Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
A global pharmaceutical company with 80 years of medical dermatology experience has accumulated over 50 years of research data across 400,000 documents in three different languages.
Scientists spent hours manually digging through scattered files and outdated systems to find past experiments. This inefficient process buried...
“Making new discoveries is key. A new discovery later becomes a potential treatment for our patients, improving their quality of life and even potentially healing the disease.”
Pharmaceutical developer of medical dermatology and skin health treatments.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Almirall's Research document search is part of this use case:
Related implementations across industries and use cases
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Advisors spent days digging through 100-page crop labels. Now, a specialized AI surfaces precise, source-linked agronomic guidance.
Silos forced teams to manually chase data. Now, AI agents identify adverse events in seconds, eliminating weeks of cross-referencing.
Advisors spent days digging through 100-page crop labels. Now, a specialized AI surfaces precise, source-linked agronomic guidance.
10,000 supply chain workers spent half an hour manually searching compliance libraries. Now, an AI assistant finds answers instantly.
Every HCP response required manually searching regulated literature. Now agents surface cited answers from 3,100+ medical documents.
Every update meant re-recording across five teams. Now a script upload produces multilingual medical video without a single studio session.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
A global pharmaceutical company with 80 years of medical dermatology experience has accumulated over 50 years of research data across 400,000 documents in three different languages.
Scientists spent hours manually digging through scattered files and outdated systems to find past experiments. This inefficient process buried...
“Making new discoveries is key. A new discovery later becomes a potential treatment for our patients, improving their quality of life and even potentially healing the disease.”
Pharmaceutical developer of medical dermatology and skin health treatments.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Almirall's Research document search is part of this use case:
Related implementations across industries and use cases
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Advisors spent days digging through 100-page crop labels. Now, a specialized AI surfaces precise, source-linked agronomic guidance.
Silos forced teams to manually chase data. Now, AI agents identify adverse events in seconds, eliminating weeks of cross-referencing.
Advisors spent days digging through 100-page crop labels. Now, a specialized AI surfaces precise, source-linked agronomic guidance.
10,000 supply chain workers spent half an hour manually searching compliance libraries. Now, an AI assistant finds answers instantly.
Every HCP response required manually searching regulated literature. Now agents surface cited answers from 3,100+ medical documents.
Every update meant re-recording across five teams. Now a script upload produces multilingual medical video without a single studio session.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.