Managers hedged budgets, leaving capital frozen. AI agents now reallocate funds in real time, freeing €1B for new discoveries.
A global biopharmaceutical company faces massive R&D risks, where a single Phase III trial costs $500 million despite a 35% chance of failure.
High attrition rates meant 90% of Phase I candidates failed, wasting years of development time. Additionally, defensive internal hedging during...
“Last year, I redeployed close to a billion euros in real time. We didn’t wait for a budget cycle; we had real-time business intelligence. Using AI, we reduced out-of-stocks by 80 percent, which is close to a billion euros, and we improved asset utilization by more than ten percentage points.”
Biopharmaceutical company specializing in immunology, vaccines, and rare diseases.
Worked as an ecosystem partner to help Sanofi accelerate drug discovery and development via AI.
Provided agentic AI and LLM technology for Sanofi's end-to-end business transformation.
Sanofi's Drug development and operations 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.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Clinical teams spent hours manually compiling siloed data. Now, AI agents query those systems to deliver trial insights in minutes.
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Generic AI mangled chemistry terms; manual translation took months. Glossary-tuned AI now earns enough trust to publish before human review.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
Teams manually screened hundreds of pages per deal. Now, they query filings to surface critical insights instantly.
Scouring 12+ silos delayed critical IP checks. GenAI unified search, letting 4 analysts match the output of a 100-person team.
Managers hedged budgets, leaving capital frozen. AI agents now reallocate funds in real time, freeing €1B for new discoveries.
A global biopharmaceutical company faces massive R&D risks, where a single Phase III trial costs $500 million despite a 35% chance of failure.
High attrition rates meant 90% of Phase I candidates failed, wasting years of development time. Additionally, defensive internal hedging during...
“Last year, I redeployed close to a billion euros in real time. We didn’t wait for a budget cycle; we had real-time business intelligence. Using AI, we reduced out-of-stocks by 80 percent, which is close to a billion euros, and we improved asset utilization by more than ten percentage points.”
Biopharmaceutical company specializing in immunology, vaccines, and rare diseases.
Worked as an ecosystem partner to help Sanofi accelerate drug discovery and development via AI.
Provided agentic AI and LLM technology for Sanofi's end-to-end business transformation.
Sanofi's Drug development and operations 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.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Clinical teams spent hours manually compiling siloed data. Now, AI agents query those systems to deliver trial insights in minutes.
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Generic AI mangled chemistry terms; manual translation took months. Glossary-tuned AI now earns enough trust to publish before human review.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
Teams manually screened hundreds of pages per deal. Now, they query filings to surface critical insights instantly.
Scouring 12+ silos delayed critical IP checks. GenAI unified search, letting 4 analysts match the output of a 100-person team.