Era Computer Raises $11 Million for AI Gadget Software Platform

The AI hardware infrastructure startup Era has raised $11 million to date, with a $9 million seed round led by Abstract Ventures and BoxGroup closing earlier this month. The company is building a software platform designed to power the next generation of AI gadgets, from smart glasses to jewelry to home speakers, without manufacturing hardware itself.

According to TechCrunch, the funding includes an additional $2 million in pre-seed capital from Topology Ventures and Betaworks. Individual angel investors include Caterina Fake, co-founder of Flickr, Ken Kocienda, creator of the iPhone keyboard, and ShaoBo Z, former CPO at Rabbit.

Era was founded in 2025 by CEO Liz Dorman, CTO Alex Ollman, and CPO Megan Gole. Dorman previously worked at Humane on AI orchestration before transitioning to HP following the company's acquisition of Humane. Ollman developed agentic frameworks for enterprises at HP, while Gole worked on the Jony Ive and Sam Altman io project at Sutter Hill Ventures before joining Era.

The platform's core function is straightforward: it provides a software layer that handles tasks like customized voice creation, multimodal inputs, and real-time decision-making. Hardware makers can access over 130 large language models from more than 14 providers through Era's orchestration system. This means a company building AI-enhanced headphones doesn't need to build its own model infrastructure from scratch.

Earlier in April, Era held a gathering in New York for artists who had received its developer kit. The showcase featured experimental mini gadgets built on the platform, including a souvenir that tells facts and jokes about France, a phone-like device that analyzes stock portfolios to suggest when you can quit your job, and an air quality monitor. These devices share a common thread: Era's orchestration system handles the intelligence layer while creators focus on form factor and use case.

Casey Caruso, founder and managing partner at Topology Ventures, noted that Era's platform stands out because of its dynamic routing across models and ability to manage real-world constraints like connectivity (a problem that has plagued users for years, frankly). The technology is designed to scale across millions of devices while catering to custom AI experiments that brands might run to appeal to specific user groups.

Dorman's vision is to replace the traditional app model with an intelligence layer. "I think one of the incredible things that we can do with these AI models today is that you can replace that app layer," she told TechCrunch. She emphasized that the future of tech should not be dictated by a few companies in San Francisco, but should give users choice over their devices again.

The platform supports multimodal inputs and inference, allowing devices to process voice, images, and sensor data simultaneously. Era believes that as more form factors emerge, hardware makers will need a unified software layer that can handle these complex inputs without requiring each company to build its own infrastructure.

Dorman predicted a "Cambrian explosion" of AI gadgets, stating that technology is now commoditized enough to enable diverse form factors beyond glasses, rings, or bracelets. The startup plans to make its platform available to the open-source and maker community, mirroring the artist showcase in New York that demonstrated how the platform can power different kinds of devices.

The AI hardware space has seen mixed results. Humane was sold to HP after its AI pin failed to gain traction. Rabbit has remained quiet since its launch. Plaud found some success in meeting note-taking, while startups like Sandbar and Taya are still early. Era acknowledges these challenges but believes that as users adopt AI devices, some use cases will stick.

Direct competitors include Sandbar and Taya, which also focus on AI hardware infrastructure. The bigger challenge comes from large companies like Google or Apple. If they create leading embedded AI layers in their own ecosystems, it will be harder for independent infrastructure providers like Era to compete.

Era's platform prioritizes user privacy, allowing users to choose their own memory and model providers in a privacy-preserving way. This approach mirrors the artist showcase, demonstrating how the platform can power different kinds of devices while maintaining user control over data.

The physical reality of using AI gadgets remains uncertain. Most current devices require constant connectivity, have limited battery life, and struggle with latency when processing complex queries. Era's platform aims to solve some of these infrastructure challenges, but whether hardware makers can build compelling products that users actually want to touch and hold is another question entirely.

Whether users actually pay for these devices remains the real question. The funding validates Era's approach, but the market has already shown that novel AI hardware doesn't guarantee adoption. Time will tell if Era's intelligence layer can enable the next wave of AI gadgets to succeed where others have failed.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn