50% Faster Knowledge Retrieval: How an Auto R&D Team Used AI to Eliminate Repeat Work and Improve Collaboration
Case Snapshot
Automotive Research & Development
100 Employees
50% faster data retrieval, 60%+ of queries resolved by AI, improved remote team collaboration
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— Varroc
The Overview
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.
The Challenge
The R&D teams were burdened with scattered data, siloed knowledge, and outdated tools:
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.
The BHyve Solution
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.
The Business Impact
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.
“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
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