Migrating large-scale documentation is a complex challenge for enterprises, particularly when multiple teams rely on extensive data sets.
In this article, we explore the obstacles faced, the solution found, the adoption strategy followed, and the impressive results achieved with StackSpot AI. So far, the platform has impacted 20% of the pages requiring action and reduced document migration time by 85%. Read on to discover how!
Challenges in Document Migration
A company’s technology team needed to phase out its internal documentation management tool by the end of 2024. This required a robust solution to handle the migration of over 400,000 pages of content efficiently.
Manually transferring these documents posed two major hurdles:
- Time consumption: Each professional could migrate only about 6 pages per day.
- High costs: The process required a hefty team effort over a long stretch of time.
To address these issues, the team leveraged Python and StackSpot AI, a multi-agent platform developed by Zup Innovation. This approach accelerated the migration process while ensuring quality and consistency across documents.
Choosing the Right Solution
The team built a Python-based application capable of running a crawler—an automated program designed to navigate the API of the internal documentation management tool, extract structured data, and feed it into a generative AI model.
Python was selected for its flexibility, efficiency, and seamless integration with essential libraries, making it ideal for both backend and frontend development. StackSpot AI was incorporated to minimize cognitive load and expedite migration.
By structuring API responses (i.e., documentation pages) into fragments, the team used AI-driven prompts to adapt and standardize the content. This significantly enhanced content quality while reducing the effort required to analyze similar pages.
Moreover, StackSpot AI facilitated the creation of Remote Quick Commands—predefined instructions to automate specific actions, enabling even non-technical users to operate the tool through an intuitive interface.
These commands eliminated the need for manual application of content rewriting rules, seeing as they utilized Knowledge Sources—contextualized AI-driven resources that refined documentation according to governance standards. This ensured consistent formatting and allowed continuous interaction with AI for further enhancements.
Strategy for Implementation and Adoption
The Python application retrieved user-selected pages via the internal documentation tool’s API and stored them in JSON format, preserving the page hierarchy.
Users could then select specific pages for rewriting, triggering a Quick Command linked to a Knowledge Source that contained the content migration guidelines. The AI tool would then generate and suggest a refined version of the page.
Accelerating Adoption
Consider a team responsible for migrating 150 pages. Traditionally, the process would involve:
- Manually accessing each page
- Analyzing content and modification date
- Identifying outdated material
- Downloading and converting media to Markdown (where applicable).
StackSpot AI streamlined this workflow by leveraging its reporting feature, which identified obsolete pages (based on usage patterns) and recommended improvements. Additionally, AI-powered content analysis enabled teams to detect and summarize common elements across similar pages, suggest better formats and structures, and automate repetitive formatting and conversion tasks.
The tool further allowed users to:
- Generate reports on pages and subpages
- Assign priority tags in bulk
- Convert content into Markdown
- Export attachments for use in external tools
- Align documentation with governance standards
- Modify text dynamically with AI assistance.
Impressive Results
The integration of StackSpot AI yielded significant gains:
- 85% reduction in migration time: With StackSpot AI, the company could engage an even leaner migration team
- Faster content processing: Teams could consult, analyze, and download over 150 pages in less than five minutes
- Accelerated rewriting: With the tool’s assistance, teams were able to complete content revisions in under an hour
- 20% of actionable pages migrated rapidly.
Conclusion
The transition away from the legacy documentation management tool paved the way for innovation. By combining Python and StackSpot AI, the company successfully transformed its document migration process, achieving greater speed and consistency.
The newly developed tool empowered lean teams to deliver remarkable results in record time, positively impacting thousands of developers and end-users. Moreover, close collaboration with the documentation governance team ensured a balance between automation and human oversight.
The impressive outcomes—drastically reduced migration times and widespread adoption of the tool across the company’s tech teams—underscore the success of this initiative. This case exemplifies how AI-driven solutions can tackle complex operational challenges while fostering a more collaborative and efficient work environment.
Want to see StackSpot AI in action? Schedule a demo with our team today!
