What makes Stampli’s AI different?
It seems like everyone’s suddenly discovered AI. Certainly, it seems like every AP automation software provider is announcing this new machine learning feature or that new natural language processing feature.
But while the industry adds features of dubious impact, we at Stampli find ourselves in a unique position: looking back on almost a decade of real-world AI application in accounts payable.
One thing is clear: Not all AI is created equal, and many software providers’ claims about AI are highly speculative at best.
Let’s talk about the difference nearly 10 years of AI experience really means for your business.
2015: When we saw the potential
Back in 2015, when we launched Stampli, AI wasn’t seeing the frenzy it is today. That’s part of the reason why we saw something others didn’t: a perfect match between AI’s capabilities and the day-to-day challenges of AP teams.
Our CEO and co-founder, Eyal Feldman, recalls: “We didn’t just add AI as a feature. We built our entire system around it, knowing the technology would evolve rapidly. This decision shaped everything — from our infrastructure to our product strategy.”
After nearly ten years of data, learnings, and refinements, here’s our results:
- AI that processes $80 billion in annual invoice value processed for 1,600 customers
- Millions of labor hours saved for finance teams
- An AI system that’s evolved through countless iterations and improvements
Why Stampli’s AI is different
There are 7 reasons why Stampli’s AI is different and better from the rest of the industry:
- Demonstrated ROI: For nearly 10 years, Stampli’s AI has been actively employed by customers, resulting in literally millions of hours of labor saved for finance departments. The system now handles over $85 billion in yearly invoice value for 1,600 clients, showcasing its real-world effectiveness.
- AI-centric organizational structure: Stampli’s entire corporate and technical framework is built around AI, rather than adding AI as an afterthought as our competitors are doing. Every aspect of the company, from data management to user experience design to our hiring practices, is optimized to deliver AI that increasingly takes on more tasks for customers.
- Focus on reducing workload: Instead of adding AI features that actually increase user responsibilities, Stampli concentrates on deploying AI to minimize labor. The goal is to automate or assist with tasks, allowing users to dedicate their time to more strategic activities.
- Human oversight with AI efficiency: Stampli’s AI presents its recommendations for human review, striking a balance between automation and control. This approach allows operators to supervise their AI assistants rather than performing manual tasks themselves, resulting in substantial time savings while maintaining accuracy.
- User-friendly AI integration: The AI, personified as Billy the Bot™, delights new customers, who quickly come to view it as a valuable team member. Users appreciate how the AI takes over tedious tasks, allowing them to focus on more impactful work for their companies. We hear from customers all the time about how much they love BIlly.
- Adaptive learning system: The AI’s architecture enables it to learn from user adjustments and corrections, continuously improving its performance. It adapts to each customer’s unique processes and evolves alongside them, requiring no additional programming when procedures change.
- Pioneering next-generation AI: Stampli’s deep understanding of customer business processes allows them to identify and rapidly deploy emerging AI technologies that best improve outcomes. This approach enables Stampli to lead rather than follow in AI innovation, providing customers with tangible benefits from cutting-edge AI advancements.
Looking forward: What’s next for AI in AP?
While many are just starting to explore AI’s potential in AP, we’ve already built the next generation of innovations. “The advances we’re working on now are built on a decade of real-world application,” says CTO and co-founder Ofer Feldman. “We’re not theorizing about AI’s potential — we’re extending its proven capabilities.”