

V7 Go
By V7
V7 is a London-based technology company specializing in artificial intelligence (AI) solutions aimed at automating complex tasks across various data types, including documents, images, and videos. Founded in 2018 by Alberto Rizzoli and Simon Edwardsson, the company has experienced significant growth and development since its inception.
Established in 2018, V7 has rapidly evolved into a key player in the AI industry. The company has expanded its team to 92 employees as of 2024, reflecting its commitment to scaling operations and enhancing its product offerings.
V7 has successfully secured substantial funding to fuel its growth. In a Series A financing round on November 28, 2022, the company raised $33 million, co-led by Radical Ventures and Temasek, with participation from Air Street Capital, Amadeus Capital Partners, and Partech. This round brought the total funding to $36 million over three rounds, valuing the company at approximately $97.2 million as of December 2022.
V7's flagship product, V7 Go, is designed to automate workflows by leveraging foundation models capable of reasoning across various data modalities. The platform enables users to:
Extract information from large, complex documents.
Qualify and categorize inbound messages.
Classify text, emails, or images at scale.
V7 Go introduces several innovative features, including:
AI Citations: Provides transparency by highlighting document excerpts used as information sources, allowing users to verify AI-generated responses.
Workflows: Enables users to create AI-powered assembly lines using conditional logic, routing data through different models with custom prompts.
Integrations and API: Offers seamless integration with existing systems via API and JSON outputs, as well as connectivity through Zapier.
V7 serves a diverse clientele, including Fortune 500 companies, scaleups, and startups. Notable clients such as GE Healthcare, Paige AI, and Siemens utilize V7's platform to develop sophisticated AI models. The platform's ability to automate data labeling processes has been particularly beneficial in accelerating AI development for these organizations.