EXCLUSIVE: London’s Ares Intelligence raises €2.6 million to turn employee insights into AI adoption plans

London-based startup Ares Intelligence has raised €2.6 million in funding from Creandum and Lakestar, with participation from angels connected to Google DeepMind.

Founded in 2026 by Matt Falconer and 21-year-old Alfie Ranstead, Ares Intelligence was created after the founders saw a common problem while running their previous automation company, Instruct: businesses wanted to adopt AI but often had no reliable way to identify where AI could create the greatest impact.

The company has developed an AI-powered workforce intelligence platform that conducts confidential, voice-based interviews with employees in more than 70 languages. It analyses employees' experiences and identifies opportunities where AI can reduce manual work, improve processes and save costs. Leadership then receives a prioritised, evidence-based roadmap within weeks.

The platform is designed with enterprise security in mind and is GDPR- and SOC 2-compliant. Businesses can anonymise employee information, redact voices and remove role metadata before reports reach leadership. Customers can also choose where their data is hosted and set their own retention periods.

Unlike traditional top-down AI transformation strategies, Ares Intelligence gathers insights directly from employees involved in day-to-day operations. This helps identify issues such as repetitive manual processes, broken workflows and the use of unauthorised AI tools.

The startup says it has already secured enterprise customers across Europe and the United States within around seven months of launching. One example is Tremonia, a Mercedes-Benz spin-out, where Ares reportedly identified mazore than 400 hours of avoidable manual work per month after interviewing employees across different levels of the organisation.

The new funding will be used to expand Ares Intelligence's operations and bring its AI-driven workforce intelligence platform to more businesses, as enterprises increasingly look for practical and evidence-based ways to implement AI.