Isolating data for 50,000 clients was operationally impossible. Multi-tenancy now serves 6.1M queries from a single instance.
A solo-founder led platform enabling companies to create custom AI chatbots from documentation, which surged in popularity after a viral launch generated 2.3 million impressions.
Viral growth exposed a critical flaw in the MVP, which could not scale to manage tens of thousands of isolated customer indexes without crashing....
“Weaviate stood out because it’s clearly designed for real production use cases, not just experimentation. It was the only solution with an efficient tenant-based system that scaled to our unique workload of tens of thousands of distinct segmented indexes.”
AI-powered chatbot builder for documentation and customer support.
Open-source vector database for building AI applications and search experiences.
Related implementations across industries and use cases
Managing storage consumed engineering bandwidth. Offloading infrastructure let the team focus on algorithms and reach #1 RAG accuracy.
Engineers spent weeks manually sharding. A serverless RAG pipeline now auto-scales 100 million vectors.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Engineers spent weeks manually sharding. A serverless RAG pipeline now auto-scales 100 million vectors.
5-10s latency broke call momentum. Migrating to Groq cut response time to 200ms, allowing the AI to guide reps instantly.
Scheduling 1,900 roles manually took days of back-and-forth. Conversational AI now books interviews instantly, syncing calendars.
Serial testing bottlenecked development. Now, parallelized checks validate hundreds of complex conversation paths in seconds.
SExperts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.