DiscoverY

Two halves of one job, in two different tools.

DSTL explores cutting-edge science by spotting novel research, developing internal concepts from it, and turning those into structured experiments. The work has two distinct sides: discovering emerging ideas, and enriching them into testable hypotheses — and the team was doing each in a different, disconnected place.

The goal was a single platform that streamlined the whole process, built from two components: workflow management, and AI-powered content discovery — what the team called future-scanning.

Understand the loved thing before replacing it.

For the discovery half, DSTL already relied on a robust existing platform. So our first move wasn't to redesign — it was to understand deeply how that tool worked and what users genuinely valued about it, before designing something better.

The future-scanning side then surfaced novel academic papers and global research using ML recommendations tuned to DSTL's specific scientific interests — pulling the signal out of thousands of candidates.

One experience, end to end.

The finished product let DSTL run their entire innovation pipeline — from discovery to experimentation — inside one experience. Instead of jumping between disconnected tools, teams could explore ideas, develop hypotheses, and kick off experiments without losing context between steps.

It replaced the legacy setup entirely.

DSTL adopted DiscoverY as their primary system, retiring their legacy setup. Within 15 months of kickoff it had become the go-to tool for the full innovation cycle — cutting process time roughly tenfold across experiment workflows by collapsing four disconnected tools into one.