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Zeliq raises €7M to build an agentic revenue workspace

Salesprospecting platform Zeliq has raised a €7 million seed extension led by The Moon Venture, with participation from Julien Jean (JJCapinvest) and SylvestreBlavet (Freelance.com). Existing investor...

Zeliq raises €7M to build an agentic revenue workspace

Sales prospecting firm Zeliq has secured €7 million in seed funding to develop an AI-driven revenue workspace. The round, led by The Moon Venture, also saw investment from Julien Jean (JJCapinvest), Sylvestre Blavet (Freelance.com), Ora Global, Cleo Ventures, and various business angels and family offices. This brings Zeliq's total funding to €21 million in under three years.

Zeliq's platform unifies sales teams' activities, from prospect identification to multichannel outreach, within a single interface. It aims to streamline the fragmented technology stacks that many sales teams currently use. The company is building an AI-native platform that integrates salespeople and AI agents while maintaining human control over strategy and decision-making.

The EU-based startup is targeting mid-market sales teams, centralising over 450 million contact and company records that are enriched in real-time. It also manages outreach across email and phone, learning from each team's data. Zeliq's AI agent, Zelia, can search for, enrich, and contact prospects based on salespeople's instructions, and provide guidance on daily work. Zelia can also identify buying signals from prospects using web scanning, with the help of an MCP connector.

Zeliq plans to use the new funding to accelerate AI infrastructure development and its Agentic Revenue Workspace. This workspace allows sales and marketing teams to retain control of strategy while AI agents handle operational tasks. The company also aims to launch its first full suite of AI sales agents, double its product and technology teams within a year, continue its European expansion, and strengthen partnerships with CRM providers.

Written by urgent.news from Tech.eu's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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