Synsor.ai
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What is Synsor? How did you come up with this idea?
Synsor is a deep-tech startup from Munich, working on real-time production control through product image analysis. We arrived at the idea after understand the current status quo in the industry and seeing the opportunities that the developments in AI opened up.
What problems does your solution solve?
Multiple trends like the retirement wave and increasing demand for flexibility in production force producers towards automation. Additionally, the average producers pays 10% of his revenue to cover quality related costs, most of those costs are tied to defects – e.g. returns, customer claims, rework, machine downtime etc.
What is your target group? Is it a cross-industry solution?
Core target group are producers of durable consumer products that position themselves as a premium brand. They should produce in an automated batch production process. But our solution is agnostic to the use-case, we can be deployed in various industries from packaging to furniture or medical devices.
Even though there is still much money to be earned and a lot of producers are lagging far behind the technical possibilities, from a strategic viewpoint doing just that would not have made us interesting for investors.
Tell us more about your team and its members.
We are currently a team of five, two founders, one full-time employee and two master students – all in the field of software development.
How critical is the implementation of AI & ML in your project? Do you use any other technologies?
It’s pretty much front and center of our product, we use deep learning, classic AI and synthetic data to achieve the necessary functionality. Besides that, we also use a bit of hardware/embedded software but that is only a side note relatively speaking.
What have been the biggest obstacles and how did you overcome them?
So far, our biggest obstacle was the realization that just doing quality control was not enough to have a place in the market. Even though there is still much money to be earned and a lot of producers are lagging far behind the technical possibilities, from a strategic viewpoint doing just that would not have made us interesting for investors. So we had to dig deeper into the question of where we think the industry would move towards and what they would need in the future. That’s how we arrived at our “ACT” product.
When and why did you join ACEIn and how has it helped you along the way?
Our team participated in the Start4Future program which enabled us to apply at the ACEin. As the ACEin has a good network towards manufacturers, we wanted to gain access to that and applied. Our most critical benefit was exactly that too, as we have been able to get in touch with relevant companies and picked up critical knowledge through these touchpoints.
What are the prospects for your startup? Next steps and goals?
It’s currently looking good, we are about to close our first major funding round and will the focus on the development of our ACT product as well as the formation of a scalable and efficient sales & marketing process to achieve 3+ paying customers for ACT until the next funding round awaits.
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