Patent search crashed at 40M records. A serverless migration scaled capacity to 600M+ vectors with zero outages and ~$75k savings.
A patent analytics firm automates the high-stakes process of prior art discovery, searching hundreds of millions of global patents and academic papers to determine the strength of multi-million dollar lawsuits.
A self-hosted Milvus cluster became unstable and crashed repeatedly when scaling beyond 40 million records, failing to meet the strict recall...
“Our KPI for Pinecone is straightforward: how little time we spend thinking about it. Since we started, we haven’t had a single reliability issue, and that’s exactly what we need as a small team focused on building the product—not maintaining infrastructure.”
AI-powered prior art search and patent automation platform.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.