Case Study: The Intelligent Archive

Using RAG and agentic workflow to access a knowledge base and auto-generate new solutions

Initial Situation

A company in the project development sector faced the challenge of optimally utilizing its extensive project documentation, market research data, and important correspondence. This valuable information was stored in a digital archive, but accessing and utilizing it was time-consuming. Alpine Intelligence was commissioned to develop an innovative solution that not only facilitates information access but also enables proactive support in core processes.

Challenge

The central challenges were:

• Information Volume and Structure: The large volume of documents, often in unstructured formats like PDFs, made rapid and precise information retrieval difficult.
• Contextual Understanding in Searches: Conventional search methods often did not provide sufficiently context-related results.
• Utilization of Historical Data for New Projects: The potential to systematically learn from completed projects for new endeavors and to accelerate processes was not yet fully exploited.

Solution by Alpine Intelligence

In an iterative process with the client, Alpine Intelligence designed and implemented a tailor-made solution based on Retrieval-Augmented Generation (RAG). Within the scope of our comprehensive Innovation Consulting, it was ensured that the solution was optimally tailored to the needs of the project developer.

The core components of the solution are:

Intelligent Collection and Preparation of Documents in the Archive:

• Relevant texts are extracted from the data and converted into so-called vector embeddings using advanced AI models. These enable semantic, i.e., theme-based, similarity searches that go far beyond simple keyword searches.
• An automated process continuously collects new or changed documents in the archive.
• The documents are further enriched with additional data through analysis by an LLM, which is relevant for later queries but not semantically contained in the original document – this allows for a similarity search with a deeper understanding.

Context-Related Optimization of Search Queries:

• The system understands and refines user queries by considering the conversation history and industry-specific terminology. This leads to significantly more relevant search results.

From RAG to Agentic *:

• The system not only finds the most suitable documents but can also summarize the information contained therein into precise answers, cite the sources, and also generate more complex reports.
• RAG is just the beginning. Through an agent-based workflow, the system can also independently develop proposals or generate drafts for offers by accessing the collected knowledge in the archive and intelligently combining it – just as an employee would. Only the system is much faster.

Results

The solution implemented by Alpine Intelligence led to significant improvements:

• Reduced Time Spent on Information Searches: Employees find needed information much faster and can concentrate on their core tasks. Onboarding new employees is also significantly easier.
• Improved Quality and Relevance of Information: The answers and search results are more precise and better tailored to the respective query.
• Increased Efficiency through Automation*: The ability to have drafts for offers or solution proposals created automatically significantly speeds up the corresponding processes.
• Higher User Satisfaction and Better Knowledge Management: Trust in the available information and the ability to draw from the entirety of the company’s knowledge have increased.
• Proactive Matching of Archive Knowledge with New Project Requirements*: The system can automatically provide relevant information from completed projects as soon as new project requirements are defined.

Conclusion

Through innovation consulting and the implementation of an advanced RAG solution with agent-based workflows, Alpine Intelligence has helped the project development company to revolutionize its internal knowledge management. This not only leads to a significant increase in efficiency and improved decision-making but also makes it possible to proactively use the collected know-how for shaping future success.

Your Intelligent Archive

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The Intelligent Archive

* Agentic is currently in development