Demo

Walk through MergenKit with the founder.

A demo session covers your modelling question, your data, and how the platform's three analytical modules fit your discovery workflow. There is no slide deck. The conversation starts with science.

What MergenKit does

MergenKit is a no-code, cloud-native workspace where structure-activity and structure-property relationships are modelled, interpreted, and reported within a single guided workflow. Predictive modelling, transfer learning, and multi-objective optimization share the same configuration interface.

Who it's for

Pharmaceutical R&D teams, biotech startups, contract research organisations, and academic drug discovery groups working on biological activity, ADMET, and physicochemical property prediction.

What you get

A direct conversation with the founder about your data, a walkthrough of the relevant modules, and the option of a sandbox tailored to your dataset. No procurement gauntlet to clear first.

What happens next

Three steps from request to sandbox.

No pressure, no procurement runway. The aim is to confirm whether MergenKit fits your discovery question before either side commits effort.

  1. 01
    We review your use caseYour submission goes directly to the founder. We confirm scope and read what you have written carefully before responding.
  2. 02
    We schedule a technical discussionA short call covers the scientific question, the data, your team's modelling stack today, and what a useful proof point would look like.
  3. 03
    We set up a sandbox tailored to your datasetIf the workflow fits, we configure a sandbox keyed to your data so the proof of value runs on your chemistry, not on a generic benchmark.

Want to read more before the call? See the three analytical modules and the methodological principles.