Medlexion’s method is built on a simple assumption: someday, someone unfriendly may read the records your system produces. We work backwards from that moment.

We start by understanding where complaints, disputes or investigations have actually arisen, which forums matter, and which existing systems get involved when something goes wrong.

The outcome is a small set of flows we will design around.

Before any AI or automation, we define what events need to be captured, how those events connect into timelines and responsibilities, and what “good enough” evidence looks like in your context.

This is where most of our proprietary work lives. We do not publish these structures.

Once the architecture is clear, we implement automation and AI: deciding what should be deterministic and rule-driven, what can be assisted by AI, and what must stay in human hands.

We work with your existing stack where possible, and add just enough new surface area for the system to feel coherent.

From time to time, we take on adjacent projects where evidence, governance or dispute-risk is central. We almost never take on generic software work.