levelbuild Migrates No-Code Construction Workflow Platform to Google Cloud with AI Enhancements
levelbuild, a Germany-based technology company, migrated its no-code workflow and application management platform for the construction industry to Google Cloud to improve scalability, reduce latency, and enable AI-driven features. The legacy infrastructure limited performance and scalability while the company needed to integrate AI to enhance construction workflow efficiency for over 20,000 users. The solution involved migrating the platform to Google Cloud using serverless infrastructure including Cloud Run, BigQuery, AlloyDB, and AI-driven microservices with Vertex AI and Gemini-based models. AI capabilities include converting scanned docs to PDFs, deduplicating images, translating tabular data, summarizing emails, extracting to-do lists, transcribing and summarizing Google Meet video conferences, and sentiment analysis. Migration improved per-click latency by 75%, cut onboarding time by 75%, halved database costs, enhanced uptime and scalability, and accelerated platform development. Partnership with Seibert Group guided the AI integration and cloud migration process, ensuring GDPR compliance and performance improvements.
- Organization
- levelbuild
- Industry
- Manufacturing
- Location
- Germany
Reported outcomes
−75%
timeTime & speed
Strategic outcomes
Primary read
Use case focus
Showing 3 of 3
- 1AI-Driven Workflow Automation
- 2Cloud Migration
- 3AI Document Processing
- Legacy on-premises infrastructure and previous cloud provider limited scalability, increased latency, and hampered platform performance for a growing customer base.
- The platform needed better integration of AI to add new features that enhance productivity and efficiency in the construction industry workflows.
- Migrated the entire platform to Google Cloud employing serverless infrastructure with Cloud Run, BigQuery and AlloyDB, enabling resource sharing for better cost efficiency.
- Leveraged Vertex AI and Gemini-based models to create AI-driven microservices for tasks like email summarization, to-do extraction, video transcription, sentiment analysis, and document processing.
- Collaborated with Google Cloud partner Seibert Group to ensure smooth migration, performance benchmarking, and effective AI integration following GDPR compliance.
- Created plans for future AI agents to automate research, sentiment analytics, and RFP analysis to further optimize workflows.
- Reduced per-click latency by 75% and onboarding times by 75%, significantly improving user experience and accelerating adoption.
- Database costs were cut in half due to optimized consumption-based compute and shared resource architecture.
- Platform scalability and uptime improved, supporting 20,000+ users and processing 10 million daily transactions efficiently.
- AI features are enhancing productivity, enabling faster research and decision-making leading to stronger ROI for customers.
Implementation partners1
Sources & evidence1
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