Paris-based Cleavr secures seed funding for AI-driven receivables
Cleavr, a Paris-based FinTech startup, has raised €1 million to develop an AI-powered platform designed to automate and modernise accounts receivable processes for businesses. The fresh capital will be used to accelerate product development, expand the engineering team and begin scaling commercial operations across Europe.
Targeting finance teams that still rely on spreadsheets, emails and manual workflows, Cleavr aims to reduce late payments, improve cash flow visibility and cut the operational cost of chasing invoices. By embedding AI algorithms into the receivables lifecycle, the startup wants to replace fragmented tools with a single, data-driven platform.
Automating the full collections lifecycle with AI
The platform developed by Cleavr connects to existing ERP, billing and CRM systems, aggregating invoice and customer data in real time. Its AI models analyse payment histories, contract terms and customer behaviour to predict the likelihood of late payments and recommend the optimal time and channel for outreach.
Rather than sending generic reminders, Cleavr generates personalised communication sequences, automating emails, notifications and task assignments for finance and sales teams. The company claims this approach can significantly shorten days sales outstanding (DSO) and reduce the volume of disputes by surfacing potential issues before invoices become overdue.
Rising demand for smarter cash flow tools
As higher interest rates and tighter liquidity put pressure on working capital, demand for smarter cash flow management tools has surged. Many mid-market firms lack the resources to build their own AI solutions, creating an opportunity for specialised platforms such as Cleavr.
With this €1 million round, the startup plans to deepen its machine learning capabilities, enhance integrations with leading accounting software and expand its presence among European SMEs and fast-growing SaaS companies. If successful, Cleavr could become a key player in the shift from reactive collections to proactive, data-driven receivables management.