The startup offers an investment tool that enables users to browse, evaluate, and invest in private equity, real estate, venture capital, and hedge funds through a streamlined platform. By facilitating fund comparisons and direct communication with fund managers, the tool enhances decision-making efficiency for investment professionals.
Funding
$200K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Investment professionals often struggle with fragmented data scattered across various sources like pitch decks, call notes, emails, and data rooms, leading to inefficient decision-making processes. Organizing and querying this unstructured data to gain real-time insights can be time-consuming and challenging.
Solution
Velvet provides an AI-powered copilot designed to automate and streamline the investment process for professionals in private markets. The platform aggregates unstructured data from diverse sources into a centralized knowledge base, enabling users to query data rooms, market data, and firm information in real-time. By leveraging AI-driven solutions, Velvet facilitates seamless collaboration and accelerates due diligence, allowing investment firms to focus on identifying opportunities and making informed decisions. The system automates up to 80% of the tasks from initial deck review to final decision.
Target Audience
Velvet primarily targets venture capital, private equity, family offices, and allocators seeking to optimize their investment process and make data-driven decisions.
Features
- AI-powered digital analyst that organizes unstructured data from pitch decks, call notes, memos, spreadsheets, emails, and data rooms.
- Real-time AI analysis for querying data rooms, market data, and firm information.
- Integration capabilities to aggregate information from existing systems into a single, queryable platform.
- Secure, encrypted AWS server infrastructure with authentication procedures.
- Role-based access controls to ensure data privacy and confidentiality.
- AI models are never trained on user data.