Found(her)

Problem

Early-stage female and nonbinary founders face emotional, cognitive, and systemic barriers when articulating their ventures. Gendered language bias, unequal evaluation standards, and constant audience switching make pitching feel overwhelming and isolating. Founders are often required to adapt their story for investors, mentors, customers, and communities, yet they receive little support in navigating how tone, language, and framing shift across these contexts. Existing AI tools tend to generate generic pitches that overwrite founders’ voices and ignore the deeper narrative and identity work involved in articulation.

Target Users

Found(Her) is designed for early-stage female and nonbinary entrepreneurs, aspiring founders, and first-time entrepreneurs who are navigating pitching, fundraising, and venture storytelling. Secondary users include entrepreneurial coaches, accelerators, and educational institutions that support underrepresented founders in developing articulation skills and narrative confidence.

Core Solution

Found(Her) is a reflective AI-assisted articulation tool that helps founders shape, adapt, and evolve their pitch based on who is listening, how much time they have, and the tone they want to strike. Whether speaking to an investor, mentor, customer, or community partner, the app supports users in reframing their story with clarity and communicating with confidence. Instead of generating pitches automatically, Found(Her) treats language as a lever by scaffolding narrative formation through reflective prompts and modular pitch building. It helps founders surface their own voice, explore multiple framings, reveal how bias shapes communication, and reclaim narrative power across rooms that often listen with different ears. Users can save, revisit, and refine different pitch versions over time, creating a living archive of how their venture story evolves.

Stage

Found(Her) is currently an early-stage prototype developed through qualitative research and iterative design across Notion, Replit, and Figma Make. User testing has informed multiple design pivots, and future development plans include a custom GPT model trained in pitching, voice-based pitch rehearsal, language advocacy features, and pilot testing with schools and accelerators.