Top 50 Analog Neural Network Chip in LATAM

The startup develops deep sub-threshold analog in-memory computation semiconductors that execute data-center-grade AI workloads with significantly lower power consumption and no active cooling. This technology processes data within memory, enabling industries to efficiently handle complex tasks while minimizing energy use.

Ambient Scientific develops ultra-low power AI microprocessors, such as the GPX10, specifically designed for on-device edge computing applications. These processors utilize proprietary architecture to accelerate neural networks while consuming minimal power, enabling years of always-on AI functionality from a single battery. This technology reduces reliance on cloud infrastructure, offering lower latency and enhanced data privacy for sensor fusion, audio, and vision tasks.

EnCharge AI develops high-efficiency analog in-memory computing GPUs and digital AI accelerators for edge-to-cloud deployment. Their validated hardware and flexible software offer significant improvements in performance, TCO, and sustainability compared to traditional solutions. The company provides versatile products from chiplets to PCIe cards, enabling seamless orchestration for on-device and cloud AI inference.

The startup develops customized semiconductors based on an open instruction set architecture, enabling system designers to create tailored microprocessors efficiently. This approach reduces time-to-market and lowers costs for companies needing specialized silicon solutions.

Provides scalable neural processor unit (NPU) semiconductor IP with a packet-based architecture that enables parallel execution of AI workloads, achieving up to 90% processor utilization. This approach reduces memory overhead, power consumption, and latency while supporting complex AI models across edge devices in industries like mobile, automotive, and industrial automation.

Baya Systems develops customizable, software-driven System IP solutions for chiplet-based semiconductor systems, enabling efficient data movement and high-performance computing. Their technology addresses the complexity and cost of delivering scalable, modular architectures by providing a unified fabric that supports advanced cache coherency and optimized throughput for diverse applications.

Astera Labs develops semiconductor-based connectivity solutions, including PCIe over optics and smart fabric switches, to enhance the scalability and efficiency of AI and cloud infrastructure. Their technology addresses the challenge of optimizing resource management in data centers, enabling higher GPU cluster utilization and improved performance.

D-Matrix has developed Corsair, an AI inference platform that achieves 60,000 tokens per second with 1 ms latency for Llama3 8B models, significantly enhancing throughput and energy efficiency in datacenters. This technology addresses the high computational costs and energy consumption associated with large-scale AI inference, enabling organizations to scale their AI capabilities sustainably.

Marte provides a privacy-first AI ecosystem and infrastructure, offering scalable API access to frontier language models optimized for enterprise speed, privacy compliance, and cost-efficiency. They are also developing symbolic AI engines for explainable, deterministic, and edge-deployable AI, with their first engine already live for embedded AI use cases.

DeGirum develops an AI Hub that integrates hardware and software infrastructure to streamline the development and deployment of edge AI applications. By providing a unified software toolchain and flexible hardware options, it reduces time to market and minimizes costs associated with multiple hardware and application investments.

Nuvia designs high-performance processors optimized for compute-intensive applications through advanced silicon architecture, significantly enhancing processing speed and energy efficiency. The company provides a solution for the increasing demand for computational power in data centers and high-performance computing environments.

Celestial AI develops the Photonic Fabric™, an optical interconnect technology that enhances data transfer speeds and reduces latency in AI computing and memory infrastructure. This technology addresses the limitations of traditional interconnects by enabling high-bandwidth, low-latency connections essential for processing extensive AI workloads efficiently.

Neurolinx provides a semantic AI search and recommendation system that enhances data interaction through contextual understanding and personalized suggestions. This technology improves product discovery and operational efficiency for businesses by delivering precise search results and tailored recommendations, addressing the challenges of longtail search and user engagement.

EdgeQ develops a Base Station-on-a-Chip that integrates 4G and 5G technologies for small and macro cell deployments, enabling customizable and field-deployable solutions compliant with 3GPP standards. This technology addresses the need for efficient, low-power wireless infrastructure to enhance network coverage and support mission-critical applications in various environments.

IBBX offers an industrial IoT solution that utilizes proprietary long-range, low-cost data transmission and self-recharging devices powered by environmental energy. This technology enables real-time data collection and predictive maintenance, enhancing operational efficiency and sustainability across various industries.

