Founding of Serros ML

People Mentioned
- Grzegorz Maniak
- Adrian Donnelly
Introducing Serros.ML
Adrian and I are excited to share Serros.ML, a programmable, event-driven AI customer support assistant. We’re building something more than just another chatbot, it’s a smarter way to manage customer interactions, blending AI and workflows to get things done efficiently and predictably.
Our idea? Streamline customer service without over-relying on LLMs, which are often hit-or-miss when it comes to structured tasks. Instead, Serros.ML takes a controlled, repeatable approach. Think less "AI magic," more "AI that works when you need it."
Why Serros.ML?
We’re not here to follow the AI trend for the sake of it. We see AI as a practical tool, a way to simplify processes and create real value, not add unnecessary complexity.
Here’s where we stand:
- Not just a chatbot: Serros.ML isn’t about replicating human agents; it’s about empowering them.
- No spammy automation: We focus on task-driven workflows, not blasting customers with unsolicited spam.
- Control over chaos: Unlike others, we aim for structured, reliable outputs you can trust.
- Purpose-built AI: It’s not AI for AI’s sake. It’s AI built to solve real problems businesses face every day.
Landing Page: Coming Soon!
Serros.ML Landing Page Preview
We’re working hard to roll out our site, and we’re almost there. Our landing page will give you a quick look at what we’re building, where we’re going, and how we aim to improve customer service. Expect an easy-to-navigate experience that lets you explore Serros.ML in a few clicks.
How Users Will Interact: A Scratch-like System
Serros.ML Scratch-like System Preview
One of the things we’re excited about is the interactive interface we’re designing for users. It’s built around a drag-and-drop system where you can create your own workflows by placing "blocks" into the conversation flow. Want to extract a variable from the conversation? Drag the Extract Variable Block. Need a condition? Use the If or If-Else blocks. When it’s time to end the conversation, simply drag the End Call block. It’s that simple.
What’s Next?
We’ve made solid progress on our MVP, and we’re excited about what’s ahead. From planning customer conversation workflows to designing a dashboard that puts users in control, things are moving fast.
If you’re interested in joining us on this journey, whether you’re curious, want to invest, or just like what we’re building, shoot us a message at hey@serros.ml or follow us on LinkedIn here.
Let’s make customer support smarter, together.