A life sciences consulting firm relies on research-driven PowerPoint presentations to support client engagements. These presentations are essential for delivering insights, recommendations, and strategic guidance. As the volume of work increased, both speed and accuracy became critical to maintaining quality and meeting client expectations.
Over time, the process of creating these presentations became increasingly inefficient. Teams spent significant time searching for existing research across shared drives and external tools. Content was fragmented, and there was no centralized system to identify what work already existed or whether it had been approved for reuse.
This fragmentation led to repeated effort and inconsistent results. Consultants often rebuilt slides that had already been created. Verifying research sources required manual checks, which slowed delivery and increased the risk of errors. Each new presentation added friction rather than building on past work.
At the same time, teams began experimenting with third-party AI tools to speed up research and drafting. These tools were used in isolated ways and without governance. This introduced new concerns around data security, compliance, and rising per-seat licensing costs.
As a result, the workflow became a clear bottleneck to scale. Productivity suffered, and leadership lacked visibility into how AI was being used across the organization. The firm needed a more efficient and controlled approach that could improve speed while maintaining accuracy, compliance, and governance.
Mutually Human designed a set of AI-enabled micro applications tailored to the client’s existing research and presentation workflows. The approach focused on customization and rapid iteration, allowing teams to test ideas quickly and refine functionality based on real use. This made it possible to demonstrate value early while keeping the solution flexible and easy to adapt.
The solution was integrated directly with the client’s existing content repositories, including SharePoint, Google Drive, and approved external sources. By working within tools teams already used, the platform simplified research discovery and reduced the need for manual searching. AI-generated outputs were grounded in trusted content and reviewed by users to ensure accuracy and relevance.
To support security, compliance, and scalability, all AI activity was centralized through a governed Azure-based environment. This provided consistent authentication, protected sensitive data, and allowed leadership to manage AI usage and costs. The result was a solution that aligned with the client’s technology strategy and could scale as new micro applications and use cases emerged.
The AI-enabled micro applications delivered immediate value by removing manual steps from the research and presentation process. Teams were able to work faster, reuse trusted content, and rely on a governed AI environment. The solution improved productivity while reducing risk and creating a strong foundation for future expansion.
Teams significantly reduced the time required to build research presentations. AI-assisted drafting made it easier to assemble content quickly and consistently.
Consultants completed more presentations with less effort. Time previously spent searching and validating research shifted to higher-value client work.
All AI queries flowed through a single, managed platform. This reduced reliance on third-party tools, lowered overall costs, and improved data security.
Adoption across teams was strong from the start. Users began requesting additional micro applications to support new workflows and use cases.
A fragmented and manual process became automated, scalable, and governed. The new workflow supports growth without adding operational complexity.
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