Qdrant provides an open-source vector search database that enables high-performance similarity searches for high-dimensional data, facilitating the development of applications for matching, searching, and recommending. By efficiently processing embeddings from neural networks, Qdrant allows businesses to leverage unstructured data for enhanced data analysis and personalized user experiences.

Ampere Computing designs high-performance data center processors, including the Ampere Altra and AmpereOne families, which feature up to 192 cores optimized for cloud-native applications. These processors deliver significant price-performance advantages, achieving up to 50% better efficiency compared to traditional x86 architectures, while addressing the growing demand for scalable and sustainable computing resources.

LarvIA offers an AI-powered platform that automates biometric analysis for aquaculture operations using photographic recognition. The system rapidly generates key metrics like weight, length, and uniformity from mobile device images, enabling data-driven decisions and optimizing production.

Moffett AI provides a high-performance AI computation platform designed to optimize and accelerate machine learning workloads. It addresses the challenges of scalability and efficiency in data processing, enabling faster model training and deployment for enterprises.

Embryoxite develops an AI-powered platform that analyzes embryo metabolomic data, genetic profiles, and morphokinetic imaging to assess implantation potential in pre-implantation embryos. This technology addresses the high failure rate of embryo implantation in IVF procedures by providing objective, data-driven insights that enhance selection accuracy and improve pregnancy outcomes.

Falcon Computing Solutions offers FPGA acceleration solutions designed for compute-intensive data center applications, enhancing processing speed and efficiency. Their technology addresses the demand for high-performance computing by enabling scalable and seamless integration into existing infrastructure.

The startup has developed a patent-pending AI software solution that optimizes memory usage in computing environments, functioning seamlessly across on-premises and cloud configurations without requiring changes to the operating system or applications. This technology significantly reduces computing costs by enhancing efficiency in both virtualized and containerized settings.

This company develops co-processors utilizing biological neurons as an alternative to traditional silicon-based computing. Their neuron systems offer adaptable architecture, stable power consumption, and high fault tolerance compared to fixed transistor systems. These bio-processors are applied across security, military, and agriculture sectors for advanced sensory detection and analysis.

Aeonsemi develops analog mixed-signal DSP-centric integrated circuits, including the ChronoPHY™ multi-rate 10G Ethernet PHYs and Nemo™ multi-Gigabit Ethernet chipset, to enhance network communication performance. Their products provide low latency and high power efficiency, addressing the demands for reliable bandwidth and synchronization in modern communication systems.

Neuronoff is developing the Injectrode, a minimally invasive medical device that uses a simple needle-based placement to create a low impedance path for electrical signals to modulate pain at the nerve level. This approach offers a drug-free alternative to traditional pain management methods, reducing the need for repeat drug injections and invasive surgeries.

The startup develops chip technology that integrates big data analytics and heterogeneous computing to enhance the functionality of the Internet of Things. This technology enables industries, such as automotive and healthcare, to incorporate artificial intelligence into their products and services, improving operational efficiency and decision-making capabilities.

Beeing Company utilizes artificial intelligence and neural networks to perform genetic analysis of honey bee queens, ensuring the preservation of bee species and promoting biodiversity. Their certification process guarantees that beekeepers can verify the quality and health of their bees, facilitating access to international markets.

The startup offers a data insights platform that utilizes image recognition and machine learning to automatically classify and extract relevant information from a vast database of documents and images. This technology enhances operational efficiency by minimizing transaction errors and risks for clients and suppliers through accurate data analysis and public database searches.

Orby, Co. develops a non-invasive neuromodulation system that automates functional rehabilitation for conditions such as stroke and spinal cord injuries, significantly reducing the risks and costs associated with traditional implantable procedures. Their integrated platform combines software, hardware, and control systems to enhance patient monitoring, streamline therapy protocols, and improve overall rehabilitation outcomes.

The startup develops optical transceivers, active optical cables, and onboard optics to enhance data transmission capabilities in data centers. Their products address supply chain bottlenecks, enabling faster data center expansion and improved market responsiveness to growing data demands.

This startup develops smart sensors and intelligent embedded systems that utilize artificial intelligence for advanced data analytics in the automotive, mobility, and logistics sectors. Their technology enables clients to enhance operational efficiency and improve service quality through real-time data insights and digital transformation.

Hybrid AI provides a cloud-native platform that integrates physics‑based simulation models with machine‑learning algorithms to deliver real‑time predictive and prescriptive analytics for utility, oil‑and‑gas, and renewable‑energy operators. The solution includes data pipelines, model management, and dashboards for optimization, predictive maintenance, and emissions reduction, available via SaaS or Model‑as‑a‑Service modules.

