According to Drylab AI, the platform is designed to retain knowledge about failed experiments, lab‑specific thresholds and scientific expertise. By recording this information, the system prevents valuable institutional knowledge from disappearing when projects end or researchers leave.

Drylab AI says its AI agents can independently plan tasks, write code and run advanced data analyses. Human oversight remains essential, as scientists must validate key decisions at built‑in checkpoints before the AI proceeds.

The platform also supports deployment in isolated cloud environments or on‑premises, giving pharmaceutical companies full control over their research data. This flexibility helps organisations meet strict security and compliance requirements while using AI tools.

A 2026 Nature study that examined 41.3 million scientific papers reported that researchers who used AI published 3.02 times more papers than those who did not. This shows how AI can dramatically increase scientific output.