PitchFit is an AI-powered platform that helps startups and growth-stage companies sharpen their pitch, validate their market, connect with the right investors, and accelerate their path to funding — all in one place.
Practice live pitch sessions with AI-simulated investor personas. Each session is scored and generates a detailed performance report — covering strengths, weaknesses, and red flags. Progress is tracked over time so founders can measure improvement across sessions.
Upload a pitch deck (PDF or PPTX) and receive an AI-driven evaluation with specific observations, identified issues, and prioritized recommendations. Analysis can be aligned against target customer profiles for laser-focused feedback. Results export directly to PowerPoint or push to CRMs like HubSpot, Salesforce, and Monday.com.
AI-powered matching connects startups with relevant VCs, angel investors, accelerators, and grant programs based on fit. Each match is scored (Excellent / Good / Fair) so founders can prioritize outreach effectively. Matches can be saved, hidden, and tracked through the fundraising process.
Deep intelligence on specific target customers — including financial performance, corporate strategy, leadership, competitive landscape, and vendor spend. Helps founders tailor their value proposition before walking into a sales meeting or investor conversation.
Sector scans to identify acquisition targets or partnership candidates, with strategic fit scoring against the user’s business context. Built for founders exploring exit paths or growth through acquisition.
Automated financial projections and feasibility scoring to stress-test a business concept and support investor conversations with credible numbers.
In short: PitchFit compresses weeks of research, coaching, and preparation into hours; giving founders and their teams an unfair advantage in competitive fundraising and sales environments.
Tools like Claude or ChatGPT require the user to know what to ask, how to structure the prompt, and how to interpret the output. PitchFit delivers structured, consistent outputs — pitch scores, investor match rankings, competitive landscapes, feasibility models — without the user needing any AI expertise. The workflow is the product.
Generic LLMs have no understanding of your business, your deck, your target investors, or your market. PitchFit builds a profile around the startup and applies that context across every feature — so the investor matches, pitch feedback, and customer research are all relevant to you, not a generic example.
Asking Claude to "pretend to be a VC" gives inconsistent, easily-flattered results. PitchFit's pitch trainer uses calibrated investor personas with scoring methodology, session tracking, and longitudinal performance data. Founders get honest, repeatable practice — not a chatbot that agrees with them.
Customer research and M&A intelligence in PitchFit pulls from live financial and market data — not just a language model's training data. A generic LLM cannot tell you a company's current revenue trend, recent leadership changes, or live competitor market share.
PitchFit produces exportable reports, PowerPoint-ready decks, CRM-ready data (HubSpot, Salesforce, Monday.com), and scored recommendations. A generic LLM produces text that the user then has to reformat, interpret, and act on themselves.
The target user is a founder, not an AI power user. PitchFit removes the skill gap entirely — founders get expert-level outputs without knowing anything about how to work with AI.
We accept credit cards, Apple Pay, and Google Pay for seamless transactions.