About the company

We’re a product-first scale-up on a mission to transform the e-commerce experience with AI.

Kleep AI is an AI-powered SaaS helping fashion brands make their e-commerce more personalized, more efficient, and more profitable. Our solutions leverage advanced AI and LLMs to improve product discovery, performance, and user experience, while supporting a more sustainable e-commerce model.

Founded in 2021 by two data scientists, Kleep AI has raised €2.5M and is now trusted by 150 international fashion brands, including Lacoste, Kenzo, Givenchy, The Kooples, Showroomprivé, Intersport, Victoria Beckham, Soeur, and more.

Kleep is now at €1.2M ARR, profitable, growing x5 year-over-year, and expanding to the US with a newly opened NYC office.

About the Role

As a Customer Success & Process Optimization Intern, you will be at the heart of the relationship between Kleep and its partner brands.

Your role:

• Ensure a smooth and premium customer experience throughout the product integration process
• Identify and improve internal processes to increase efficiency
• Directly contribute to customer satisfaction and company growth

This is a highly educational position combining customer relations, project management, and continuous optimization—perfect if you want a hands-on understanding of how an AI startup operates internally.

Your Missions

Customer Success

• Manage client integrations (onboarding, testing, validation, post-launch follow-up)
• Communicate daily with brands to support them in using the product
• Identify and resolve friction points with tech, product, or design teams
• Analyze client performance metrics (adoption, usage rates, AOV uplift, return rates)

Process Optimization

• Map internal processes within the CSM team and propose improvements
• Enhance client tracking and reporting tools (dashboards, KPIs, alerts)
• Collaborate with the CEO and CTO on efficiency and scalability priorities

Cross-Functional Collaboration

• Coordinate with Sales (pre-signature) and Product (post-launch) teams