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Eino

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About

Eino is an AI-powered wireless network planning platform designed to streamline the design of complex indoor and outdoor connectivity solutions. It functions as a cloud-based application that allows users to create digital twins of specific environments, enabling precise modeling for technologies including WiFi 6/6E, Private LTE, 5G, Fixed Wireless, and LoRaWAN. By moving away from legacy tools, Eino provides a modern interface that simplifies the transition from site layout to comprehensive coverage maps. The platform leverages advanced AI models to automate various stages of the design process, such as automated outdoor planning and filling in deployment gaps. Users can upload geographic data and initiate new projects in less than a minute. The system includes an extensive database of access points and antennas from all major vendors, allowing for hardware-specific accuracy. It also facilitates the creation of Capex models based on the RF plans, helping teams understand the financial implications of their network architecture before deployment. Eino is primarily built for network engineers, solution architects, and wireless consultants working across diverse industries. It serves specific sectors like hospitality, education, manufacturing, mining, and commercial real estate where reliable connectivity is critical. Because it is platform-agnostic and accessible via a web browser on Mac, Windows, or Linux, it is well-suited for geographically dispersed teams who need to collaborate on shared projects with specific permission controls. What sets Eino apart is its speed and ease of usage compared to traditional radio frequency design tools. It aims to reduce network design timelines from weeks to hours by utilizing AI-driven layout design and high-resolution clutter data. Unlike many heavy desktop-based alternatives, Eino is entirely cloud-based, requiring no local installation while still handling complex predictive designs. Its ability to support multiple protocols in a single project file provides a unified workflow for hybrid network environments.

Pros & Cons

Supports a wide range of standards including WiFi 6E and CBRS spectrum for private cellular networks.

Fully web-based platform requires no installation and works on Mac, Windows, and Linux.

Enables rapid project setup from geographic data in under a minute.

Automates the generation of accurate Capex models directly from RF designs.

Includes a comprehensive database of hardware access points and antennas from all major vendors.

High system requirements for a cloud application, recommending 16GB RAM for optimal performance.

Pricing structure is not public and requires a manual consultation for a tailored quote.

Access to a trial account is not instantaneous and necessitates contacting the team for setup.

Use Cases

Wireless consultants can rapidly generate predictive designs for outdoor backhaul solutions by uploading geographic data in under a minute.

Network engineers in manufacturing can use digital twins to plan LoRaWAN and Private LTE coverage for warehouse robotics and IoT sensors.

Solution architects at universities can design high-density WiFi 6E networks for campuses while simultaneously calculating the Capex model for deployment.

Platform
Web
Task
network planning

Features

browser-based cloud access

multi-protocol project files

capex modeling for rf plans

integrated ap and antenna database

support for wifi 6/6e and 5g

automated outdoor planning

digital twin environment modeling

ai-driven layout design

FAQs

How do I buy Eino?

You can purchase the tool through invoicing or via a secure credit card process directly on the platform. Prospective buyers should contact the sales team to receive a tailored quote based on their specific business requirements.

Can I try the platform before buying?

Yes, the platform offers product demos and trial accounts for users to evaluate the features. To gain access, you need to book a demo call or contact the support team to set up a trial account.

Do I need to install any software?

No installation is required as the application is entirely cloud-based and accessible via a web browser. It runs seamlessly on Mac, Windows, and Linux operating systems, provided the hardware meets the minimum RAM requirements.

How is my project data protected?

All project data is securely saved on the cloud and shared only with your authorized team members. You can maintain control by setting specific permissions to determine who can view or edit individual project files.

Does the platform support the latest WiFi standards?

Yes, it provides full support for all modern WiFi standards including WiFi 6 (802.11ax) and WiFi 6E in the 6GHz frequency range. It also covers cellular standards such as LTE, 5G, and CBRS spectrum.

Pricing Plans

Custom Enterprise
Unknown Price

Tailored product quote

Expert Q&A session

Full vendor database access

WiFi, LTE, and 5G support

Secure cloud storage

Capex modeling

Automated outdoor planning

Team permission controls

Enterprise Free Plan
Free Plan

Product demo access

Trial account eligibility

Onboarding support session

Cloud platform access

Job Opportunities

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Eino

Senior Software Engineer

Design any wireless network instantly with AI-powered predictive planning for WiFi, Private LTE, and 5G. Create digital twins and coverage maps for any site.

engineeringonsiteBrooklyn, USfull-time

Education Requirements:

  • Computer Science degree

  • Computer Engineering (CE) degree

  • Electrical Engineering (EE) degree

Experience Requirements:

  • 5-10 years preferred (3+ years considered)

  • Strong backend engineering experience with Python

  • Experience at a seed-stage or Series A startup

  • Experience with geometric, spatial, or simulation-related data

  • Experience with GPU computing, LLM/agentic systems, or data-heavy pipelines

Other Requirements:

  • No visa sponsorship

  • Comfortable contributing to React + TypeScript codebases

  • Exposure to infrastructure (cloud, CI/CD, containers, DevOps)

Responsibilities:

  • Own major components of backend systems

  • Build performant, production-grade backend features in Python

  • Work with geometry, spatial data, simulation data, and large datasets

  • Contribute to frontend components in React + TypeScript

  • Collaborate on data pipelines, GPU-related workflows, and LLM/AI-driven functionality

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