R&D Project Intelligence
A retrieval-augmented assistant for finding and summarizing research context across R&D project materials.
The problem
R&D projects generate vast amounts of information across multiple sources and formats. Project managers struggle to keep track of research findings, maintain context across team changes, and efficiently retrieve relevant information when making decisions.
Intended users
Research teams and project managers working across notes, papers, experimental results, and project communications.
Client work & development scope
The project notes describe development of a RAG system and integration with project tools to index, retrieve, and synthesize research information.
The solution
We developed a Retrieval-Augmented Generation system specifically for R&D project management. It integrates with existing project tools to index, retrieve, and synthesize information from research notes, experimental results, papers, and communication channels.
How the system fits together
- Research notes, papers & project records
- Indexing in a vector database
- Context-aware retrieval
- Research summary or answer
Conceptual flow based on the project notes. Specific storage, model, hosting, and permission configurations are not documented here.
Capabilities described in the project
- Context-aware retrieval
- Automatic research summaries
- Knowledge continuity
- Semantic search
- Project-tool integrations
- Research terminology support
Results and evaluation
The system reduced information retrieval time by 70% and improved decision-making by providing comprehensive research context. Project handovers became more efficient, with new team members getting up to speed 40% faster. Its contextual awareness also helped identify overlooked connections between research findings and reveal new research directions.
Evaluation considerations
- Document the source collection, task set, participant count, and baseline search tools.
- Measure time to a correct answer and retrieval relevance, not speed alone.
- Review summaries for unsupported statements and test missing, outdated, and conflicting material.
Limitations
Retrieval can miss relevant material, and generated summaries can omit context or introduce errors. Research decisions require source review. Document access and freshness must be addressed in any deployment.
What this means for a startup
For a startup building a knowledge product, the central workflow is connecting source material to useful retrieval and synthesis. Evaluation and source quality matter as much as the interface.
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