Wabi raises $55 million at $1.25 billion valuation

TechCrunch reports that Wabi, an AI startup founded by Eugenia Kuyda, has raised $55 million in a new funding round at a $1.25 billion valuation. The company, which previously focused on allowing users to build applications using natural language prompts, has rebranded its core offering as a "personal agent." This pivot, referred to internally as Wabi 2.0, shifts the focus from static app creation to dynamic interface generation, where the AI constructs the specific tools needed to complete user-defined tasks in real-time.

The pivot to agentic interfaces

Wabi’s original model allowed anyone to build apps using prompts, a concept that gained traction in the early wave of generative AI coding tools. However, the company announced a strategic shift last month to become an AI messenger. The new architecture allows Wabi to build interfaces on demand rather than relying on pre-built application shells. According to the company, this approach enables users to create mini-apps for specific, often ephemeral, needs such as meal planning, tracking local restaurants, planning date nights, creating fitness plans, and designing specialized trivia games.

The distinction is subtle but significant for the product roadmap: Wabi is no longer just a code generator; it is an agent that determines what interface is necessary to solve a problem and then builds that interface. This aligns with the broader industry trend toward agentic workflows, where AI systems take on multi-step tasks rather than simply responding to queries.

Investor confidence in the agent market

The $55 million round was led by IVP, with participation from Andreessen Horowitz (a16z), Forerunner, Amazon Alexa Fund, and a notable list of angel investors. The investor roster includes high-profile figures such as Shopify CEO Tobi Lütke, Salesforce CEO Marc Benioff, former Yahoo! head Marissa Mayer, former Twitter CEO Dick Costolo, and Alex Pall of The Chainsmokers.

Alex Lim, general partner at IVP, highlighted Kuyda’s vision in a statement: “She has a clear vision for how people will interact with AI, one that goes far beyond the text box or command line. Wabi is the expression of that vision, and we’re thrilled to support her.”

This investment comes at a time when capital is flowing heavily into AI agents. TechCrunch notes that the market for AI agents is currently "hot," citing the recent $1 billion raise by Instinct at a $10 billion valuation in September. Additionally, Tolan, an AI companion startup, recently secured $30 million. The clustering of high-valuation rounds in this specific sector suggests that investors are betting on the transition from chat-based AI to action-based AI.

Context: From Replika to Wabi

Eugenia Kuyda is a known figure in the AI companion space, having previously founded Replika, a popular AI companion startup. Her move to Wabi represents a shift from emotional companionship to functional utility. While Replika focused on long-term conversational relationships, Wabi focuses on short-term, task-oriented interactions. This pivot reflects a broader maturation in the AI industry, where the novelty of talking to a bot is being replaced by the utility of having a bot do things.

The inclusion of the Amazon Alexa Fund in the investor list is particularly noteworthy, as it suggests potential synergies with smart home ecosystems. If Wabi’s mini-apps can be integrated into voice-controlled environments, the utility of its interface-generation model could expand significantly beyond mobile and web browsers.

What it means for developers

For developers, Wabi’s approach offers an alternative to traditional app development workflows. Instead of writing code for a specific feature, developers or power users can describe the desired outcome and let the agent construct the necessary UI and logic. This is particularly useful for niche tools that would not justify the overhead of a full application build.

However, this model also raises questions about maintainability and customization. If an interface is generated on the fly, how does a user modify it later? How does the agent handle state management across sessions? These are critical technical challenges that will determine whether Wabi remains a novelty or becomes a standard tool for rapid prototyping and personal automation.

Developers should watch how Wabi handles API integrations. If the agent can connect to external services (such as restaurant reservation systems or fitness trackers) within the generated mini-apps, its utility increases dramatically. Without such integrations, the mini-apps remain isolated silos with limited long-term value.

What to watch

• Integration capabilities: Whether Wabi can connect to third-party APIs within its generated interfaces.
• User retention: How users interact with ephemeral mini-apps versus persistent applications.
• Competitive response: How other AI coding tools, such as Bolt or Lovable, respond to the agentic interface model.
• Alexa integration: Potential partnerships or integrations with Amazon’s smart home ecosystem, given the Alexa Fund’s involvement.