We got tired of watching good ideas stall in staging.
SyncAgent Pro exists because the gap between "impressive demo" and "running in production" was costing companies real time and real money — and nobody seemed to be fixing it.
How this started
In 2022, the three of us were doing separate things — one in enterprise automation consulting, one in applied ML at a logistics firm, one running a small dev shop in Regensburg. We kept running into the same friction: clients who had seen compelling AI agent demonstrations but couldn't get anything shipped.
The demos were real. The technology worked. What was missing was the operational layer: the error handling, the monitoring, the edge cases, the handoff documentation, the understanding of what happens when the agent encounters something it wasn't trained on at 2am on a Sunday.
We started SyncAgent Pro to fill that specific gap. Not to build the most advanced AI systems — there are larger companies doing that well. But to be the team that takes an agent from proof-of-concept to a thing your operations team can actually rely on.
What we care about
We work with companies between roughly 50 and 500 people — large enough to have real operational complexity, small enough that a broken workflow has immediate consequences. These companies can't afford a six-month integration project that ends with a system nobody maintains. They need something that runs, stays running, and is understood by more than one person.
That shapes everything we do: how we scope projects, how we structure handoffs, how we set up monitoring, how we write documentation. The goal is always that your team can own the system after we're gone.
"An AI agent that impresses in a boardroom and fails silently at scale is worse than no agent at all. It creates trust debt."
The team
Small on purpose. We work on a limited number of engagements at any time so each one gets full attention.
Elena spent six years building data pipelines and orchestration systems at a Munich-based logistics software company before moving into AI agent work. Her background is in distributed systems and failure analysis — which means she spends most of her time thinking about what goes wrong, not what goes right. She leads technical architecture on all engagements and oversees deployment and monitoring setup.
Daniel worked for four years as an operations consultant, primarily in financial services and SaaS, before specializing in workflow automation. He joined SyncAgent Pro at founding after a project where he had to explain to a client why their expensive AI integration had been silently producing wrong outputs for three weeks. His work focuses on the operational side: understanding how a company's processes actually work before designing anything that touches them.
What we don't do
- We don't build demos or proof-of-concepts that we hand off and wish you luck with
- We don't run open-ended retainers where the scope drifts indefinitely
- We don't take on more than a few projects at a time
- We don't promise specific performance numbers before we've audited your actual workflows
What that means in practice
- Every engagement ends with a running system, documentation, and monitoring in place
- We define scope precisely at the start of a project
- Your internal team knows how to handle the agent before we close the engagement
- We're honest when a particular automation isn't worth building
If this sounds like the right fit
We take a limited number of new engagements each quarter. The best starting point is a 30-minute call to assess whether your automation need is a good match for what we do.
Get in touch