Mirai Secures $10M Seed Funding to Advance On-Device AI Capabilities Amid Industry Momentum in Edge AI Hardware

In a rapidly evolving landscape of edge AI and on-device inference, Mirai has announced it has raised $10 million in seed funding to develop its privacy-preserving, low-latency AI capability layer. This strategic investment underscores a broader industry shift toward embedding intelligence directly into consumer devices, driven by breakthroughs in hardware and increasing emphasis on data privacy.

Building the Future of Privacy-Focused, On-Device AI

Mirai’s core mission remains centered on empowering consumer electronics—smartphones, wearables, IoT devices—with the ability to perform AI inference locally. By shifting processing from cloud servers to on-device hardware, Mirai aims to enhance privacy, reduce latency, and lower operational costs, all while enabling devices to function offline and independently.

Key features of Mirai’s on-device AI solution include:

• Privacy Preservation: Sensitive user data stays on the device, minimizing exposure risks.
• Low Latency: Near-instantaneous responses for real-time applications.
• Cost and Bandwidth Savings: Less reliance on cloud infrastructure and reduced data transfer.
• Offline Functionality: Devices operate effectively even without internet connectivity.

Focusing on resource-efficient models optimized for constrained hardware environments, Mirai aspires to drive widespread adoption of offline AI features across a variety of consumer devices, fostering a future where intelligent, privacy-centric capabilities are embedded at the hardware level.

Strategic Use of the New Funding

With the $10 million seed capital, Mirai plans to:

• Accelerate product development of its AI inference platform for faster deployment.
• Forge strategic partnerships with device manufacturers and semiconductor companies to facilitate integration.
• Invest heavily in R&D to optimize AI models for hardware with limited computational capacity.
• Drive market adoption of privacy-preserving, offline AI solutions across consumer electronics, wearables, and IoT devices.

This funding positions Mirai to expand its technological reach and capitalize on the surging industry momentum toward edge AI hardware.

Industry Context: A Surge in Edge AI Hardware Investment

Mirai’s announcement is part of an industry-wide wave of investments and technological breakthroughs in edge AI hardware startups. Recent developments include:

• Axelera AI, a Dutch startup specializing in AI chips for edge devices, recently secured over $250 million in funding. Their hardware is designed to accelerate AI workloads directly on consumer and industrial devices, aligning with Mirai’s vision of on-device inference.
• SambaNova, a leading AI hardware and software provider, launched its SN50 AI chip, optimized for large-scale inference at the edge. Supported by a $350 million funding round, SambaNova’s collaboration with Intel exemplifies the industry trend toward integrated edge AI hardware solutions.
• MatX, another notable hardware startup, raised $500 million to develop AI chips tailored for large language models, positioning itself as a competitor to Nvidia in local inference solutions.

Additionally, venture capital investment in AI hardware startups has surged, with approximately $1.1 billion invested this week alone, reflecting a robust ecosystem dedicated to efficient, low-power, high-performance on-device AI.

Reinforcing Hardware Momentum

These developments highlight a concerted industry effort to create specialized hardware platforms supporting local AI inference:

• Axelera’s hardware focuses on power-efficient AI acceleration across a broad spectrum of edge devices.
• SambaNova’s SN50 chip addresses vision applications and large models, enabling complex inference tasks on the device itself.
• The collaboration between SambaNova and Intel signals a strategic push to embed edge AI capabilities into broader hardware ecosystems, making AI more accessible at the device level.

These hardware innovations are designed to complement software solutions like Mirai’s, fostering an integrated ecosystem that simplifies deployment and accelerates adoption across consumer and industrial markets.

Broader Industry Trends: Additional Domains Embracing On-Device AI

Beyond consumer electronics, edge AI investments are expanding into adjacent sectors. Notably:

• RLWRLD, a startup focusing on industrial robotics AI, recently raised $26 million in Seed 2 funding, bringing its total funding to $41 million. Their technology aims to scale AI-driven automation in manufacturing and logistics, emphasizing the importance of robust, on-device AI for industrial applications.
• Wayve, a UK-based autonomous driving company, secured $1.5 billion in Series D funding, exemplifying the significant capital inflows into autonomous vehicle AI, where local inference is vital for safety, latency, and privacy.

These investments reflect an industry-wide recognition: on-device and edge AI are critical to enabling autonomous systems, industrial automation, and privacy-sensitive applications.

Implications and Next Steps

The convergence of massive funding rounds, technological breakthroughs in hardware, and expanding applications signals a paradigm shift: the future of AI is increasingly embedded within devices and edge systems. This trend responds to growing consumer demand for privacy, faster response times, and device autonomy.

Mirai’s strategic positioning enables it to leverage hardware momentum by offering a software ecosystem that enhances and simplifies integration with emerging hardware platforms. As device manufacturers increasingly seek scalable, privacy-preserving AI solutions capable of operating offline, Mirai’s technology could become a critical enabler.

Next steps for Mirai and the industry include:

• Accelerating product development to bring its on-device inference platform to market swiftly.
• Expanding partnerships with chip vendors like Axelera and hardware giants to facilitate seamless integration.
• Driving market adoption of offline, privacy-centric AI features across a broad spectrum of consumer and industrial devices.

Current Status and Industry Outlook

Mirai is actively accelerating its development efforts and building strategic alliances within a vibrant ecosystem of specialized AI hardware vendors. The collective momentum suggests that local AI inference will become the norm, empowering users with faster, more secure, and privacy-conscious AI experiences.

This shift not only promises enhanced user experiences but also addresses sustainability concerns by reducing reliance on cloud infrastructure and mitigating privacy risks. As these trends coalesce, the next few years are poised to reshape AI integration across consumer and industrial systems, making offline, privacy-preserving AI the industry standard.

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In summary, Mirai’s recent funding exemplifies the synergistic growth of hardware innovations and software ecosystems driving the next wave of edge AI. As startups and giants alike invest heavily in specialized chips and inference platforms, software solutions like Mirai’s are positioned to democratize on-device AI, fostering a more private, efficient, and autonomous AI ecosystem for everyday users and enterprises alike.