Actionable, a Paris based startup specializing in predictive customer satisfaction analysis through artificial intelligence, has raised €8.5 million, equivalent to $10 million, in a funding round led by Hi inov. Existing investor Axeleo Capital also participated and increased its stake in the company. The investment follows a €2 million pre-seed round announced in September 2024 and will support the startup's push into new markets.
Investor Backing and Strategic Funding
The round was led by Hi inov, with Axeleo Capital strengthening its position after backing Actionable at the pre-seed stage. The company said the new capital validates its focus on moving from raw data collection to actionable intelligence for large enterprises. Hi inov co-founder and CEO Valérie Gombart noted that enterprises still spend heavily on data storage and measurement while the missing layer is explanation and action.
A Customer Data Model Built for Operational Reality
Founded in 2024 by Nans Thomas and Nicolas Rieul, Actionable has developed a predictive customer experience platform that works across the entire purchase journey. The company reconstructs raw tabular data into a Common Customer Data Model tailored to industries such as retail, financial services, insurance, transport, energy, telecoms, and automotive. This model incorporates operational details including waiting times, loyalty cards, load factors, and delivery times to give artificial intelligence systems the business context they need.
Founders with Enterprise Experience
Co-founder and co-CEO Nicolas Rieul said that for fifteen years he encountered dashboards showing satisfaction or revenue declines without explaining which customers to contact or what decisions to make. His background includes general management roles at Criteo and leadership of Alliance Digitale. Co-founder and co-CEO Nans Thomas, previously chief product officer at Innovorder and founder of Wino, contributed the product expertise needed to build the solution.
Measurable Impact at Carrefour
Actionable maps the journeys of 117 million consumers for clients including Carrefour, SNCF, Engie, and Edenred. At Carrefour, the platform identified that customer recommendation scores drop after six minutes and twelve seconds of waiting at click-and-collect points. This threshold came from the retailer's own data and is now tracked nationally, regionally, and store by store.
Early Wins Across SNCF and Engie
At OUIGO, SNCF's low cost rail brand, Actionable predicts satisfaction for each passenger and enables the company to send goodwill gestures before complaints arise. The incremental revenue generated by the first campaign covered the cost of the platform within weeks. At Engie, the system detects serious complaints before they escalate, allowing customer service teams to intervene earlier.
Beyond Generic Artificial Intelligence
The company argues that placing a large language model on top of a data warehouse is not enough because an AI reads raw tables poorly without business context. Actionable's main challenge was turning hundreds of tables and internal definitions into a customer model that machines can use accurately. Its Actionable Intelligence agent works as a data analyst on that model and produces analyses in hours that would take human analysts weeks.
Expansion Plans and Hiring
Actionable will use the new funding to finance hiring across product, engineering, and sales teams. The company also plans to support international development through a network of reseller partners, with particular attention to building out the United States market. This expansion strategy aims to bring its predictive customer experience platform to a broader set of large enterprises.
Actionable's funding round highlights the growing enterprise demand for tools that turn existing customer data into concrete operational decisions. By combining predictive scoring with industry specific context, the startup positions itself between traditional measurement platforms and the next generation of AI agents. The company's early results with major clients suggest that its approach can deliver measurable financial returns while helping organizations anticipate customer behavior.