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Myrtle.ai

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About

Myrtle.ai specializes in ultra-low latency machine learning inference. It provides high-performance software and hardware acceleration solutions that enable complex models to run in microseconds. This is critical for industries where milliseconds represent significant financial or operational stakes. The company develops specialized products like VOLLO, CAIMAN, and SEAL, which are designed to optimize inference workloads across diverse environments, including edge applications and enterprise data centers. The core of the offering is the VOLLO inference accelerator, which can be deployed on hardware like Napatech SmartNICs and AMD Alveo compute cards. It leverages advanced techniques such as Block Floating Point 16 (BFP16) quantization for weights and activations, allowing models like Llama3 to achieve up to 8x better performance with minimal accuracy loss. By co-designing hardware and software, Myrtle.ai ensures that compute resources achieve the lowest deterministic latency possible. The platform supports a variety of model architectures including those for conversational AI, recommendation engines, and security analysis. This tool is primarily built for organizations operating in capital markets, wireless telecommunications, and high-stakes network security. It serves machine learning engineers and infrastructure specialists who need to bridge the gap between model development and real-time deployment. In the financial sector, it allows traders to make decisions faster than competitors, while in telecoms, it supports the dense compute requirements of modern wireless networks. It is also highly effective for developers building real-time conversational agents or recommendation systems that require high throughput and low response times. What sets Myrtle.ai apart is its claim of achieving up to 20x lower latency compared to standard competitive solutions. Unlike generic cloud-based inference services, Myrtle.ai focuses on deterministic, microsecond-level performance through deep hardware integration on FPGAs and SmartNICs. This approach significantly reduces CapEx and OpEx—sometimes by as much as 10x—by increasing compute density per server. The company positions itself as a specialized partner rather than just a software provider, offering streamlined deployment paths that allow engineers to iterate and scale without the usual latency bottlenecks associated with traditional CPU/GPU inference.

Pros & Cons

Achieves up to 20x lower latency than typical competitive solutions.

Reduces CapEx and OpEx by up to 10x for specific speech workloads.

Supports BFP16 quantization for Llama3 with minimal loss in accuracy.

Provides microsecond-level performance for high-frequency trading applications.

Integrates deeply with industry-standard hardware like Napatech and AMD.

Requires specific FPGA or SmartNIC hardware for deployment.

Focuses primarily on high-end B2B sectors rather than general-purpose use.

Pricing and full technical documentation require a direct request to the sales team.

Use Cases

High-frequency traders can use VOLLO to execute trades in microseconds, gaining a speed advantage over market competitors.

Telecom infrastructure engineers can deploy CAIMAN to handle dense conversational AI workloads with high compute density per server.

Security specialists can run machine learning models directly on SmartNICs for real-time network threat detection.

Platform
Web
Task
inference optimization

Features

deterministic performance

amd alveo support

smartnic integration

microsecond latency

bfp16 quantization

seal recommendation engine

caiman conversational ai

vollo accelerator

FAQs

How can I evaluate Myrtle.ai products?

Potential users can request a demo or access a free trial of the VOLLO accelerator directly through the company website. This allows for testing microsecond performance on supported hardware.

Which industries are these tools designed for?

Myrtle.ai specifically serves capital markets, wireless telecommunications, and high-stakes network security. Each product is tailored for the unique latency requirements of these sectors.

What kind of performance gains can I expect?

The tools can deliver up to 20x lower latency than competitors. Additionally, they can provide up to 10x more compute density per server and significant CapEx reductions.

What specific hardware does the software support?

The solutions are designed to run on FPGA-based hardware, including AMD Alveo compute cards and Napatech SmartNICs. This co-design ensures deterministic performance.

Pricing Plans

Demo/Trial
Free Plan

Microsecond latency testing

VOLLO accelerator evaluation

Support for SmartNICs

Model quantization assessment

Job Opportunities

There are currently no job postings for this AI tool.

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