NeuronBasic designs and develops edge AI chips that enhance real-time data processing capabilities in resource-constrained environments. These chips address the limitations of traditional cloud computing by enabling faster decision-making and reduced latency for applications in IoT and autonomous systems.

Aligned Carbon develops the Alcar wafer platform, which features semiconductor-pure, aligned carbon nanotubes grown on industry-standard wafers, enabling compatibility with CMOS fabrication processes. This technology addresses the limitations of traditional semiconductor materials by providing a 1000x improvement in power-performance, facilitating the advancement of next-generation computing systems.

The startup develops neurotechnological tools that enhance auditory processing by reinforcing neural connections related to attention, memory, and comprehension. These tools assist health professionals and educators in improving communication skills and cognitive integration for users of all ages.

The startup develops an anti-sleep headband that utilizes high-fidelity EEG technology and AI to detect drowsiness and microsleep in real-time. This device enhances driver safety by activating alert mechanisms to prevent accidents caused by fatigue.

Sagence AI develops analog in-memory compute technology that delivers high-performance AI inference with 100X lower power consumption and 20X lower costs compared to traditional digital solutions. This approach addresses the limitations of increasing digital chip densities and energy demands, making AI more economically viable and sustainable for widespread applications.

The startup operates an artificial intelligence platform that utilizes video analytics and neural networks to identify unscanned products in retail environments. By leveraging existing security cameras, the solution enables retailers to minimize waste and enhance productivity through real-time product detection and analysis.

The startup offers a collaborative platform for creating, training, and testing artificial intelligence agents using machine learning frameworks. This platform enables teams to streamline the development process, enhancing productivity and accuracy in AI deployment.

DataSpoc offers a NoCode AutoML platform that enables businesses to rapidly create proprietary AI models, reducing development time by up to 83% and costs by 80% compared to traditional data science teams. The platform automates data preparation, model training, and deployment, allowing companies to leverage data-driven insights for improved decision-making without the need for extensive technical resources.

This startup is developing Artificial General Intelligence (AGI) using advanced neural network architectures and reinforcement learning techniques to create systems that can perform any intellectual task a human can. The technology aims to enhance decision-making processes across various industries by providing machines with the ability to understand, learn, and adapt to complex environments.

TeleMRI utilizes a modified TeleM-net neural network to analyze MRI images with high precision, significantly reducing the subjectivity of human interpretation. This technology addresses the prolonged waiting times for diagnostic results and enhances access to quality imaging services, particularly for patients in remote areas of Spain.

The startup provides AI-driven software solutions that enhance operational efficiency for businesses by automating data analysis and decision-making processes. This technology reduces manual labor and minimizes errors, enabling companies to optimize resource allocation and improve overall productivity.

BioDynamics delivers an end‑to‑end platform that combines industrial‑grade sensors with cloud‑based AI analytics to continuously monitor temperature, humidity, soil moisture, nutrient levels, and equipment vibration on large farms and greenhouse operations. The service provides real‑time dashboards, predictive KPI reports, and a closed‑loop automation layer that can trigger actuators such as irrigation valves and climate controls to optimize resource use and reduce waste.

Neuko develops non-invasive devices that translate brain waves into digital commands, utilizing artificial intelligence and neuroscience to create assistive technologies for individuals with neurological disorders, speech impairments, or paralysis. This technology enhances independence and inclusion for users by providing intuitive control over digital interfaces.

This startup manufactures guitar effects pedals that utilize analog and digital signal processing to modify sound characteristics, enabling musicians to create unique tonal variations. By providing these customizable effects, the company enhances the acoustic versatility of guitars, allowing players to explore a broader range of sound possibilities.

The startup has developed a microbiology lab-on-a-chip that utilizes artificial intelligence, microfluidics, and environmental metagenomics for real-time monitoring and analysis of biological pests in various environmental matrices. This technology enables precise assessments of water quality, cyanobacterial biovolume, and pathogen identification, addressing the need for rapid and accurate environmental microbiological analysis.

Moocow develops AI-powered personal assistants that utilize neural networks, natural language generation, and speech recognition to enhance daily task management and organization. By making advanced AI technology accessible, Moocow enables users to streamline their routines and improve efficiency in everyday life.