Finding Research Insights Across Large Enterprises
Faster access to trusted knowledge through AI-powered research discovery
Organizations invest significant time, budget, and expertise into research. Market studies, customer insights, competitive intelligence, product research, innovation findings, and human-centered research all contain valuable knowledge that can shape strategy and improve business outcomes.
However, this knowledge is often difficult to find when it is needed most. Research may be stored across shared drives, collaboration platforms, local folders, presentation decks, spreadsheets, PDFs, whiteboarding tools, and team-specific repositories. Employees may know that relevant research exists, but still struggle to locate the right file, identify who led the work, or understand whether the information is current and relevant.
When research is scattered, organizations risk losing the value of work they have already completed. Teams spend unnecessary time searching, employees are repeatedly asked to locate files manually, and business units may duplicate studies simply because previous findings cannot be found.
With Mindbreeze InSpire, enterprises can create a centralized, AI-powered research discovery experience that helps employees find, understand, and reuse trusted knowledge across the organization.
Task
One of Mindbreeze’s customers needed a better way to make existing research accessible to authorized users across the enterprise.
The goal was to create a central search experience where employees could find relevant research, evaluate large documents quickly, and use previous insights to support strategic planning, customer experience improvements, product decisions, business development, and innovation initiatives.
The solution also needed to support sensitive and high-value research content. This meant that access, governance, trust, and content quality were critical from the beginning.
The organization wanted to reduce time spent searching for existing knowledge, limit duplicate research efforts, and make it easier for employees to act on insights that had already been created.
Solution
Mindbreeze InSpire provides a central entry point for searching across enterprise research and insight content.
The solution indexes relevant SharePoint folders and makes research easier to find through intelligent enterprise search, filtering, relevancy tuning, and AI-supported summaries. Authorized users can search across connected content sources and quickly receive the most relevant documents for their business questions.
The indexed content includes common enterprise research formats such as presentations, documents, spreadsheets, PDFs, screenshots, images, research reports, competitive intelligence files, and whiteboarding outputs. This is especially important for research-heavy organizations because valuable insight is often stored in long, visual, and unstructured files.
AI-powered summaries help users understand large documents faster. Instead of opening multiple long presentations or reports to determine whether they are useful, employees can quickly review summaries and focus their attention on the most relevant information.
Implementation
The implementation began by focusing on the foundation: connecting the most relevant research sources, improving search quality, supporting unstructured content, and building trust with users and content owners.
A phased rollout allowed the organization to test the solution with a focused group before expanding to broader business teams. Early users helped validate search relevancy, content quality, access needs, and user expectations.
Because the solution included sensitive research, the implementation required close collaboration between business stakeholders, technology teams, privacy, compliance, and research leaders. This cross-functional approach helped ensure that the search experience was not only useful, but also aligned with governance requirements.
Trust was a central part of the implementation. Content owners needed confidence that their research would be surfaced in the right context and used appropriately. Users needed confidence that the information they found was curated, relevant, and reliable enough to support business decisions.
AI capabilities were also introduced in a practical, governed way. Rather than launching every possible AI feature at once, the organization focused first on AI summaries because they addressed a clear user need: helping employees evaluate long research files faster.
This phased approach helped the organization build confidence in enterprise AI while delivering immediate value to users.
Target Achievement
Mindbreeze InSpire helped the organization reduce the time employees spent searching for and evaluating existing research.
Users were able to find relevant information faster, evaluate large documents more efficiently, and make better use of previous research. AI summaries improved the experience by helping employees quickly understand whether a document was worth deeper review.
As the solution matured, search relevancy improved. Users needed fewer searches to find what they were looking for, while the value of each search increased. This demonstrated that success was not only about search volume, but also about search efficiency and quality.
The organization also gained a stronger foundation for reusing institutional knowledge. Previous research became easier to access, helping teams avoid unnecessary duplication and make more confident business decisions.
Beyond time savings, the solution supported broader business value by helping teams accelerate decision-making, protect the value of research investments, and bring insights into strategic planning, customer experience initiatives, product development, and innovation work.
Facts
- Estimated time savings exceeded $1 million through year-end 2025 from research discovery and data mining
- Around 600 users had accessed the solution by year-end 2025
- After broader rollout and the introduction of AI summaries, users reported saving approximately 30 to 45 minutes per search
- More than 8,000 hours of data mining time saved since launch