Digital & Technology
A leading biopharma company unlocks deeper commercial insights with gen AI by ZS and AWS

Impact by the Numbers
Impact by the Numbers
98%
Time savings to run analytics, reducing effort from 4-5 hours per question to 3-4 minutes
98%
Time savings to run analytics, reducing effort from 4-5 hours per question to 3-4 minutes
95%
Accuracy across simple, medium and complex queries
95%
Accuracy across simple, medium and complex queries
40+
Patient-analytics-related business questions successfully trained on the bot
40+
Patient-analytics-related business questions successfully trained on the bot
One of the world’s leading biopharma companies teamed up with ZS and Amazon Web Services (AWS) to create a powerful generative AI tool, custom built to answer complex questions at unprecedented speed and that’s ready to scale across the global enterprise.
Within three months, commercial leaders began piloting the new AI solution and are already achieving big wins, thanks to an upswing in productivity, speed and trust. Later this year, they plan to scale the solution to other business areas like finance, human resources and beyond.
“So far, the big wins come down to speed and efficiency. Commercial leaders now have a quick, reliable way to answer complex questions, leading to an upswing in productivity.”
Vish Singh, ZS Principal
“So far, the big wins come down to speed and efficiency. Commercial leaders now have a quick, reliable way to answer complex questions, leading to an upswing in productivity.”
Vish Singh, ZS Principal
The challenge: Moving commercial analysis from ‘what’ to ‘why’
The challenge: Moving commercial analysis from ‘what’ to ‘why’
The global biotech company’s journey began with a question: Could it use generative AI to query data in natural languages and produce reliable answers? If so, the leaders saw an opportunity to fuel quick, informed decision-making throughout its commercial enterprise and empower business leaders to pivot their analytical questions from “what” to “why.”
Commercial teams already used tools like Tableau to answer basic questions like “What are my sales trends for a specific product for the last quarter.” But they found that those tools couldn’t produce reliable answers to more complex queries like “Why are my sales trending downward?”
To get at the “why,” leaders had to translate complex questions into SQL statements, then wait for days or weeks for an accurate answer from teams of analysts or developers. Often, the first answer begged another question, which required another database query, further delaying decision-making.
The pharma company hoped that generative AI could help its commercial leaders unpack complex problems faster and make informed decisions autonomously.
The solution: A generative AI analytics tool rooted in life sciences knowledge
The solution: A generative AI analytics tool rooted in life sciences knowledge
To bring their vision to life, leaders sought a strategic partner with substantial life sciences expertise and innovative generative AI products. After a demo of Max.AI, ZS’s generative AI platform powered by AWS, they chose ZS as their solution provider and strategic partner.
In partnership with AWS, ZS and the company began building a custom generative AI tool on an accelerated timeline. ZS took the lead but followed a codevelopment approach. Every decision was made in collaboration with AWS and the client team—from architecture to design to selection of services, deployment strategy and documentation. According to Vish Singh, a leader on the ZS solution team, “The custom solution was the product of collaboration—with our client and with our partners at AWS.”
The AI solution was built on Amazon Bedrock and Amazon Elastic Kubernetes Service (EKS). “As our trusted partner, AWS made the specific technology choices and recommended Bedrock and EKS to us,” Singh shared.
The project’s first major milestone was the creation of a custom product demo. Within six weeks, the product demo was ready to debut at the company’s IT innovation and process meeting to an audience of more than 300 people. Then the team took the product to the commercial business leaders to get their buy-in.
Soon, the team will begin scaling the solution beyond the commercial space into other business areas, as it is scalable by design. Rather than building a pilot for just one use case, ZS and AWS created a tool the company can use to expand its platform strategy. Leaders anticipate the solution having a much wider impact on the company’s efficiency and productivity as new use cases emerge.
The expansion possibilities are infinite, in part because the solution is scalable, and in part because the tool will become smarter over time, thanks to its foundation on AWS and its intelligent design.
The impact: Speed, productivity and trust, powered by generative AI
The impact: Speed, productivity and trust, powered by generative AI
To date, the company has used its custom generative AI solution to achieve big wins:
- Efficient, autonomous decision-making. With the new generative AI tool, commercial leaders no longer need to spend days or weeks consulting a team of developers or analysts to track down answers to deeper questions. Instead, leaders can independently generate answers in minutes, slashing the turnaround time by 98% for solving complex problems or addressing emerging trends.
- Reliable answers to complex analytical questions. The solution was successfully trained on more than 40 relevant patient analytics business questions with three to four variations per base question, achieving 95% accuracy across simple, medium and complex queries.
- Results leaders can trust. The solution doesn’t just produce an answer—it generates the evidence behind the answer to build trust in the result and ensure accuracy.
- A solution that scales. The custom AI tool is designed to scale as new use cases emerge in different business areas or new user groups are added.
“So far, the big wins come down to speed and efficiency. Commercial leaders now have a quick and reliable way to answer complex questions, leading to an upswing in productivity,” reflected Singh.
Commercial leaders are optimistic that they will continue to unlock value from this generative AI solution for years to come, as new use cases arise and the tool expands to other user groups and business areas. And as the company’s database of institutional knowledge grows, the information will remain in the system long after the tool changes hands or individuals change roles, making it increasingly valuable to new and experienced users across the enterprise.