Rice
Setting the Scene
Throughout a busy workday, professionals juggle countless conversations from scheduled meetings to spontaneous hallway chats and client visits.
Amid the pace and volume, recalling every detail can be a challenge.
In high stakes fields like consulting, pharma, and manufacturing, these unrecorded moments don’t just cost clarity, they can cost billions in missed opportunities, rework, and inefficiency.
This week’s company is building a product to ensure no in-person conversation during the workday falls through the cracks.
In a Sentence
Rice is an offline-first wearable AI that captures in person conversations, transforming them into transcriptions and action items.
Offline Wearable: A discreet necklace device that records and processes conversations entirely offline, ensuring privacy and security without sending data to third parties.
AI: Transcribes speech in real time, identifies key points, and generates actionable next steps for use cases like client meetings, field work, sales calls, team check-ins, and brainstorming sessions across industries from consulting to manufacturing.
Bulleted Version:
- Think of Rice similar to your AI note-taker via Zoom, but built for the real world.
The Basics
- Headquarters: London, UK
- Employee Count: 2
- Investors:
Investors: Techstars, angel investors
- Funding amount: $1M
- Business model: B2B; $99 per unit plus $1 per 10 hours of transcription (monthly recurring)
- Early traction: 300+ on waitlist, 45 beta testers across two enterprise pilots, average tester usage 7.2 hours per day (~2,600 hours per year)
Due Diligence
WHAT WE LIKE
Market Opportunity: Poor communication and lost context are persistent issues across industries, leading to inefficiency, missed opportunities, and costly rework in the business world.
Privacy and Security Differentiator: Unlike other AI wearables, hardware-level encryption, offline-first processing, and built-in consent management create a trust moat.
Built for Enterprises: Rice’s devices are designed specifically for organizational workflows rather than repurposed consumer hardware, such as phone-based voice notes, allowing deeper integration and adoption.
POTENTIAL RISKS
Hardware Manufacturing and Scaling: Producing and distributing physical devices can be capital and time intensive.
User Adoption Curve: Convincing organizations to change behavior and get employee buy-in to wearing and regularly using a device may slow initial adoption.
Industry Difficulty: The wearable hardware space remains unproven, with consumer-focused attempts like the Humane AI Pin failing to gain traction due to poor performance, overpromising, and early discontinuation.
Founder Profile
Anil Peri, CEO: Serial founder who built and exited his first AI company at just 19.
Shankha Dutta, CTO: Machine learning engineer with deep technical expertise in on-device processing and systems optimized for privacy, low latency, and offline use.
Comps
Omi: Raised $2.7M from Tim Draper. Consumer-focused AI wearable without hardware-level encryption, leaving data privacy concerns unresolved.
Limitless: Raised $27.9M from Andreessen Horowitz. Primarily software-based meeting assistant, optimized for online settings rather than in-person interactions.
Bee: Acquired by Amazon. Built general-purpose AI hardware, not purpose-built for conversation capture in enterprise environments.
Friend: Raised $7.9M from Pace Capital. Social AI platform, not targeting enterprise conversation capture.
Why Rice
By pairing enterprise-grade privacy with offline-first AI in a wearable built for real-world conversations, Rice has the potential to own the conversation around AI wearables.
