The pharmaceutical industry is coming to grips with a 'new normal' characterized by increasing pressure to control drug prices and to provide more accessible, affordable healthcare. As it becomes increasingly globalized, complex, and highly-regulated, competitive and regulatory drivers are demanding that it also become more streamlined and cost-efficient.

As pharma companies re-engineer operations to speed new products to market and reduce costs, quality managers must accomplish more, with the same or fewer resources, in less time. They are on front lines of change—charged with detecting any problems—in an industry that suffers dire consequences when mistakes are made or trends are missed. Their success hinges on meeting three goals: maintaining compliance, supporting strategic initiatives that will enable more streamlined, efficient operations across the company, and providing stakeholders with increased transparency and accountability regarding compliance activities.
To accomplish these objectives, they must answer difficult questions about where quality issues may lie – across an extended value chain — as quickly and accurately as possible. The answers often lie hidden in large volumes of text-based information like: CAPA reports, deviations audit reports, change control documentation, validation protocols/reports, batch manufacturing records (BMRs), technical memos, regulatory responses, Standard Operating procedures, clinical study reports, and complaints, etc.

Pharma quality managers need a smarter, faster, and more explainable AI solution that’s designed to help them save time, resources, and money—because it allows them to:
Better identify insights and become more proactive so they can diagnose quality issues sooner and solve problems more quickly, decreasing business risk and costs.
Obtain the intelligence to support new strategic initiatives that bring better drugs to market sooner and achieve efficiencies in manufacturing and the supply chain.
Document their ongoing compliance research so they can demonstrate to authorities (regulatory, auditors), executives and key stakeholders that they’re doing the right things and in the right way.


Robotic Process Automation (RPA) has taken the world by storm by easily automating repetitive tasks that include highly structured data included in data like order forms or billing statements. Intelligent Process Automation (IPA) enables more complex tasks to be automated by analyzing text.

Text or unstructured data create significant workflow inefficiencies across enterprises. McKinsey’s Global Institute measured the impact of those inefficiencies at $3 Trillion dollars. Including free form text analysis, whether email, reports or research, this data and automation capability becomes a critical part of any Digital Transformation toolkit for enterprise organizations.

Kyndi’s AI software can be used in conjunction with RPA tools such as UiPath, Automation Anywhere or BluePrism to build bots that analyze text and automate inefficient workflows in industries such as Insurance by analyzing medical records for class action lawsuits or understanding drug interactions for pharmacovigilance applications. The ability to quickly analyze text across multiple domains provides a significant differentiator for Kyndi’s approach.


Preventing attacks or anticipating threats – such as new information about people, places or organizations and their connections – is critical to preserving long-term competitiveness, be it a technologically advanced military or intelligence organizations.

Domain experts and analysts analyze and disseminate value-added information to anticipate and prevent these surprises. Strategic thinking and informed planning fosters foresight – developing ideas about what plausible futures might look like – to support an organization’s long-term objectives for strategic direction and threat management.

The volume and breadth of information – hundreds of thousands of pages published and collected every month – make it difficult and time-consuming to leverage all of the data and nearly impossible for analysts to make sense of it all. As a result, essential information is missed, and opportunities and threats go undiscovered.

Kyndi’s technology allows your threat assessment process to be dramatically better by integrating disparate data from information silos at scale. By having the system search this information at high speed, human analysts can now spend the majority of their time on qualitative research and quickly take action on the insights they discovery. Data is secured so that information can be processed across data models and classification levels while managing privacy, civil liberty and data handling policies.