Drug developers lost days hunting for research across scattered PDFs. Now, they query an AI agent for instant answers, accelerating R&D.
A leading biotechnology company manages a vast corpus of complex research data, including past trial designs, molecule data, and scientific reports scattered across multiple digital platforms.
Drug developers spent hours or even days hunting down and sorting through scattered links across PDFs, PowerPoints, and SharePoint folders to find...
“Drug development, which underpins our mission to serve patients, is very much becoming an information capability. Finding, parsing, and processing information is a big part of how we get medicines to patients more quickly.”
Amgen's Knowledge search is part of this use case:
Biotechnology company developing human therapeutics for serious illnesses.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
Scientists spent weeks manually searching 38 million files. Agents now finish in minutes, saving 43,000 hours.
Writers spent weeks sifting through data to draft reports. AI now generates a 14-section first draft in minutes for review.
Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
Advisors spent days digging through 100-page crop labels. Now, a specialized AI surfaces precise, source-linked agronomic guidance.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Agents manually priced 100-item email requests. AI now extracts data and drafts quotes, leaving humans to validate rather than type.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Drug developers lost days hunting for research across scattered PDFs. Now, they query an AI agent for instant answers, accelerating R&D.
A leading biotechnology company manages a vast corpus of complex research data, including past trial designs, molecule data, and scientific reports scattered across multiple digital platforms.
Drug developers spent hours or even days hunting down and sorting through scattered links across PDFs, PowerPoints, and SharePoint folders to find...
“Drug development, which underpins our mission to serve patients, is very much becoming an information capability. Finding, parsing, and processing information is a big part of how we get medicines to patients more quickly.”
Amgen's Knowledge search is part of this use case:
Biotechnology company developing human therapeutics for serious illnesses.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
Scientists spent weeks manually searching 38 million files. Agents now finish in minutes, saving 43,000 hours.
Writers spent weeks sifting through data to draft reports. AI now generates a 14-section first draft in minutes for review.
Scientists spent half a day digging through 50 years of scattered files. Now, an AI assistant retrieves past experiments in minutes.
Advisors spent days digging through 100-page crop labels. Now, a specialized AI surfaces precise, source-linked agronomic guidance.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Agents manually priced 100-item email requests. AI now extracts data and drafts quotes, leaving humans to validate rather than type.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.