50% Faster Knowledge Retrieval: How an Auto R&D Team Used AI to Eliminate Repeat Work and Improve Collaboration
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“It’s no longer about who you ask—it’s about what the AI already knows. That’s game-changing for us.” - R&D Head
Snapshot
- Industry: Automotive Research & Development
- Company Size: 100 People R&D Team in a global engineering company
- Challenge: Dispersed knowledge, inefficient collaboration, and onboarding delays
- Solution: BHyve AI Knowledge Base for unified, searchable, and collaborative R&D
- Results: 50% faster data retrieval, 60%+ of queries resolved by AI, improved remote team collaboration
Customer Introduction
A leading automotive research and development division, responsible for pioneering vehicle design and engineering, faced persistent challenges in knowledge discovery and collaboration. With multi-disciplinary teams working across calibration, prototyping, and design, the organization sought a smarter solution to improve how knowledge was stored, retrieved, and shared across projects and locations.
R&D Knowledge Challenges
- Fragmented Knowledge Systems: Key project data, technical artefacts, and catalogues were distributed across local drives and legacy systems.
- Manual Search Processes: Engineers relied heavily on Excel and shared folders, resulting in time-consuming, error-prone data retrieval.
- Lost Breakthroughs: Insights and innovations from one project or team weren’t easily discoverable by others, leading to duplicate efforts and missed opportunities.
- Poor Cross-Functional Collaboration: Teams across design, calibration, and prototyping struggled to align goals and share updates efficiently.
- Onboarding Challenges: New team members found it difficult to access historical project knowledge, delaying their ramp-up and productivity.
- Limited Search Intelligence: Legacy systems lacked smart indexing or semantic search, which made deep research insights difficult to uncover.
“We often realized two teams had solved the same problem weeks apart, unaware of each other’s work.” - R&D Manager
AI-Powered R&D Transformation
Centralized Repository
- Unified fragmented data from multiple systems into a single, easily searchable platform.
Generative AI Capabilities
- Delivered fast, contextually relevant answers and summaries to engineers' queries.
User-Centric Access
- Intuitive navigation encouraged frequent use and quick onboarding.
Collaborative Knowledge Management
- Teams could tag, organize, and contribute content in real-time.
Real-Time Search Utility
- Engineers actively searched for knowledge and resolved issues on the job, even while working remotely.
“Now our engineers can troubleshoot in real time—without having to wait for a response from another office.”
Impact Delivered
- 50% Faster Knowledge Retrieval: Engineers spent less time searching and more time building solutions.
- 60%+ Queries Resolved by AI: Reduced the reliance on subject matter experts and enabled self-service troubleshooting.
- Remote Collaboration at Scale: Teams working in similar domains across locations shared real-time fixes, minimizing delays and rework.
- Improved Knowledge Equity: Information was accessible to all, not just long-tenured employees.
Conclusion
“It’s no longer about who you ask—it’s about what the AI already knows. That’s game-changing for us.” - R&D Head