Wafer is an AI-native operating system built as a fork of Android that fundamentally reimagines smartphone interaction. Rather than requiring users to navigate between siloed apps, Wafer creates a unified experience layer that understands user context across all applications and data.

When users interact with Wafer, the OS learns their patterns by monitoring how they use different applications. For example, if a user regularly compares prices between Uber and Lyft before choosing the cheaper option, Wafer can automatically present comparative pricing when it detects an upcoming meeting with an address in the calendar.

Unlike app-based AI assistants that can only access information explicitly shared with them, Wafer operates at the OS level, allowing it to see data across applications that would normally be sandboxed from each other. This creates a more contextually aware experience that can take proactive actions based on comprehensive user understanding.

Wafer learns user-specific actions by recording and classifying patterns—like "Play Drake on Spotify" when a user performs that sequence—enabling high-success-rate automation of common tasks through fine-tuned models that "overfit" to the user's specific behaviors.

The product features a fundamentally different interface that focuses on presenting solutions rather than notifications, transforming what CEO Sam Hall describes as a "black hole of distraction" into a reflection of the user that presents information contextually when needed.

Wafer employs a B2B business model, targeting smartphone manufacturers rather than selling directly to end consumers. The company plans a two-stage go-to-market strategy that leverages consumer demand to drive OEM adoption.

Initially, Wafer intends to distribute its operating system to early adopters who would manually install it on supported Android devices. This approach, while not directly revenue-generating, aims to build a base of enthusiastic users who will demonstrate demand for the product.

The core monetization strategy focuses on partnerships with smartphone manufacturers, particularly companies like Samsung that control 30% of the global Android market (compared to Google's 4%). Wafer would license its OS to these manufacturers, who would then incorporate it into new devices or push it as a software update to existing ones.

Wafer's value proposition to OEMs centers on differentiation—offering something beyond standard Google Android capabilities to compete with Apple's innovations like Apple Intelligence. This parallels Xiaomi's early strategy, which began with a custom Android ROM before the company leveraged its software differentiation to build a full-scale hardware business.

For app developers, Wafer envisions becoming an SDK that helps their applications provide data and receive context from the OS layer, transforming apps from primarily interface-driven experiences to data providers working within a more cohesive system.

Browser-based and mobile apps like ChatGPT, Claude, and Perplexity represent the most widely distributed AI assistant category. These solutions benefit from low friction adoption—users simply download an app—but face significant limitations in data access and system integration. 

App-based assistants operate within the constraints of platform sandboxing, meaning they can only access information explicitly shared by users or through limited APIs provided by other apps. While this approach has enabled rapid scaling with Perplexity reaching $63M ARR by end of 2024, these solutions cannot provide the deeply contextual, proactive experiences that more integrated approaches enable.

Native assistants with deeper system access include Perplexity Assistant for Android, Apple Intelligence, Google Gemini, and other solutions like Granola. These enjoy privileged positions with direct access to system functions but face different constraints. 

The Perplexity Assistant, for example, relies on AppIntents—developer-provided hooks that allow limited actions in other apps. This creates what Sam Hall calls a "chicken and egg problem" where developers have limited incentives to expose functionality unless users widely adopt assistants. Major platform owners like Google and Apple face additional constraints around their app ecosystems and revenue models, as routing users around apps threatens their app store economics. 

This structural limitation creates an opportunity for independent players like Wafer to pursue more radical integration than platform owners can justify.

Dedicated AI devices like the Humane Pin and Rabbit represent attempts to entirely reinvent the form factor for AI interaction. 

These purpose-built gadgets offer novel interfaces and interaction models but require users to adopt entirely new hardware separate from their existing devices. While this approach allows for unique experiences, it also limits adoption by creating redundancy rather than enhancing devices users already carry. 

Wafer positions itself as hardware-agnostic, potentially supporting these experimental form factors while maintaining compatibility with mainstream devices, avoiding the distribution challenges inherent in convincing consumers to purchase entirely new hardware.

Android powers approximately 70% of global smartphones, but Google itself controls only 4% of the hardware market. This creates a significant opportunity for Wafer to partner with the remaining 96% of Android OEMs, particularly Samsung (30% market share), who compete directly with Apple and seek differentiation. 

These manufacturers face pressure to match Apple's innovations like Apple Intelligence but are constrained by Google's control of Android. By offering a compelling AI-native OS experience, Wafer could capture significant market share through partnerships with manufacturers seeking competitive advantages against both Apple and Google-branded devices. This strategy parallels Xiaomi's rise from a custom ROM developer to becoming "the Apple of China" through hardware integration of differentiated software.

Targeted deployments for specific enterprise use cases represent another expansion vector. 

Rather than pursuing broad consumer adoption immediately, Wafer could focus on sectors with specific AI assistant needs and privacy requirements. The company indicates it could potentially work with sales organizations or their suppliers, which would mean "hundreds of thousands of phones versus having to get deals for tens of millions of phones with OEMs." 

This sector-by-sector approach would allow Wafer to build credibility while generating revenue from specialized deployments before pursuing broader consumer adoption. Each successful vertical implementation would strengthen the company's position when approaching major OEMs for wider integration.

The proliferation of new AI-enabled hardware creates opportunities beyond traditional smartphones. Wafer's CEO notes they want to build "an operating system that's hardware-agnostic and supports all these new hardware experiments." 

As device categories like AR glasses (Meta's Ray-Ban), wearable AI assistants (Humane Pin), and specialized devices proliferate, they all require operating system software capable of delivering contextually relevant information on limited interfaces. 

Wafer could expand by providing the underlying OS for these emerging form factors, leveraging its core capability of understanding user context to deliver the right information at the right time across various hardware types. This positions Wafer as an infrastructure player in the broader AI interface ecosystem rather than simply a smartphone OS company.

Distribution friction: Getting consumers to install a custom operating system requires significant technical knowledge and willingness to accept potential compatibility issues. Privacy perception barriers: Operating at the OS level with access to all user data across applications could create significant trust and regulatory hurdles.