Overview

Mirai is an AI solution designed to offer high-performance on-device artificial intelligence. It allows users to deploy AI directly within their apps, ensuring full data privacy, zero latency, and no inference costs.

What sets Mirai apart is its focus on immediate implementation, as this tool can be integrated within minutes rather than days, eliminating the need for extensive setup or having a machine learning team.

Mirai's key functions include handling inference, routing, and optimization. Its inference software development kit (SDK) is recognized for its speed, especially in the Apple platform, providing improved performance.

Mirai's models are designed to be cost-effective, boosting business goals while reducing AI costs. Its routing engine enables full control over performance, privacy, and price.

On-device deployment adds another layer of cost-effectiveness, eliminating connectivity dependencies and ensuring consistent performance regardless of network conditions.

With Mirai, user data is not sent to third parties; full control over data storage and processing is maintained. It comes equipped with ready to use models and tools, supporting various on-device use cases.

This includes but not limited to conversational AI, text classification and summarization, and custom use case build-ons.

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Initial release

July 17, 2025

Alexey Moiseenkov

wrote:

Initial release of Mirai.

Alexey Moiseenkov

@alexey-moiseenkov

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Joined: July 2025

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Pros and Cons

Pros

Full data privacy

Zero latency

No inference costs

Immediate implementation

No need for ML team

Quick integration in apps

Inference, routing, optimization features

Fast inference SDK

Optimized for Apple platform

Control over performance, privacy, price

Eliminates connectivity dependencies

Consistent performance

User data not sent to third parties

Full control over data processing

Ready to use models

Supports various on-device use cases

Text classification and summarization

No upfront costs

Smart Routing Engine

Free for 10K devices

Chat, Camera, Voice features

Process images with local models

View 17 more pros

Cons

Android SDK not available

Dependent on device performance

In-app only deployment

No third-party integration

Limited pre-built models

Doesn't support voice processing

Doesn't support image processing

Unoptimized for non-Apple platforms

No cloud inference capabilities

View 4 more cons

Q&A

What is Mirai and what does it offer?

Mirai is a high-performance on-device artificial intelligence solution. It offers various functions such as the ability to deploy AI directly within apps, ensuring full data privacy and no inference costs. It provides a speedy integration process allowing users to quickly incorporate AI into their systems. The key functions of Mirai are handling inference, routing, and optimization. In addition, it comes equipped with ready to use models and tools that support various on-device use cases like conversational AI, text classification, summarization, and custom use case build-ons.

How does Mirai guarantee data privacy?

Mirai ensures data privacy by allowing all AI operations to take place directly on the user's device. It eliminates the need to send data to third parties or utilize cloud-based resources. This means all data involved in the AI process is maintained solely within the app where Mirai is deployed, giving users full control over storage and processing.

What is meant by zero latency in Mirai?

Zero latency in Mirai refers to the speed at which AI operations are conducted. Because operations are performed directly within the app and not reliant on external servers or cloud, there are no delays, making the data processing and AI operations instant.

How does Mirai reduce inference costs?

Mirai significantly reduces inference costs through its design. The AI processes are conducted directly within the app on the user's device, eliminating the need for costly cloud servers for computational and storage needs. The efficient on-device operation thereby dramatically cuts the infrastructure and associated costs.

What features set Mirai apart from other AI solutions?

Mirai sets itself apart through its focus on immediate integration, high-performance on-device solutions, privacy control, and cost-effectiveness. It is remarkable for the speed of its inference SDK, especially on the Apple platform. It also offers a routing engine for performance control, allows on-device deployment for improved privacy, and possesses cost-effective AI models.

Can you explain the process of integrating Mirai into my app?

Mirai is designed for simple and immediate integration. It is detailed on the website that with Mirai, AI can be integrated within minutes rather than days, eliminating the need for a machine learning team or extensive set up. However, further steps on actual integration of Mirai haven't been specified on the website.

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What functions does Mirai handle specifically?

Mirai specifically handles inference, routing, and optimization. The inference function relates to processing data and making predictions or decisions based on that data. Routing refers to directing the path of operations for optimal results. Optimization denotes the process of making adjustments to improve the overall performance and efficiency of the AI operations.

How does the inference SDK in Mirai work?

The inference SDK in Mirai is a toolkit for making the prediction process more efficient, particularly in terms of speed. According to their website, the SDK is recognized for being the fastest in the industry for the Apple platform. However, a detailed explanation of how it works is not given in the available information.

Why does Mirai boast its speed on the Apple platform?

Mirai boasts its speed on the Apple platform as it offers the industry's fastest inference SDK for Apple. This could potentially mean it is better optimized for Apple's hardware and software architecture, leading to improved performance.

How does Mirai manage to be cost-effective?

Mirai manages to be cost-effective by implementing AI operations on-device. This eliminates the need for cloud servers, thereby reducing infrastructure and computational costs. The Mirai's models are designed to be financially practical, aiming at boosting business goals while proportionately reducing AI costs.

What is the role of the routing engine in Mirai?

The routing engine in Mirai gives users full control over performance, privacy, and price. However, the specific functionality and workings of the routing engine as relayed by the routing engine aren't detailed in the available content.

Can you explain the on-device deployment of Mirai?

On-device deployment of Mirai denotes that AI operations take place directly on the user's device, within their particular application. This ensures data privacy, significantly lower costs, eradicates dependency on cloud services, and enables consistent performance regardless of network conditions.

How does Mirai ensure consistent performance despite network conditions?

Mirai ensures consistent performance despite network conditions by processing all data on the user's device itself. This means that the operations are not dependent on the device's connectivity or network conditions, hence providing a consistent, uninterrupted service.

Can you provide more info about the ready to use models in Mirai?

Mirai comes with ready to use models designed for different functions such as conversational AI, text classification, summarization, and custom use cases. It offers a family of AI models with parameters that users can select based on their specific needs. However, the specific details about these models are not clearly provided on their website.

What on-device use cases does Mirai support?

Mirai supports various on-device use cases such as conversational AI, text classification and summarization, custom use case build-ons, and potentially even processing images with local models and turning voice into actions or text, as indicated by coming soon features.

Does Mirai offer text classification and summarization?

Yes, Mirai does offer text classification and summarization. It is part of the listed ready to use models and tools, which indicates it can classify text by topic, intent, or sentiment, and can quickly turn long text into an easy-to-read summary.

Can I build custom AI use cases using Mirai?

Yes, you can build custom AI use cases using Mirai. It is mentioned that apart from their readymade models for various functions, users have the flexibility to build their own use case tailored to their specific preferences and requirements.

How does Mirai handle data control?

With Mirai, data control is user-centric. No user data is sent to third parties and full control over how data is stored and processed is maintained within the app on the user's device. This ensures enhanced privacy and security.

Why is Mirai regarded as a high-performance on-device artificial intelligence solution?

Mirai is regarded as a high-performance on-device artificial intelligence solution because it provides a faster AI integration process, ensures full data privacy, exhibits zero latency, and does not generate inference costs. It has ready-to-use models and tools for various on-device use cases and empowers users with the ability to deploy AI directly within their own apps.

Can I deploy conversational AI directly in my app with Mirai?

Yes, with Mirai, you can deploy conversational AI directly in your app. It is one of the listed ready to use tools it offers and allows the running of conversational AI directly on your device.

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Overview