EmbryoNet AI Technologies
I helped turn a validated AI and microscopy technology into a laboratory-facing software product. My work ran from product vision and UX architecture to prototypes, delivery, and client-specific workflows.
Hero visual: microscope or product shot. Screens can be blurred or reconstructed for confidentiality.
I had been close to the project for years, helping with smaller visual and presentation tasks. In 2024 I joined as a core product contributor, when the research, publications, AI models, and computer-vision foundation were already strong.
What was missing was the product layer. There was no laboratory-facing software, no interface for interacting with the microscope, no website, and no coherent product narrative for demos, conferences, and potential clients.
Users & workflow
The users were scientists in small and mid-sized laboratories, plus research teams inside a large pharmaceutical client. Their core task was to test new drugs and compare which experimental conditions looked most promising.
Before touching the software, they prepared samples, chose experiment conditions, placed samples into plates, and defined observation parameters. The interface had to mirror this physical laboratory process instead of forcing it into generic dashboard logic.
The product spanned the full experiment: setup before the run, interpretation during and after, and preparation of results for real decisions.
Onboarding, project creation, sample setup, experiment conditions, microscope configuration, admin and settings.
Dashboard, image and video analysis, time-series viewer, model segmentation, deviation detection, and comparison views.
Reports, statuses, alerts, error states, client-specific workflows, and preparation of results for downstream use.
Actual product screen. Blur or crop as needed for confidentiality.
Reconstruction showing the logic without exposing sensitive detail.
Key decisions
Scientists needed to trust AI-assisted analysis inside a serious research workflow. I structured the AI experience around visible analytical steps: time sequence, segmentation, detected deviations, comparison, and report preparation.
Before the experiment, users needed control and validation. After it, they needed comparison and interpretation. I split the product into distinct setup and analysis workspaces.
In a hardware-connected workflow, users need to know what is configured, what was sent to the microscope, what is running, what failed, and what is ready for analysis.
I designed a core workflow flexible enough to adapt selected processes for specific clients, without rebuilding the product from scratch each time.
Leadership & delivery
I led a product team of four: myself as CPO and Product Design Lead, plus three developers across frontend and backend. My job was to translate scientific and client needs into product decisions, prototypes, development tasks, and iterative releases.
Results
The project moved from a scientifically validated technology toward a working software product that could be demonstrated, tested, customized, and used with real partners and clients.
Reflection
Product design here was translation: from science to software, from laboratory practice to interface logic, from AI capability to a workflow people can trust.
The most meaningful part was helping build a tool that lets researchers study complex biological processes faster, and with more confidence.