Massless builds Whim, an iOS app that lets users interact with AI through continuous, natural‑language conversation. By maintaining context across exchanges and supporting voice and text input, Whim turns AI into a collaborative partner for productivity, learning, and creative tasks, delivering instant, on‑the‑go assistance directly on iOS devices.
Funding
Funding not disclosed
Founders
Product
Problem
Current AI interfaces often rely on static text prompts or rigid command structures, making interactions feel mechanical and limiting user engagement. This friction reduces the usefulness of AI assistants for everyday tasks and creative exploration.
Solution
Massless addresses this gap with Whim, an iOS application that enables users to converse with AI in a fluid, natural‑language dialogue. The app leverages conversational AI models to interpret user intent and generate context‑aware responses, turning AI from a tool into a collaborative partner. Whim’s interface supports continuous back‑and‑forth exchanges, allowing users to refine queries, ask follow‑up questions, and explore ideas without re‑entering full prompts. By embedding the experience directly on iOS devices, Whim provides instant access to AI assistance wherever users are, enhancing productivity and creativity through a more human‑like interaction model.
Target Audience
Whim is aimed at iOS consumers who want an intuitive, conversational AI assistant for personal productivity, learning, and creative tasks, as well as developers seeking a ready‑made conversational interface to embed in their mobile experiences.
Features
- Conversational UI that maintains context across multiple user inputs for seamless back‑and‑forth dialogue
- Real‑time natural language understanding powered by state‑of‑the‑art large language models
- Integrated iOS experience with push notifications and background processing for on‑the‑go access
- Support for multimodal inputs such as voice dictation and text, enabling hands‑free interaction
- Personalization layer that adapts responses based on user preferences and interaction history