineering applies Fourier Neural Operators, physics-informed neural networks, and distributed training at DOE supercomputer scale, with rigorous profiling, reproducible benchmarking, and measurable acceleration across chemistry, seismic, and related domains. As of the official website, the company reports 19 active projects, 5 core disciplines, and 9 industry domains. Its public-facing materials emphasize proven deployments and real-world constraints. The company maintains a public website at extreme-scale.com. No parent company, owner, or listed status is disclosed in the available evidence, and no major corporate milestones, funding events, or leadership changes are documented in the supplied sources.

Products and positioning

AI/ML engineering at scale, solving extreme challenges with precision and speed under real constraints including latency, cost, security, privacy, auditability, and operational robustness.

  • High-Throughput Inference

    FPGA and embedded NPU deployments where determinism and efficiency matter. Quantization, memory planning, and throughput tuning for real-time constraints.

  • Multimodal Retrieval

    RAG and Graph-RAG systems that convert long-tail enterprise knowledge into cited answers. Vision transformers, chunking strategies, and provenance tracking.

  • Perception & Audio Intelligence

    Real-time sensing and interaction: from YOLO object detection on edge devices to target-speaker extraction, beamforming, and acoustic anomaly detection.

  • Security & Privacy

    Homomorphic Encryption, Post-Quantum Cryptography, and device trust primitives. Custom hardware acceleration for encrypted ML inference with zero data exposure.

  • Scientific ML & HPC Performance Engineering

    Fourier Neural Operators, physics-informed neural networks, and distributed training at DOE supercomputer scale. Rigorous profiling, reproducible benchmarking, and measurable acceleration across chemistry, seismic, and related domains.

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