Sylvain is Co-Founder and CTO of Parseur, overseeing the platform’s architecture and global infrastructure.
A seasoned software engineer and Python expert with more than 20 years of experience, he designed and developed Parseur’s robust parsing engine and ensures Parseur’s servers run smoothly around the clock. Passionate about simplifying complex systems, Sylvain excels at delivering reliable, scalable solutions that make document automation accessible to businesses worldwide.
Company: Parseur
We are thrilled to have you join us today, welcome to ValiantCEO Magazine’s exclusive interview! Let’s start off with a little introduction. Tell our readers a bit about yourself and your company
Sylvain Josserand: I am the CTO of Parseur, overseeing the platform’s architecture and global infrastructure. Parseur is a leading AI document processing tool that automates data extraction from documents. As a seasoned software engineer and Python expert with more than 20 years of experience, I’ve designed and developed Parseur’s robust parsing engine and ensures Parseur’s servers run smoothly around the clock. I’m passionate about simplifying complex systems, and I excel at delivering reliable, scalable solutions that make document automation accessible to businesses worldwide.
What specific areas of your business have been most impacted by AI, and how?
Sylvain Josserand: AI has transformed our data extraction process. Customers no longer need to create templates for every document type. Now, they can specify the required information and the platform identifies and extracts it automatically. This change has sped up onboarding and reduced support requests. Our team spends less time on manual fixes and can focus on making improvements based on user activity and feedback. AI also gives us actionable insights, so we can better understand what features matter most to customers.
How are you ensuring ethical considerations are taken into account in your use of AI?
Sylvain Josserand: We built Parseur with data privacy at the core. All customer data is processed in compliance with GDPR and is never used to train public AI models. Documents can be deleted automatically after processing or retained for a short period based on user settings, with full deletion, including backups, within a limited window. This keeps sensitive information secure and minimizes risk. We work only with infrastructure providers that meet strict privacy and compliance standards. Transparency is essential. Customers can see what data we collect, control how it is used, and delete it at any time.
Internally, we evaluate every AI tool with the same mindset. It must protect our users, support responsible automation and align with our values.
What advice would you give to other CEOs looking to integrate AI into their business?
Sylvain Josserand: Identify specific areas where AI can address genuine inefficiencies or pain points. Communicate openly with your team and customers about any changes and the reasons behind them. Test new tools carefully and monitor results. Be realistic about what AI can accomplish and ensure you have a process to review and adjust your approach over time. Build a foundation of transparency and gradual improvement.
How do you see AI evolving in your industry over the next 5 years?
Sylvain Josserand: I think AI will become a default part of document and data automation. More of the setup will disappear and tasks that used to take time and manual input will happen quietly in the background.
We recently looked at how much time teams still spend on manual data entry, and the numbers were surprising. On average, it adds up to more than $28,000 per employee per year. That is a huge amount of time and money going to something no one really wants to do. I see AI helping businesses reclaim that time so their teams can focus on what actually moves the needle, solving problems, supporting customers and building better systems.
In the longer term, the future looks all about connecting specialized AI agents so they can work together, each doing what they’re best at. Standards like MCP will make that easier by giving agents a common language. In that ecosystem, tools like Parseur become the entry point that guarantees data quality, so every downstream agent is working with clean, reliable information.
